From 1fd58c467113a8143815ce1ebd4e82c81806588d Mon Sep 17 00:00:00 2001
From: Quarto GHA Workflow Runner <quarto-github-actions-publish@example.com>
Date: Mon, 28 Aug 2023 16:29:00 +0000
Subject: [PATCH] Built site for gh-pages

---
 .nojekyll                                     |    2 +-
 chapters/append/auth.html                     |  101 +-
 chapters/append/cheatsheets.html              | 1751 +++++++++++++++++
 chapters/append/lab-map.html                  |  133 +-
 chapters/intro-images/lab-arch.png            |  Bin 157003 -> 215670 bytes
 chapters/intro-images/mindmap.png             |  Bin 0 -> 132679 bytes
 chapters/intro.html                           |  160 +-
 chapters/sec1/1-0-sec-intro.html              |   98 +-
 chapters/sec1/1-1-env-as-code.html            |  135 +-
 chapters/sec1/1-2-proj-arch.html              |   93 +-
 chapters/sec1/1-3-data-access.html            |   99 +-
 chapters/sec1/1-4-monitor-log.html            |   93 +-
 chapters/sec1/1-5-deployments.html            |   97 +-
 .../2-4-docker.html => sec1/1-6-docker.html}  |  334 +---
 .../images/docker-lifecycle.png               |  Bin
 .../{sec2 => sec1}/images/docker-on-host.png  |  Bin
 chapters/sec1/images/repro-spectrum.png       |  Bin 273815 -> 265797 bytes
 chapters/sec2/2-0-sec-intro.html              |  151 +-
 chapters/sec2/2-1-cloud.html                  | 1038 ++++++++++
 chapters/sec2/2-1-cmd-line.html               |  733 -------
 chapters/sec2/2-2-cmd-line-use.html           | 1165 -----------
 .../sec2/{2-3-ssh.html => 2-2-cmd-line.html}  |  420 ++--
 chapters/sec2/2-3-linux.html                  | 1028 ++++++++++
 chapters/sec2/2-4-app-admin.html              |  980 +++++++++
 chapters/sec2/2-5-scale.html                  | 1009 ++++++++++
 chapters/sec2/2-6-networking.html             | 1010 ++++++++++
 .../{sec3/3-4-dns.html => sec2/2-7-dns.html}  |  366 ++--
 .../{sec3/3-5-ssl.html => sec2/2-8-ssl.html}  |  326 ++-
 chapters/sec2/images/directories.png          |  Bin 169681 -> 169682 bytes
 chapters/sec2/images/firewall-proxy.png       |  Bin 0 -> 194203 bytes
 chapters/sec2/images/perms-ex.png             |  Bin 0 -> 244148 bytes
 chapters/sec2/images/ssh.png                  |  Bin 145491 -> 148149 bytes
 chapters/sec2/images/ssl.png                  |  Bin 0 -> 194975 bytes
 chapters/sec3/3-0-sec-intro.html              |  170 +-
 chapters/sec3/3-1-cloud.html                  | 1118 -----------
 .../3-1-os-ds-in-ent.html}                    |  159 +-
 .../3-2-ent-networks.html}                    |  174 +-
 chapters/sec3/3-2-linux-admin.html            | 1577 ---------------
 .../4-3-auth.html => sec3/3-3-auth.html}      |  161 +-
 chapters/sec3/3-3-networking.html             | 1067 ----------
 .../3-4-ent-servers.html}                     |  155 +-
 chapters/sec3/3-6-servers.html                |  866 --------
 chapters/{sec4 => sec3}/images-auth/RBAC.png  |  Bin
 .../images-scaling/dev-test-prod.png          |  Bin
 .../images-scaling/lb-cluster.png             |  Bin
 .../sec3/images-traffic/namecheap-config.png  |  Bin 57767 -> 0 bytes
 chapters/sec3/images/instance-summary.png     |  Bin 73416 -> 0 bytes
 chapters/sec4/4-0-sec-intro.html              |  677 -------
 index.html                                    |   91 +-
 search.json                                   |  993 ++++++----
 sitemap.xml                                   |   92 +-
 51 files changed, 9079 insertions(+), 9543 deletions(-)
 create mode 100644 chapters/append/cheatsheets.html
 create mode 100644 chapters/intro-images/mindmap.png
 rename chapters/{sec2/2-4-docker.html => sec1/1-6-docker.html} (82%)
 rename chapters/{sec2 => sec1}/images/docker-lifecycle.png (100%)
 rename chapters/{sec2 => sec1}/images/docker-on-host.png (100%)
 create mode 100644 chapters/sec2/2-1-cloud.html
 delete mode 100644 chapters/sec2/2-1-cmd-line.html
 delete mode 100644 chapters/sec2/2-2-cmd-line-use.html
 rename chapters/sec2/{2-3-ssh.html => 2-2-cmd-line.html} (50%)
 create mode 100644 chapters/sec2/2-3-linux.html
 create mode 100644 chapters/sec2/2-4-app-admin.html
 create mode 100644 chapters/sec2/2-5-scale.html
 create mode 100644 chapters/sec2/2-6-networking.html
 rename chapters/{sec3/3-4-dns.html => sec2/2-7-dns.html} (65%)
 rename chapters/{sec3/3-5-ssl.html => sec2/2-8-ssl.html} (58%)
 create mode 100644 chapters/sec2/images/firewall-proxy.png
 create mode 100644 chapters/sec2/images/perms-ex.png
 create mode 100644 chapters/sec2/images/ssl.png
 delete mode 100644 chapters/sec3/3-1-cloud.html
 rename chapters/{sec4/4-1-os-ds-in-ent.html => sec3/3-1-os-ds-in-ent.html} (91%)
 rename chapters/{sec4/4-2-ent-networks.html => sec3/3-2-ent-networks.html} (86%)
 delete mode 100644 chapters/sec3/3-2-linux-admin.html
 rename chapters/{sec4/4-3-auth.html => sec3/3-3-auth.html} (90%)
 delete mode 100644 chapters/sec3/3-3-networking.html
 rename chapters/{sec4/4-4-ent-servers.html => sec3/3-4-ent-servers.html} (91%)
 delete mode 100644 chapters/sec3/3-6-servers.html
 rename chapters/{sec4 => sec3}/images-auth/RBAC.png (100%)
 rename chapters/{sec4 => sec3}/images-scaling/dev-test-prod.png (100%)
 rename chapters/{sec4 => sec3}/images-scaling/lb-cluster.png (100%)
 delete mode 100644 chapters/sec3/images-traffic/namecheap-config.png
 delete mode 100644 chapters/sec3/images/instance-summary.png
 delete mode 100644 chapters/sec4/4-0-sec-intro.html

diff --git a/.nojekyll b/.nojekyll
index 51416ff2e..93c056512 100644
--- a/.nojekyll
+++ b/.nojekyll
@@ -1 +1 @@
-3e1f9aa3
\ No newline at end of file
+862eb966
\ No newline at end of file
diff --git a/chapters/append/auth.html b/chapters/append/auth.html
index 7be602c4b..0794b3c1d 100644
--- a/chapters/append/auth.html
+++ b/chapters/append/auth.html
@@ -31,7 +31,7 @@
 <script src="../../site_libs/quarto-search/quarto-search.js"></script>
 <meta name="quarto:offset" content="../../">
 <link href="../../chapters/append/lab-map.html" rel="next">
-<link href="../../chapters/sec4/4-4-ent-servers.html" rel="prev">
+<link href="../../chapters/sec3/3-4-ent-servers.html" rel="prev">
 <script src="../../site_libs/quarto-html/quarto.js"></script>
 <script src="../../site_libs/quarto-html/popper.min.js"></script>
 <script src="../../site_libs/quarto-html/tippy.umd.min.js"></script>
@@ -177,13 +177,19 @@
   <a href="../../chapters/sec1/1-5-deployments.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">5</span>&nbsp; <span class="chapter-title">Deployments and code promotion</span></span></a>
   </div>
+</li>
+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/sec1/1-6-docker.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">6</span>&nbsp; <span class="chapter-title">Demystifying Docker</span></span></a>
+  </div>
 </li>
       </ul>
   </li>
         <li class="sidebar-item sidebar-item-section">
       <div class="sidebar-item-container"> 
             <a href="../../chapters/sec2/2-0-sec-intro.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text">IT/Admin Tools</span></a>
+ <span class="menu-text">IT/Admin for Data Science</span></a>
           <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-2" aria-expanded="true" aria-label="Toggle section">
             <i class="bi bi-chevron-right ms-2"></i>
           </a> 
@@ -191,121 +197,98 @@
       <ul id="quarto-sidebar-section-2" class="collapse list-unstyled sidebar-section depth1 show">  
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec2/2-1-cmd-line.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">6</span>&nbsp; <span class="chapter-title">Opening the Command Line</span></span></a>
+  <a href="../../chapters/sec2/2-1-cloud.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">7</span>&nbsp; <span class="chapter-title">The Cloud</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec2/2-2-cmd-line-use.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">7</span>&nbsp; <span class="chapter-title">Using the Command Line</span></span></a>
+  <a href="../../chapters/sec2/2-2-cmd-line.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">8</span>&nbsp; <span class="chapter-title">Customizing the command line</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec2/2-3-ssh.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">8</span>&nbsp; <span class="chapter-title">Secure server connections with SSH</span></span></a>
+  <a href="../../chapters/sec2/2-3-linux.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">9</span>&nbsp; <span class="chapter-title">Intro to Linux Administration</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec2/2-4-docker.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">9</span>&nbsp; <span class="chapter-title">Demystifying Docker</span></span></a>
+  <a href="../../chapters/sec2/2-4-app-admin.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Application administration</span></span></a>
   </div>
 </li>
-      </ul>
-  </li>
-        <li class="sidebar-item sidebar-item-section">
-      <div class="sidebar-item-container"> 
-            <a href="../../chapters/sec3/3-0-sec-intro.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text">IT/Admin for Data Science</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-3" aria-expanded="true" aria-label="Toggle section">
-            <i class="bi bi-chevron-right ms-2"></i>
-          </a> 
-      </div>
-      <ul id="quarto-sidebar-section-3" class="collapse list-unstyled sidebar-section depth1 show">  
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-1-cloud.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Getting Started with the Cloud</span></span></a>
+  <a href="../../chapters/sec2/2-5-scale.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Server Resources and Scaling</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-2-linux-admin.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Basic Linux SysAdmin</span></span></a>
-  </div>
-</li>
-          <li class="sidebar-item">
-  <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-3-networking.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-6-networking.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">12</span>&nbsp; <span class="chapter-title">Intro to Computer Networks</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-4-dns.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-7-dns.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">13</span>&nbsp; <span class="chapter-title">DNS allows for human-readable addresses</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-5-ssl.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-8-ssl.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">14</span>&nbsp; <span class="chapter-title">You should use SSL/HTTPS</span></span></a>
   </div>
-</li>
-          <li class="sidebar-item">
-  <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-6-servers.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Choosing the right server for you</span></span></a>
-  </div>
 </li>
       </ul>
   </li>
         <li class="sidebar-item sidebar-item-section">
       <div class="sidebar-item-container"> 
-            <a href="../../chapters/sec4/4-0-sec-intro.html" class="sidebar-item-text sidebar-link">
+            <a href="../../chapters/sec3/3-0-sec-intro.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text">Making it Enterprise-Grade</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true" aria-label="Toggle section">
+          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-3" aria-expanded="true" aria-label="Toggle section">
             <i class="bi bi-chevron-right ms-2"></i>
           </a> 
       </div>
-      <ul id="quarto-sidebar-section-4" class="collapse list-unstyled sidebar-section depth1 show">  
+      <ul id="quarto-sidebar-section-3" class="collapse list-unstyled sidebar-section depth1 show">  
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec4/4-1-os-ds-in-ent.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></a>
+  <a href="../../chapters/sec3/3-1-os-ds-in-ent.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec4/4-2-ent-networks.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></a>
+  <a href="../../chapters/sec3/3-2-ent-networks.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec4/4-3-auth.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></a>
+  <a href="../../chapters/sec3/3-3-auth.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec4/4-4-ent-servers.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">19</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></a>
+  <a href="../../chapters/sec3/3-4-ent-servers.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></a>
   </div>
 </li>
       </ul>
   </li>
         <li class="sidebar-item sidebar-item-section">
       <div class="sidebar-item-container"> 
-            <a class="sidebar-item-text sidebar-link text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-5" aria-expanded="true">
+            <a class="sidebar-item-text sidebar-link text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true">
  <span class="menu-text">Appendices</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-5" aria-expanded="true" aria-label="Toggle section">
+          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true" aria-label="Toggle section">
             <i class="bi bi-chevron-right ms-2"></i>
           </a> 
       </div>
-      <ul id="quarto-sidebar-section-5" class="collapse list-unstyled sidebar-section depth1 show">  
+      <ul id="quarto-sidebar-section-4" class="collapse list-unstyled sidebar-section depth1 show">  
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
   <a href="../../chapters/append/auth.html" class="sidebar-item-text sidebar-link active">
@@ -317,6 +300,12 @@
   <a href="../../chapters/append/lab-map.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">B</span>&nbsp; <span class="chapter-title">Lab Map</span></span></a>
   </div>
+</li>
+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/append/cheatsheets.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">C</span>&nbsp; <span class="chapter-title">Cheatsheets</span></span></a>
+  </div>
 </li>
       </ul>
   </li>
@@ -358,7 +347,7 @@ <h1 class="title"><span id="sec-append-auth" class="quarto-section-identifier">A
 
 </header>
 
-<p><a href="../sec4/4-3-auth.html">Chapter&nbsp;<span>18</span></a> was all about a conceptual understanding of how auth works and what SSO is. In that chapter, we briefly mentioned a few technologies used to do auth, including LDAP/AD, SAML, and OIDC/OAuth2.0.</p>
+<p><a href="../sec3/3-3-auth.html">Chapter&nbsp;<span>17</span></a> was all about a conceptual understanding of how auth works and what SSO is. In that chapter, we briefly mentioned a few technologies used to do auth, including LDAP/AD, SAML, and OIDC/OAuth2.0.</p>
 <p>In this chapter we’ll get a little deeper into the actual technologies that underlies different auth. Having a basic understanding of these technologies can be helpful when you’re talking to IT/Admins. That said, it’s definitely beyond the scope of most people’s need to understand, which is why this is an appendix.</p>
 <p>In terms of auth technologies, the biggest distinction is between “token-based” systems that can do SSO and others that that cannot. There is also a distinction between systems that are considered modern and those that are more legacy systems.</p>
 <p><strong>Auth Technologies by Type</strong></p>
@@ -410,7 +399,7 @@ <h1 class="title"><span id="sec-append-auth" class="quarto-section-identifier">A
 </tr>
 </tbody>
 </table>
-<p>As we went over in <a href="../sec4/4-3-auth.html">Chapter&nbsp;<span>18</span></a>, the basic distinction is that in credential-based systems, users provide their credentials to every system to login. The system passes the credentials along to a central store where they’re verified and authentication is returned. Authorization has to be done at the service level.</p>
+<p>As we went over in <a href="../sec3/3-3-auth.html">Chapter&nbsp;<span>17</span></a>, the basic distinction is that in credential-based systems, users provide their credentials to every system to login. The system passes the credentials along to a central store where they’re verified and authentication is returned. Authorization has to be done at the service level.</p>
 <p>That’s different than a token-based system. In a token based system, users get a token directly from a central authority. They then take that ticket to each system when they try to access it. The system checks the validity of the ticket and responds accordingly.</p>
 <p>This sounds like a subtle difference, but it’s extremely powerful. In a credential-based system, users have to provide their credentials to each service. This means the service has to be secure enough for those credentials. If you’ve just got a token or ticket, you don’t have to trust the service nearly as much because it never sees your credentials.</p>
 <p>The other huge distinction is about session expiration. In most systems, you don’t have to re-authenticate every single time you access it. In a credential-based system, that means that you usually trade your credentials for a cookie issued by the service. Again, you’ve got to trust the service to properly issue and expire that cookie. And even if you trust the service, you’ve got to separately set the timeout for each service. And if you want to revoke it, no can do.</p>
@@ -736,8 +725,8 @@ <h2 data-number="A.5" class="anchored" data-anchor-id="oauth-saml"><span class="
 </script>
 <nav class="page-navigation">
   <div class="nav-page nav-page-previous">
-      <a href="../../chapters/sec4/4-4-ent-servers.html" class="pagination-link">
-        <i class="bi bi-arrow-left-short"></i> <span class="nav-page-text"><span class="chapter-number">19</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span>
+      <a href="../../chapters/sec3/3-4-ent-servers.html" class="pagination-link">
+        <i class="bi bi-arrow-left-short"></i> <span class="nav-page-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span>
       </a>          
   </div>
   <div class="nav-page nav-page-next">
diff --git a/chapters/append/cheatsheets.html b/chapters/append/cheatsheets.html
new file mode 100644
index 000000000..8538b326f
--- /dev/null
+++ b/chapters/append/cheatsheets.html
@@ -0,0 +1,1751 @@
+<!DOCTYPE html>
+<html xmlns="http://www.w3.org/1999/xhtml" lang="en" xml:lang="en"><head>
+
+<meta charset="utf-8">
+<meta name="generator" content="quarto-1.3.353">
+
+<meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes">
+
+
+<title>DevOps for Data Science - Appendix C — Cheatsheets</title>
+<style>
+code{white-space: pre-wrap;}
+span.smallcaps{font-variant: small-caps;}
+div.columns{display: flex; gap: min(4vw, 1.5em);}
+div.column{flex: auto; overflow-x: auto;}
+div.hanging-indent{margin-left: 1.5em; text-indent: -1.5em;}
+ul.task-list{list-style: none;}
+ul.task-list li input[type="checkbox"] {
+  width: 0.8em;
+  margin: 0 0.8em 0.2em -1em; /* quarto-specific, see https://github.com/quarto-dev/quarto-cli/issues/4556 */ 
+  vertical-align: middle;
+}
+/* CSS for syntax highlighting */
+pre > code.sourceCode { white-space: pre; position: relative; }
+pre > code.sourceCode > span { display: inline-block; line-height: 1.25; }
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+.sourceCode { overflow: visible; }
+code.sourceCode > span { color: inherit; text-decoration: inherit; }
+div.sourceCode { margin: 1em 0; }
+pre.sourceCode { margin: 0; }
+@media screen {
+div.sourceCode { overflow: auto; }
+}
+@media print {
+pre > code.sourceCode { white-space: pre-wrap; }
+pre > code.sourceCode > span { text-indent: -5em; padding-left: 5em; }
+}
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+ <span class="menu-text"><span class="chapter-number">12</span>&nbsp; <span class="chapter-title">Intro to Computer Networks</span></span></a>
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+ <span class="menu-text"><span class="chapter-number">13</span>&nbsp; <span class="chapter-title">DNS allows for human-readable addresses</span></span></a>
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+      <div class="sidebar-item-container"> 
+            <a href="../../chapters/sec3/3-0-sec-intro.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text">Making it Enterprise-Grade</span></a>
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+ <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></a>
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+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/sec3/3-2-ent-networks.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></a>
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+  <a href="../../chapters/sec3/3-3-auth.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></a>
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+  <a href="../../chapters/sec3/3-4-ent-servers.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></a>
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+        <nav id="TOC" role="doc-toc" class="toc-active">
+    <h2 id="toc-title">Table of contents</h2>
+   
+  <ul>
+  <li><a href="#cheat-docker" id="toc-cheat-docker" class="nav-link active" data-scroll-target="#cheat-docker"><span class="header-section-number">C.1</span> Docker</a>
+  <ul class="collapse">
+  <li><a href="#docker-cli-commands" id="toc-docker-cli-commands" class="nav-link" data-scroll-target="#docker-cli-commands"><span class="header-section-number">C.1.1</span> Docker CLI Commands</a></li>
+  <li><a href="#flags-for-docker-run" id="toc-flags-for-docker-run" class="nav-link" data-scroll-target="#flags-for-docker-run"><span class="header-section-number">C.1.2</span> Flags for <code>docker run</code></a></li>
+  <li><a href="#dockerfile-commands" id="toc-dockerfile-commands" class="nav-link" data-scroll-target="#dockerfile-commands"><span class="header-section-number">C.1.3</span> Dockerfile Commands</a></li>
+  </ul></li>
+  <li><a href="#cloud-services" id="toc-cloud-services" class="nav-link" data-scroll-target="#cloud-services"><span class="header-section-number">C.2</span> Cloud Services</a></li>
+  <li><a href="#cheat-cli" id="toc-cheat-cli" class="nav-link" data-scroll-target="#cheat-cli"><span class="header-section-number">C.3</span> Command Line</a>
+  <ul class="collapse">
+  <li><a href="#general-command-line" id="toc-general-command-line" class="nav-link" data-scroll-target="#general-command-line"><span class="header-section-number">C.3.1</span> General Command Line</a></li>
+  <li><a href="#linux-navigation" id="toc-linux-navigation" class="nav-link" data-scroll-target="#linux-navigation"><span class="header-section-number">C.3.2</span> Linux Navigation</a></li>
+  <li><a href="#reading-text-files" id="toc-reading-text-files" class="nav-link" data-scroll-target="#reading-text-files"><span class="header-section-number">C.3.3</span> Reading Text Files</a></li>
+  <li><a href="#manipulating-files" id="toc-manipulating-files" class="nav-link" data-scroll-target="#manipulating-files"><span class="header-section-number">C.3.4</span> Manipulating Files</a></li>
+  <li><a href="#move-things-tofrom-server" id="toc-move-things-tofrom-server" class="nav-link" data-scroll-target="#move-things-tofrom-server"><span class="header-section-number">C.3.5</span> Move things to/from server</a></li>
+  <li><a href="#write-files-from-the-command-line" id="toc-write-files-from-the-command-line" class="nav-link" data-scroll-target="#write-files-from-the-command-line"><span class="header-section-number">C.3.6</span> Write files from the command line</a></li>
+  <li><a href="#command-line-text-editors-vim-nano" id="toc-command-line-text-editors-vim-nano" class="nav-link" data-scroll-target="#command-line-text-editors-vim-nano"><span class="header-section-number">C.3.7</span> Command Line Text Editors (Vim + Nano)</a></li>
+  </ul></li>
+  <li><a href="#cheat-file" id="toc-cheat-file" class="nav-link" data-scroll-target="#cheat-file"><span class="header-section-number">C.4</span> Cheatsheet: Users and Permissions</a>
+  <ul class="collapse">
+  <li><a href="#users" id="toc-users" class="nav-link" data-scroll-target="#users"><span class="header-section-number">C.4.1</span> Users</a></li>
+  <li><a href="#permissions" id="toc-permissions" class="nav-link" data-scroll-target="#permissions"><span class="header-section-number">C.4.2</span> Permissions</a></li>
+  </ul></li>
+  <li><a href="#cheat-ssh" id="toc-cheat-ssh" class="nav-link" data-scroll-target="#cheat-ssh"><span class="header-section-number">C.5</span> Cheatsheet: <code>ssh</code></a></li>
+  <li><a href="#cheat-admin" id="toc-cheat-admin" class="nav-link" data-scroll-target="#cheat-admin"><span class="header-section-number">C.6</span> Cheatsheet: Linux Admin Commands</a>
+  <ul class="collapse">
+  <li><a href="#users-1" id="toc-users-1" class="nav-link" data-scroll-target="#users-1"><span class="header-section-number">C.6.1</span> Users</a></li>
+  <li><a href="#permissions-1" id="toc-permissions-1" class="nav-link" data-scroll-target="#permissions-1"><span class="header-section-number">C.6.2</span> Permissions</a></li>
+  <li><a href="#install-applications-ubuntu" id="toc-install-applications-ubuntu" class="nav-link" data-scroll-target="#install-applications-ubuntu"><span class="header-section-number">C.6.3</span> Install applications (Ubuntu)</a></li>
+  <li><a href="#storage" id="toc-storage" class="nav-link" data-scroll-target="#storage"><span class="header-section-number">C.6.4</span> Storage</a></li>
+  <li><a href="#processes" id="toc-processes" class="nav-link" data-scroll-target="#processes"><span class="header-section-number">C.6.5</span> Processes</a></li>
+  <li><a href="#networking" id="toc-networking" class="nav-link" data-scroll-target="#networking"><span class="header-section-number">C.6.6</span> Networking</a></li>
+  <li><a href="#the-path" id="toc-the-path" class="nav-link" data-scroll-target="#the-path"><span class="header-section-number">C.6.7</span> The path</a></li>
+  </ul></li>
+  <li><a href="#cheat-ports" id="toc-cheat-ports" class="nav-link" data-scroll-target="#cheat-ports"><span class="header-section-number">C.7</span> Cheatsheet: IP Addresses and Ports</a>
+  <ul class="collapse">
+  <li><a href="#special-ip-addresses" id="toc-special-ip-addresses" class="nav-link" data-scroll-target="#special-ip-addresses"><span class="header-section-number">C.7.1</span> Special IP Addresses</a></li>
+  <li><a href="#special-ports" id="toc-special-ports" class="nav-link" data-scroll-target="#special-ports"><span class="header-section-number">C.7.2</span> Special Ports</a></li>
+  </ul></li>
+  <li><a href="#cheatsheet-debugging-tips" id="toc-cheatsheet-debugging-tips" class="nav-link" data-scroll-target="#cheatsheet-debugging-tips"><span class="header-section-number">C.8</span> Cheatsheet: Debugging Tips</a>
+  <ul class="collapse">
+  <li><a href="#check-storage-usage" id="toc-check-storage-usage" class="nav-link" data-scroll-target="#check-storage-usage"><span class="header-section-number">C.8.1</span> Check storage usage</a></li>
+  <li><a href="#look-at-whats-running" id="toc-look-at-whats-running" class="nav-link" data-scroll-target="#look-at-whats-running"><span class="header-section-number">C.8.2</span> Look at what’s running</a></li>
+  <li><a href="#make-sure-the-right-ports-are-open" id="toc-make-sure-the-right-ports-are-open" class="nav-link" data-scroll-target="#make-sure-the-right-ports-are-open"><span class="header-section-number">C.8.3</span> Make sure the right ports are open</a></li>
+  <li><a href="#check-your-path" id="toc-check-your-path" class="nav-link" data-scroll-target="#check-your-path"><span class="header-section-number">C.8.4</span> Check your path</a></li>
+  </ul></li>
+  <li><a href="#comprehension-questions" id="toc-comprehension-questions" class="nav-link" data-scroll-target="#comprehension-questions"><span class="header-section-number">C.9</span> Comprehension Questions</a></li>
+  </ul>
+<div class="toc-actions"><div><i class="bi bi-github"></i></div><div class="action-links"><p><a href="https://github.com/akgold/do4ds/edit/main/chapters/append/cheatsheets.qmd" class="toc-action">Edit this page</a></p></div></div></nav>
+    </div>
+<!-- main -->
+<main class="content" id="quarto-document-content">
+
+<header id="title-block-header" class="quarto-title-block default">
+<div class="quarto-title">
+<h1 class="title"><span id="sec-append-cheat" class="quarto-section-identifier">Appendix C — Cheatsheets</span></h1>
+</div>
+
+
+
+<div class="quarto-title-meta">
+
+    
+  
+    
+  </div>
+  
+
+</header>
+
+<section id="cheat-docker" class="level2" data-number="C.1">
+<h2 data-number="C.1" class="anchored" data-anchor-id="cheat-docker"><span class="header-section-number">C.1</span> Docker</h2>
+<section id="docker-cli-commands" class="level3" data-number="C.1.1">
+<h3 data-number="C.1.1" class="anchored" data-anchor-id="docker-cli-commands"><span class="header-section-number">C.1.1</span> Docker CLI Commands</h3>
+<table class="table">
+<colgroup>
+<col style="width: 3%">
+<col style="width: 18%">
+<col style="width: 29%">
+<col style="width: 49%">
+</colgroup>
+<thead>
+<tr class="header">
+<th>Stage</th>
+<th>Command</th>
+<th>What it does</th>
+<th>Notes and helpful options</th>
+</tr>
+</thead>
+<tbody>
+<tr class="odd">
+<td>Build</td>
+<td><code>docker build &lt;directory&gt;</code></td>
+<td>Builds a directory containing a Dockerfile into an image.</td>
+<td><code>-t &lt;name:tag&gt;</code> provide a name to the container. <code>tag</code> is optional, defaults to <code>latest</code>.</td>
+</tr>
+<tr class="even">
+<td>Move</td>
+<td><code>docker push &lt;image&gt;</code></td>
+<td>Push a container to a registry.</td>
+<td></td>
+</tr>
+<tr class="odd">
+<td>Move</td>
+<td><code>docker pull &lt;image&gt;</code></td>
+<td>Pull a container from a registry.</td>
+<td>Rarely used because <code>run</code> pulls the container if needed.</td>
+</tr>
+<tr class="even">
+<td>Run</td>
+<td><code>docker run &lt;image&gt;</code></td>
+<td>Run a container.</td>
+<td>See flags in next table.</td>
+</tr>
+<tr class="odd">
+<td>Run</td>
+<td><code>docker stop &lt;container&gt;</code></td>
+<td>Stop a running container.</td>
+<td><code>docker kill</code> can be used if <code>stop</code> fails.</td>
+</tr>
+<tr class="even">
+<td>Run</td>
+<td><code>docker ps</code></td>
+<td>List containers.</td>
+<td>Useful to get running container id to do things to it.</td>
+</tr>
+<tr class="odd">
+<td>Run</td>
+<td><code>docker exec &lt;container&gt; &lt;command&gt;</code></td>
+<td>Run a command inside a running container.</td>
+<td>Basically always used to open a shell in a container with <code>docker exec -it &lt;container&gt; /bin/bash</code></td>
+</tr>
+<tr class="even">
+<td>Run</td>
+<td><code>docker logs &lt;container&gt;</code></td>
+<td>Views logs for a container.</td>
+<td></td>
+</tr>
+</tbody>
+</table>
+</section>
+<section id="flags-for-docker-run" class="level3" data-number="C.1.2">
+<h3 data-number="C.1.2" class="anchored" data-anchor-id="flags-for-docker-run"><span class="header-section-number">C.1.2</span> Flags for <code>docker run</code></h3>
+<table class="table">
+<caption><em>Reminder: Order for <code>-p</code> and <code>-v</code> is <code>&lt;host&gt;:&lt;container&gt;</code></em></caption>
+<colgroup>
+<col style="width: 14%">
+<col style="width: 33%">
+<col style="width: 52%">
+</colgroup>
+<thead>
+<tr class="header">
+<th>Flag</th>
+<th>Effect</th>
+<th>Notes</th>
+</tr>
+</thead>
+<tbody>
+<tr class="odd">
+<td><code>--name &lt;name&gt;</code></td>
+<td>Give a name to the running container.</td>
+<td>Optional. Will be auto-assigned if not provided.</td>
+</tr>
+<tr class="even">
+<td><code>--rm</code></td>
+<td>Remove container when its stopped.</td>
+<td>Don’t use in production. You probably want to inspect failed containers.</td>
+</tr>
+<tr class="odd">
+<td><code>-d</code></td>
+<td>Detach container (don’t block the terminal).</td>
+<td>Almost always used in production.</td>
+</tr>
+<tr class="even">
+<td><code>-p &lt;port&gt;:&lt;port&gt;</code></td>
+<td>Publish port from inside container to outside.</td>
+<td>Needed if you want to access an app or API running inside the container.</td>
+</tr>
+<tr class="odd">
+<td><code>-v &lt;dir&gt;:&lt;dir&gt;</code></td>
+<td>Mount volume into the container.</td>
+<td></td>
+</tr>
+</tbody>
+</table>
+</section>
+<section id="dockerfile-commands" class="level3" data-number="C.1.3">
+<h3 data-number="C.1.3" class="anchored" data-anchor-id="dockerfile-commands"><span class="header-section-number">C.1.3</span> Dockerfile Commands</h3>
+<p>These are the commands that go in a Dockerfile when you’re building it.</p>
+<table class="table">
+<colgroup>
+<col style="width: 9%">
+<col style="width: 60%">
+<col style="width: 29%">
+</colgroup>
+<thead>
+<tr class="header">
+<th>Command</th>
+<th>Purpose</th>
+<th>Example</th>
+</tr>
+</thead>
+<tbody>
+<tr class="odd">
+<td><code>FROM</code></td>
+<td>Indicate base container.</td>
+<td><code>FROM rocker/r-ver:4.1.0</code></td>
+</tr>
+<tr class="even">
+<td><code>RUN</code></td>
+<td>Run a command when building.</td>
+<td><code>RUN apt-get update</code></td>
+</tr>
+<tr class="odd">
+<td><code>COPY</code></td>
+<td>Copy from build directory into the container.</td>
+<td><code>COPY . /app/</code></td>
+</tr>
+<tr class="even">
+<td><code>CMD</code></td>
+<td>Specify the command to run when the container starts.</td>
+<td><code>CMD quarto render .</code></td>
+</tr>
+</tbody>
+</table>
+</section>
+</section>
+<section id="cloud-services" class="level2" data-number="C.2">
+<h2 data-number="C.2" class="anchored" data-anchor-id="cloud-services"><span class="header-section-number">C.2</span> Cloud Services</h2>
+<table class="table">
+<colgroup>
+<col style="width: 20%">
+<col style="width: 36%">
+<col style="width: 21%">
+<col style="width: 21%">
+</colgroup>
+<thead>
+<tr class="header">
+<th>Service</th>
+<th>AWS</th>
+<th>Azure</th>
+<th>GCP</th>
+</tr>
+</thead>
+<tbody>
+<tr class="odd">
+<td>Kubernetes cluster</td>
+<td>EKS (Elastic Kubernetes Service) or Fargate</td>
+<td>AKS (Azure Kubernetes Service)</td>
+<td>GKE (Google Kubernetes Engine)</td>
+</tr>
+<tr class="even">
+<td>Run a container /application</td>
+<td>ECS (Elastic Container Service) or Elastic Beanstalk</td>
+<td>Azure Container Apps</td>
+<td>Google App Engine</td>
+</tr>
+<tr class="odd">
+<td>Run an API</td>
+<td>Lambda</td>
+<td>Azure Functions</td>
+<td>Google Cloud Functions</td>
+</tr>
+<tr class="even">
+<td>Database</td>
+<td>RDS or Reds hift[^2-1-cloud-8]</td>
+<td>Azure Database</td>
+<td>Google Cloud SQL</td>
+</tr>
+<tr class="odd">
+<td>ML Platform</td>
+<td>SageMaker</td>
+<td>Azure ML</td>
+<td>Vertex AI</td>
+</tr>
+</tbody>
+</table>
+</section>
+<section id="cheat-cli" class="level2" data-number="C.3">
+<h2 data-number="C.3" class="anchored" data-anchor-id="cheat-cli"><span class="header-section-number">C.3</span> Command Line</h2>
+<section id="general-command-line" class="level3" data-number="C.3.1">
+<h3 data-number="C.3.1" class="anchored" data-anchor-id="general-command-line"><span class="header-section-number">C.3.1</span> General Command Line</h3>
+<table class="table">
+<thead>
+<tr class="header">
+<th>Symbol</th>
+<th>What it is</th>
+</tr>
+</thead>
+<tbody>
+<tr class="odd">
+<td><code>man &lt;command&gt;</code></td>
+<td>Open manual for <code>command</code></td>
+</tr>
+<tr class="even">
+<td><code>q</code></td>
+<td>Quit the current screen</td>
+</tr>
+<tr class="odd">
+<td><code>\</code></td>
+<td>Continue bash command on new line</td>
+</tr>
+<tr class="even">
+<td><code>ctrl + c</code></td>
+<td>Quit current execution</td>
+</tr>
+</tbody>
+</table>
+</section>
+<section id="linux-navigation" class="level3" data-number="C.3.2">
+<h3 data-number="C.3.2" class="anchored" data-anchor-id="linux-navigation"><span class="header-section-number">C.3.2</span> Linux Navigation</h3>
+<table class="table">
+<colgroup>
+<col style="width: 18%">
+<col style="width: 38%">
+<col style="width: 38%">
+</colgroup>
+<thead>
+<tr class="header">
+<th>Command</th>
+<th>What it does/is</th>
+<th>Notes + Helpful options</th>
+</tr>
+</thead>
+<tbody>
+<tr class="odd">
+<td><code>/</code></td>
+<td>System root or file path separator</td>
+<td></td>
+</tr>
+<tr class="even">
+<td><code>.</code></td>
+<td>current working directory</td>
+<td></td>
+</tr>
+<tr class="odd">
+<td><code>..</code></td>
+<td>Parent of working directory</td>
+<td></td>
+</tr>
+<tr class="even">
+<td><code>~</code></td>
+<td>Home directory of the current user</td>
+<td></td>
+</tr>
+<tr class="odd">
+<td><code>ls &lt;dir&gt;</code></td>
+<td>List objects in a directory</td>
+<td><p><code>-l</code> - format as list</p>
+<p><code>-a</code> - all (include hidden files that start with <code>.</code>)</p></td>
+</tr>
+<tr class="even">
+<td><code>pwd</code></td>
+<td>Print working directory</td>
+<td></td>
+</tr>
+<tr class="odd">
+<td><code>cd &lt;dir&gt;</code></td>
+<td>Change directory</td>
+<td>Can use relative or absolute paths</td>
+</tr>
+</tbody>
+</table>
+</section>
+<section id="reading-text-files" class="level3" data-number="C.3.3">
+<h3 data-number="C.3.3" class="anchored" data-anchor-id="reading-text-files"><span class="header-section-number">C.3.3</span> Reading Text Files</h3>
+<table class="table">
+<colgroup>
+<col style="width: 31%">
+<col style="width: 31%">
+<col style="width: 31%">
+</colgroup>
+<thead>
+<tr class="header">
+<th>Command</th>
+<th>What it does</th>
+<th>Notes + Helpful options</th>
+</tr>
+</thead>
+<tbody>
+<tr class="odd">
+<td><code>cat &lt;file&gt;</code></td>
+<td>Print a file from the top.</td>
+<td></td>
+</tr>
+<tr class="even">
+<td><code>less &lt;file&gt;</code></td>
+<td>Print a file, but just a little.</td>
+<td><p>Can be very helpful to look at a few rows of csv.</p>
+<p>Lazily reads lines, so can be <em>much</em> faster than <code>cat</code> for big files.</p></td>
+</tr>
+<tr class="odd">
+<td><code>head &lt;file&gt;</code></td>
+<td>Look at the beginning of a file.</td>
+<td>Defaults to 10 lines, can specify a different number with <code>-n &lt;n&gt;</code>.</td>
+</tr>
+<tr class="even">
+<td><code>tail &lt;file&gt;</code></td>
+<td>Look at the end of a file.</td>
+<td><p>Useful for logs where the newest part is last.</p>
+<p>The <code>-f</code> flag is useful to follow for a live view.</p></td>
+</tr>
+<tr class="odd">
+<td><code>g r    e p &lt;expression&gt;</code></td>
+<td>Search a file using regex.</td>
+<td><p>Writing regex can be a pain. I suggest testing expressions on regex101.com.</p>
+<p>Often useful in combination with the pipe.</p></td>
+</tr>
+<tr class="even">
+<td><code>|</code></td>
+<td>The pipe</td>
+<td></td>
+</tr>
+</tbody>
+</table>
+</section>
+<section id="manipulating-files" class="level3" data-number="C.3.4">
+<h3 data-number="C.3.4" class="anchored" data-anchor-id="manipulating-files"><span class="header-section-number">C.3.4</span> Manipulating Files</h3>
+<table class="table">
+<colgroup>
+<col style="width: 29%">
+<col style="width: 33%">
+<col style="width: 33%">
+</colgroup>
+<thead>
+<tr class="header">
+<th>Command</th>
+<th>What it does/is</th>
+<th>Notes + Helpful Options</th>
+</tr>
+</thead>
+<tbody>
+<tr class="odd">
+<td><code>rm &lt;path&gt;</code></td>
+<td>Remove</td>
+<td><p><code>-r</code> - recursively remove everything below a file path</p>
+<p><code>-f</code> - force - don’t ask for each file</p>
+<p><strong>Be very careful, it’s permanent</strong></p></td>
+</tr>
+<tr class="even">
+<td><code>c  p &lt;from&gt; &lt;to&gt;</code></td>
+<td>Copy</td>
+<td></td>
+</tr>
+<tr class="odd">
+<td><code>m  v &lt;from&gt; &lt;to&gt;</code></td>
+<td>Move</td>
+<td></td>
+</tr>
+<tr class="even">
+<td><code>*</code></td>
+<td>Wildcard</td>
+<td></td>
+</tr>
+<tr class="odd">
+<td><code>mkdir</code>/<code>rmdir</code></td>
+<td>Make/remove directory</td>
+<td><code>-p</code> - create any parts of path that don’t exist</td>
+</tr>
+</tbody>
+</table>
+</section>
+<section id="move-things-tofrom-server" class="level3" data-number="C.3.5">
+<h3 data-number="C.3.5" class="anchored" data-anchor-id="move-things-tofrom-server"><span class="header-section-number">C.3.5</span> Move things to/from server</h3>
+<table class="table">
+<colgroup>
+<col style="width: 13%">
+<col style="width: 40%">
+<col style="width: 40%">
+</colgroup>
+<thead>
+<tr class="header">
+<th>Command</th>
+<th>What it does</th>
+<th>Notes + Helpful options</th>
+</tr>
+</thead>
+<tbody>
+<tr class="odd">
+<td><code>tar</code></td>
+<td>Create/extract archive file</td>
+<td><p>Almost always used with flags.</p>
+<p>Create is usually</p>
+<p><code>tar -czf &lt; a  r c hive name&gt; &lt;file(s)&gt;</code></p>
+<p>Extract is usually</p>
+<p><code>t  a r  -xfv &lt;archive name&gt;</code></p></td>
+</tr>
+<tr class="even">
+<td><code>scp</code></td>
+<td>Secure copy via <code>ssh</code></td>
+<td><p>Run on laptop to server</p>
+<p>Can use most <code>ssh</code> flags (like <code>-i</code> and <code>-v</code>)</p></td>
+</tr>
+</tbody>
+</table>
+</section>
+<section id="write-files-from-the-command-line" class="level3" data-number="C.3.6">
+<h3 data-number="C.3.6" class="anchored" data-anchor-id="write-files-from-the-command-line"><span class="header-section-number">C.3.6</span> Write files from the command line</h3>
+<table class="table">
+<colgroup>
+<col style="width: 8%">
+<col style="width: 38%">
+<col style="width: 53%">
+</colgroup>
+<thead>
+<tr class="header">
+<th>Command</th>
+<th>What it does</th>
+<th>Notes</th>
+</tr>
+</thead>
+<tbody>
+<tr class="odd">
+<td><code>touch</code></td>
+<td>Creates file if doesn’t already exist.</td>
+<td>Updates last updated to current time if it does exist.</td>
+</tr>
+<tr class="even">
+<td><code>&gt;</code></td>
+<td>Overwrite file contents</td>
+<td>Creates a new file if it doesn’t exist</td>
+</tr>
+<tr class="odd">
+<td><code>&gt;&gt;</code></td>
+<td>Concatenate to end of file</td>
+<td>Creates a new file if it doesn’t exist</td>
+</tr>
+</tbody>
+</table>
+</section>
+<section id="command-line-text-editors-vim-nano" class="level3" data-number="C.3.7">
+<h3 data-number="C.3.7" class="anchored" data-anchor-id="command-line-text-editors-vim-nano"><span class="header-section-number">C.3.7</span> Command Line Text Editors (Vim + Nano)</h3>
+<table class="table">
+<colgroup>
+<col style="width: 8%">
+<col style="width: 46%">
+<col style="width: 44%">
+</colgroup>
+<thead>
+<tr class="header">
+<th>Command</th>
+<th>What it does</th>
+<th>Notes + Helpful options</th>
+</tr>
+</thead>
+<tbody>
+<tr class="odd">
+<td><code>^</code></td>
+<td>Prefix for file command in <code>nano</code> editor.</td>
+<td>Its the <code>⌘</code> or <code>Ctrl</code> key, not the caret symbol.</td>
+</tr>
+<tr class="even">
+<td><code>i</code></td>
+<td>Enter insert mode (able to type) in <code>vim</code></td>
+<td></td>
+</tr>
+<tr class="odd">
+<td><code>escape</code></td>
+<td>Enter normal mode (navigation) in <code>vim</code>.</td>
+<td></td>
+</tr>
+<tr class="even">
+<td><code>:w</code></td>
+<td>Write the current file in <code>vim</code> (from normal mode)</td>
+<td>Can be combined to save and quit in one, <code>:wq</code></td>
+</tr>
+<tr class="odd">
+<td><code>:q</code></td>
+<td>Quit <code>vim</code> (from normal mode)</td>
+<td><code>:q!</code> quit without saving</td>
+</tr>
+</tbody>
+</table>
+</section>
+</section>
+<section id="cheat-file" class="level2" data-number="C.4">
+<h2 data-number="C.4" class="anchored" data-anchor-id="cheat-file"><span class="header-section-number">C.4</span> Cheatsheet: Users and Permissions</h2>
+<section id="users" class="level3" data-number="C.4.1">
+<h3 data-number="C.4.1" class="anchored" data-anchor-id="users"><span class="header-section-number">C.4.1</span> Users</h3>
+<table class="table">
+<colgroup>
+<col style="width: 29%">
+<col style="width: 70%">
+</colgroup>
+<thead>
+<tr class="header">
+<th>Command</th>
+<th>What it does</th>
+</tr>
+</thead>
+<tbody>
+<tr class="odd">
+<td><code>su &lt;username&gt;</code></td>
+<td>Change to be a different user.</td>
+</tr>
+<tr class="even">
+<td><code>whoami</code></td>
+<td>Get username of current user.</td>
+</tr>
+<tr class="odd">
+<td><code>id</code></td>
+<td>Get full user + group info on current user.</td>
+</tr>
+<tr class="even">
+<td><code>passwd</code></td>
+<td>Change password.</td>
+</tr>
+<tr class="odd">
+<td><code>useradd</code></td>
+<td>Add a new user.</td>
+</tr>
+<tr class="even">
+<td><code>u sermod &lt;username&gt;</code></td>
+<td>Modify user <code>username</code>. <code>-aG &lt;group&gt;</code> adds to a group</td>
+</tr>
+</tbody>
+</table>
+</section>
+<section id="permissions" class="level3" data-number="C.4.2">
+<h3 data-number="C.4.2" class="anchored" data-anchor-id="permissions"><span class="header-section-number">C.4.2</span> Permissions</h3>
+<table class="table">
+<colgroup>
+<col style="width: 16%">
+<col style="width: 27%">
+<col style="width: 55%">
+</colgroup>
+<thead>
+<tr class="header">
+<th>Command</th>
+<th>What it does</th>
+<th>Helpful options + notes</th>
+</tr>
+</thead>
+<tbody>
+<tr class="odd">
+<td><code>chm o d &lt;permissi ons&gt; &lt;file&gt;</code></td>
+<td>Modifies permissions on a file.</td>
+<td>Number indicates permissions for user, group, others: add 4 for read, 2 for write, 1 for execute, 0 for nothing.</td>
+</tr>
+<tr class="even">
+<td><code>cho w n  &lt;user/gr oup&gt; &lt;file&gt;</code></td>
+<td>Change the owner of a file.</td>
+<td>Can be used for user or group, e.g.&nbsp;<code>:my-group</code>.</td>
+</tr>
+<tr class="odd">
+<td><code>su  &lt;username&gt;</code></td>
+<td>Change active user to <code>username</code>.</td>
+<td></td>
+</tr>
+<tr class="even">
+<td><code>sud o &lt;command&gt;</code></td>
+<td>Adopt super user permissions for the following command.</td>
+<td></td>
+</tr>
+</tbody>
+</table>
+</section>
+</section>
+<section id="cheat-ssh" class="level2" data-number="C.5">
+<h2 data-number="C.5" class="anchored" data-anchor-id="cheat-ssh"><span class="header-section-number">C.5</span> Cheatsheet: <code>ssh</code></h2>
+<div class="sourceCode" id="cb1"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb1-1"><a href="#cb1-1"></a><span class="fu">ssh</span> <span class="op">&lt;</span>user<span class="op">&gt;</span>@<span class="op">&lt;</span>host<span class="op">&gt;</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+<table class="table">
+<colgroup>
+<col style="width: 6%">
+<col style="width: 40%">
+<col style="width: 52%">
+</colgroup>
+<thead>
+<tr class="header">
+<th>Flag</th>
+<th>What it does</th>
+<th>Notes</th>
+</tr>
+</thead>
+<tbody>
+<tr class="odd">
+<td><code>-v</code></td>
+<td>Verbose, good for debugging.</td>
+<td>Add more <code>v</code>s as you please, <code>-vv</code> or <code>-vvv</code>.</td>
+</tr>
+<tr class="even">
+<td><code>-i</code></td>
+<td>Choose identity file (private key)</td>
+<td>Not necessary with default key names.</td>
+</tr>
+</tbody>
+</table>
+</section>
+<section id="cheat-admin" class="level2" data-number="C.6">
+<h2 data-number="C.6" class="anchored" data-anchor-id="cheat-admin"><span class="header-section-number">C.6</span> Cheatsheet: Linux Admin Commands</h2>
+<section id="users-1" class="level3" data-number="C.6.1">
+<h3 data-number="C.6.1" class="anchored" data-anchor-id="users-1"><span class="header-section-number">C.6.1</span> Users</h3>
+<table class="table">
+<colgroup>
+<col style="width: 32%">
+<col style="width: 67%">
+</colgroup>
+<thead>
+<tr class="header">
+<th>Command</th>
+<th>What it does</th>
+</tr>
+</thead>
+<tbody>
+<tr class="odd">
+<td><code>su &lt;username&gt;</code></td>
+<td>Change to be a different user.</td>
+</tr>
+<tr class="even">
+<td><code>whoami</code></td>
+<td>Get username of current user.</td>
+</tr>
+<tr class="odd">
+<td><code>id</code></td>
+<td>Get full user + group info on current user.</td>
+</tr>
+<tr class="even">
+<td><code>passwd</code></td>
+<td>Change password.</td>
+</tr>
+<tr class="odd">
+<td><code>useradd</code></td>
+<td>Add a new user.</td>
+</tr>
+<tr class="even">
+<td><code>use   r m od &lt;username&gt;</code></td>
+<td>Modify user <code>username</code>. <code>-aG &lt;group&gt;</code> adds to a group</td>
+</tr>
+</tbody>
+</table>
+</section>
+<section id="permissions-1" class="level3" data-number="C.6.2">
+<h3 data-number="C.6.2" class="anchored" data-anchor-id="permissions-1"><span class="header-section-number">C.6.2</span> Permissions</h3>
+<table class="table">
+<colgroup>
+<col style="width: 18%">
+<col style="width: 27%">
+<col style="width: 54%">
+</colgroup>
+<thead>
+<tr class="header">
+<th>Command</th>
+<th>What it does</th>
+<th>Helpful options + notes</th>
+</tr>
+</thead>
+<tbody>
+<tr class="odd">
+<td><code>ch m od &lt;per m i s s ions&gt; &lt;file&gt;</code></td>
+<td>Modifies permissions on a file.</td>
+<td>Number indicates permissions for user, group, others: add 4 for read, 2 for write, 1 for execute, 0 for nothing.</td>
+</tr>
+<tr class="even">
+<td><code>c h ow n  &lt;us e r / g roup&gt; &lt;file&gt;</code></td>
+<td>Change the owner of a file.</td>
+<td>Can be used for user or group, e.g.&nbsp;<code>:my-group</code>.</td>
+</tr>
+<tr class="odd">
+<td><code>s u &lt;username&gt;</code></td>
+<td>Change active user to <code>username</code>.</td>
+<td></td>
+</tr>
+<tr class="even">
+<td><code>s u do &lt;command&gt;</code></td>
+<td>Adopt super user permissions for the following command.</td>
+<td></td>
+</tr>
+</tbody>
+</table>
+</section>
+<section id="install-applications-ubuntu" class="level3" data-number="C.6.3">
+<h3 data-number="C.6.3" class="anchored" data-anchor-id="install-applications-ubuntu"><span class="header-section-number">C.6.3</span> Install applications (Ubuntu)</h3>
+<table class="table">
+<colgroup>
+<col style="width: 48%">
+<col style="width: 51%">
+</colgroup>
+<tbody>
+<tr class="odd">
+<td><strong>Command</strong></td>
+<td><strong>What it does</strong></td>
+</tr>
+<tr class="even">
+<td><code>apt-get u p d a t e &amp;&amp; apt-get upgrade -y</code></td>
+<td>Fetch and install upgrades to system packages</td>
+</tr>
+<tr class="odd">
+<td><code>a p t-get install &lt;package&gt;</code></td>
+<td>Install a system package.</td>
+</tr>
+<tr class="even">
+<td><code>wget</code></td>
+<td>Download a file from a URL.</td>
+</tr>
+<tr class="odd">
+<td><code>gdebi</code></td>
+<td>Install local <code>.deb</code> file.</td>
+</tr>
+</tbody>
+</table>
+</section>
+<section id="storage" class="level3" data-number="C.6.4">
+<h3 data-number="C.6.4" class="anchored" data-anchor-id="storage"><span class="header-section-number">C.6.4</span> Storage</h3>
+<table class="table">
+<colgroup>
+<col style="width: 13%">
+<col style="width: 40%">
+<col style="width: 40%">
+</colgroup>
+<thead>
+<tr class="header">
+<th>Command</th>
+<th>What it does</th>
+<th>Helpful options</th>
+</tr>
+</thead>
+<tbody>
+<tr class="odd">
+<td><code>df</code></td>
+<td>Check storage space on device.</td>
+<td><code>-h</code> for human readable file sizes.</td>
+</tr>
+<tr class="even">
+<td><code>du</code></td>
+<td>Check size of files.</td>
+<td><p>Most likely to be used as <code>d  u - h &lt;dir&gt; | sort -h</code></p>
+<p>Also useful to combine with <code>head</code>.</p></td>
+</tr>
+</tbody>
+</table>
+</section>
+<section id="processes" class="level3" data-number="C.6.5">
+<h3 data-number="C.6.5" class="anchored" data-anchor-id="processes"><span class="header-section-number">C.6.5</span> Processes</h3>
+<table class="table">
+<colgroup>
+<col style="width: 9%">
+<col style="width: 34%">
+<col style="width: 55%">
+</colgroup>
+<thead>
+<tr class="header">
+<th>Command</th>
+<th>What it does</th>
+<th>Helpful options</th>
+</tr>
+</thead>
+<tbody>
+<tr class="odd">
+<td><code>top</code></td>
+<td>See what’s running on the system.</td>
+<td></td>
+</tr>
+<tr class="even">
+<td><code>ps aux</code></td>
+<td>See all system processes.</td>
+<td>Consider using <code>--sort</code> and pipe into <code>head</code> or <code>grep</code></td>
+</tr>
+<tr class="odd">
+<td><code>kill</code></td>
+<td>Kill a system process.</td>
+<td><code>-9</code> to force kill immediately</td>
+</tr>
+</tbody>
+</table>
+</section>
+<section id="networking" class="level3" data-number="C.6.6">
+<h3 data-number="C.6.6" class="anchored" data-anchor-id="networking"><span class="header-section-number">C.6.6</span> Networking</h3>
+<table class="table">
+<colgroup>
+<col style="width: 23%">
+<col style="width: 28%">
+<col style="width: 47%">
+</colgroup>
+<thead>
+<tr class="header">
+<th>Command</th>
+<th>What it does</th>
+<th>Helpful options</th>
+</tr>
+</thead>
+<tbody>
+<tr class="odd">
+<td><code>netstat</code></td>
+<td>See ports and services using them.</td>
+<td>Usually used with <code>-tlp</code>, for tcp listening applications, including <code>pid</code></td>
+</tr>
+<tr class="even">
+<td><code>ssh - L  &lt;port&gt;:&lt;ip&gt;: &lt;port&gt; &lt;host&gt;</code></td>
+<td>Port forwards a remote port on host to local.</td>
+<td>Choose local port to match remote port. Remote <code>ip</code> is usually <code>localhost</code>.</td>
+</tr>
+</tbody>
+</table>
+</section>
+<section id="the-path" class="level3" data-number="C.6.7">
+<h3 data-number="C.6.7" class="anchored" data-anchor-id="the-path"><span class="header-section-number">C.6.7</span> The path</h3>
+<table class="table">
+<colgroup>
+<col style="width: 47%">
+<col style="width: 50%">
+</colgroup>
+<thead>
+<tr class="header">
+<th>Command</th>
+<th>What it does</th>
+</tr>
+</thead>
+<tbody>
+<tr class="odd">
+<td><code>which &lt;command&gt;</code></td>
+<td>Finds the location of the binary that runs when you run <code>command</code>.</td>
+</tr>
+<tr class="even">
+<td><dl>
+<dt>`ln -s &lt; lo cation to link&gt;</dt>
+<dd>
+<p>&lt; l ocation of symlink&gt;`</p>
+</dd>
+</dl></td>
+<td>Creates a symlink from file at <code>location to link</code> to <code>location of symlink</code>.</td>
+</tr>
+</tbody>
+</table>
+</section>
+</section>
+<section id="cheat-ports" class="level2" data-number="C.7">
+<h2 data-number="C.7" class="anchored" data-anchor-id="cheat-ports"><span class="header-section-number">C.7</span> Cheatsheet: IP Addresses and Ports</h2>
+<section id="special-ip-addresses" class="level3" data-number="C.7.1">
+<h3 data-number="C.7.1" class="anchored" data-anchor-id="special-ip-addresses"><span class="header-section-number">C.7.1</span> Special IP Addresses</h3>
+<table class="table">
+<colgroup>
+<col style="width: 20%">
+<col style="width: 76%">
+</colgroup>
+<thead>
+<tr class="header">
+<th>Code</th>
+<th>Meaning</th>
+</tr>
+</thead>
+<tbody>
+<tr class="odd">
+<td>127.0.0.1</td>
+<td><code>localhost</code> or loopback – the machine that originated the request</td>
+</tr>
+<tr class="even">
+<td><p>192.168.x.x</p>
+<p>172.16.x.x.x</p>
+<p>10.x.x.x</p></td>
+<td>Protected address blocks used for private IP addresses.</td>
+</tr>
+</tbody>
+</table>
+</section>
+<section id="special-ports" class="level3" data-number="C.7.2">
+<h3 data-number="C.7.2" class="anchored" data-anchor-id="special-ports"><span class="header-section-number">C.7.2</span> Special Ports</h3>
+<p>All ports below 1024 are reserved for server tasks and cannot be assigned to admin-controlled services.</p>
+<table class="table">
+<thead>
+<tr class="header">
+<th>Protocol/Application</th>
+<th>Default Port</th>
+</tr>
+</thead>
+<tbody>
+<tr class="odd">
+<td>HTTP</td>
+<td>80</td>
+</tr>
+<tr class="even">
+<td>HTTPS</td>
+<td>443</td>
+</tr>
+<tr class="odd">
+<td>SSH</td>
+<td>22</td>
+</tr>
+<tr class="even">
+<td>PostgreSQL</td>
+<td>5432</td>
+</tr>
+<tr class="odd">
+<td>RStudio Server</td>
+<td></td>
+</tr>
+<tr class="even">
+<td>Shiny Server</td>
+<td></td>
+</tr>
+<tr class="odd">
+<td>JupyterHub</td>
+<td></td>
+</tr>
+</tbody>
+</table>
+</section>
+</section>
+<section id="cheatsheet-debugging-tips" class="level2" data-number="C.8">
+<h2 data-number="C.8" class="anchored" data-anchor-id="cheatsheet-debugging-tips"><span class="header-section-number">C.8</span> Cheatsheet: Debugging Tips</h2>
+<p>If things are going poorly on your server, here are some steps you might take to try to troubleshoot.</p>
+<section id="check-storage-usage" class="level3" data-number="C.8.1">
+<h3 data-number="C.8.1" class="anchored" data-anchor-id="check-storage-usage"><span class="header-section-number">C.8.1</span> Check storage usage</h3>
+<p>A common culprit for weird server behavior is running out of storage space. There are two handy commands for monitoring the amount of storage you’ve got – <code>du</code> and <code>df</code>. These commands are almost always used with the <code>-h</code> flag to put file sizes in human-readable formats.</p>
+<p><code>df</code>, for disk free, shows the capacity left on the device where the directory sits.</p>
+<p>For example, here’s the result of running the <code>df</code> command on the chapters directory on my laptop that includes this chapter.</p>
+<div class="sourceCode" id="cb2"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb2-1"><a href="#cb2-1"></a> <span class="ex">❯</span> df <span class="at">-h</span> chapters                                                    </span>
+<span id="cb2-2"><a href="#cb2-2"></a><span class="ex">Filesystem</span>     Size   Used  Avail Capacity iused      ifree %iused  Mounted on</span>
+<span id="cb2-3"><a href="#cb2-3"></a><span class="ex">/dev/disk3s5</span>  926Gi  163Gi  750Gi    18% 1205880 7863468480    0%   /System/Volumes/Data</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+<p>So you can see that the chapters folder lives on a disk called <code>/dev/disk3s5</code> that’s a little less than 1Tb and is 18% full – no problem. On a server this can be really useful to know, because it’s quite easy to switch a disk out for a bigger one in the same spot.</p>
+<p>If you’ve figured out that a disk is full and need to figure out where the culprits are, the <code>du</code> can be useful. <code>du</code>, short for disk usage, gives you the size of individual files inside a directory. It’s particularly useful in combination with the <code>sort</code> command.</p>
+<p>For example, here’s the result of running <code>du</code> on the <code>chapters</code> directory where the text files for this book live.</p>
+<div class="sourceCode" id="cb3"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb3-1"><a href="#cb3-1"></a> <span class="ex">❯</span> du <span class="at">-h</span> chapters <span class="kw">|</span> <span class="fu">sort</span> <span class="at">-h</span>                                      </span>
+<span id="cb3-2"><a href="#cb3-2"></a> <span class="ex">44K</span>    chapters/sec2/images-servers</span>
+<span id="cb3-3"><a href="#cb3-3"></a><span class="ex">124K</span>    chapters/sec3/images-scaling</span>
+<span id="cb3-4"><a href="#cb3-4"></a><span class="ex">156K</span>    chapters/sec2/images</span>
+<span id="cb3-5"><a href="#cb3-5"></a><span class="ex">428K</span>    chapters/sec2/images-traffic</span>
+<span id="cb3-6"><a href="#cb3-6"></a><span class="ex">656K</span>    chapters/sec1/images-code-promotion</span>
+<span id="cb3-7"><a href="#cb3-7"></a><span class="ex">664K</span>    chapters/sec1/images-docker</span>
+<span id="cb3-8"><a href="#cb3-8"></a><span class="ex">1.9M</span>    chapters/sec1/images-repro</span>
+<span id="cb3-9"><a href="#cb3-9"></a><span class="ex">3.4M</span>    chapters/sec1</span>
+<span id="cb3-10"><a href="#cb3-10"></a><span class="ex">3.9M</span>    chapters/sec3/images-auth</span>
+<span id="cb3-11"><a href="#cb3-11"></a><span class="ex">4.1M</span>    chapters/sec3</span>
+<span id="cb3-12"><a href="#cb3-12"></a><span class="ex">4.5M</span>    chapters/sec2/images-networking</span>
+<span id="cb3-13"><a href="#cb3-13"></a><span class="ex">5.3M</span>    chapters/sec2</span>
+<span id="cb3-14"><a href="#cb3-14"></a> <span class="ex">13M</span>    chapters</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+<p>So if I were thinking about cleaning up this directory, I could see that my <code>images-networking</code> directory in <code>sec2</code> is the biggest single bottom-level directory. If you find yourself needing to find big files on your Linux server, it’s worth spending some time with the help pages for <code>du</code>. There are lots of really useful options.</p>
+<p><code>du</code> is useful for identifying large files and directories on a server.</p>
+</section>
+<section id="look-at-whats-running" class="level3" data-number="C.8.2">
+<h3 data-number="C.8.2" class="anchored" data-anchor-id="look-at-whats-running"><span class="header-section-number">C.8.2</span> Look at what’s running</h3>
+<p>A running program is a <em>process</em>. For example, when you type <code>python</code> on the command line to open a REPL, that starts a single Python process. If you were to start a second terminal session and run <code>python</code> again, you’d have a second Python process.</p>
+<p>Complicated programs often involves multiple than one process. For example, running the RStudio IDE involves (at minimum) one process for the IDE itself and one for the R session that it uses in the background. The relationships between these different processes is mostly hidden from you – the end user.</p>
+<p>As a server admin, finding runaway processes, killing them, and figuring out how to prevent the them from happening again is a pretty common task. Runaway processes usually misbehave by using up the entire CPU or filling up the entire machine’s RAM.</p>
+<p>Like users and groups have ids, each process has a numeric process id (<code>pid</code>). Each process also has an owner – this can be either a service account or a real user. If you’ve got a rogue process, the pattern is to try to find the process and make note of its <code>pid</code>. Then you can immediately end the process by <code>pid</code> with the <code>kill</code> command.</p>
+<p>So, how do you find a troublesome process?</p>
+<p>The <code>top</code> command is a good first stop. <code>top</code> shows the top CPU-consuming processes in real time. Here’s the <code>top</code> output from my machine as I write this sentence.</p>
+<div class="sourceCode" id="cb4"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb4-1"><a href="#cb4-1"></a><span class="ex">PID</span>    COMMAND      %CPU TIME     <span class="co">#TH    #WQ  #PORT MEM    PURG   CMPRS PGRP</span></span>
+<span id="cb4-2"><a href="#cb4-2"></a><span class="ex">0</span>      kernel_task  16.1 03:56:53 530/10 0    0     2272K  0B     0B    0</span>
+<span id="cb4-3"><a href="#cb4-3"></a><span class="ex">16329</span>  WindowServer 16.0 01:53:20 23     6    3717  941M-  16M+   124M  16329</span>
+<span id="cb4-4"><a href="#cb4-4"></a><span class="ex">24484</span>  iTerm2       11.3 00:38.20 5      2    266-  71M-   128K   18M-  24484</span>
+<span id="cb4-5"><a href="#cb4-5"></a><span class="ex">29519</span>  top          9.7  00:04.30 1/1    0    36    9729K  0B     0B    29519</span>
+<span id="cb4-6"><a href="#cb4-6"></a><span class="ex">16795</span>  Magnet       3.1  00:39.16 3      1    206   82M    0B     39M   16795</span>
+<span id="cb4-7"><a href="#cb4-7"></a><span class="ex">16934</span>  Arc          1.8  18:18.49 45     6    938   310M   144K   61M   16934</span>
+<span id="cb4-8"><a href="#cb4-8"></a><span class="ex">16456</span>  Messages     1.7  06:58.27 4      1    603   138M   2752K  63M   16456</span>
+<span id="cb4-9"><a href="#cb4-9"></a><span class="ex">1</span>      launchd      1.7  13:41.03 4/1    3/1  3394+ 29M    0B     6080K 1</span>
+<span id="cb4-10"><a href="#cb4-10"></a><span class="ex">573</span>    diagnosticd  1.4  04:31.97 3      2    49    2417K  0B     816K  573</span>
+<span id="cb4-11"><a href="#cb4-11"></a><span class="ex">16459</span>  zoom.us      1.3  66:38.37 30     3    2148  214M   384K   125M  16459</span>
+<span id="cb4-12"><a href="#cb4-12"></a><span class="ex">16575</span>  UniversalCon 1.3  01:15.89 2      1    131   12M    0B     2704K 16575</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+<p>In most instances, the first three columns are the most useful. You’ve got the name of the process (<code>COMMAND</code>) and how much CPU its using. Right now, nothing is using very much CPU. If I were to find something concerning – perhaps an R process that is using 500% of CPU – I would want to take notice of its <code>pid</code> to kill it with <code>kill</code>.</p>
+<div class="callout callout-style-default callout-note callout-titled">
+<div class="callout-header d-flex align-content-center">
+<div class="callout-icon-container">
+<i class="callout-icon"></i>
+</div>
+<div class="callout-title-container flex-fill">
+So much CPU?
+</div>
+</div>
+<div class="callout-body-container callout-body">
+<p>For <code>top</code> (and most other commands), CPU is expressed as a percent of <em>single core</em> availability. So, on a modern machine with multiple cores, it’s very common to see CPU totals well over 100%. Seeing a single process using over 100% of CPU is rarer.</p>
+</div>
+</div>
+<p>The <code>top</code> command takes over your whole terminal. You can exit with <code>Ctrl + c</code>.</p>
+<p>Another useful command for finding runaway processes is <code>ps aux</code>. It lists a snapshot of all processes running on the system, along with how much CPU and RAM they’re using. You can sort the output with the <code>--sort</code> flag and specify sorting by cpu with <code>--sort -%cpu</code> or by memory with <code>--sort -%mem</code>.</p>
+<p>Because <code>ps aux</code> returns <em>every</em> running process on the system, you’ll probably want to pipe the output into <code>head</code>.</p>
+<p>Another useful way to use <code>ps aux</code> is in combination with <code>grep</code>. If you pretty much know what the problem is – often this might be a runaway R or Python process – <code>ps aux | grep &lt;name&gt;</code> can be super useful to get the <code>pid</code>.</p>
+<p>For example, here are the RStudio processes currently running on my system.<a href="#fn1" class="footnote-ref" id="fnref1" role="doc-noteref"><sup>1</sup></a></p>
+<div class="sourceCode" id="cb5"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb5-1"><a href="#cb5-1"></a> <span class="op">&gt;</span> ps <span class="ex">aux</span> <span class="kw">|</span> <span class="fu">grep</span> <span class="st">"RStudio"</span>                                                                                      <span class="pp">[</span><span class="ss">10:21:18</span><span class="pp">]</span></span>
+<span id="cb5-2"><a href="#cb5-2"></a><span class="ex">USER</span>               PID  %CPU %MEM      VSZ    RSS   TT  STAT STARTED      TIME COMMAND</span>
+<span id="cb5-3"><a href="#cb5-3"></a><span class="ex">alexkgold</span>        23583   0.9  1.7 37513368 564880   <span class="pp">??</span>  S    Sat09AM  17:15.27 /Applications/RStudio.app/Contents/MacOS/RStudio</span>
+<span id="cb5-4"><a href="#cb5-4"></a><span class="ex">alexkgold</span>        23605   0.5  0.4 36134976 150828   <span class="pp">??</span>  S    Sat09AM   1:58.16 /Applications/RStudio.app/Contents/MacOS/rsession <span class="at">--config-file</span> none <span class="at">--program-mode</span> desktop </span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+</section>
+<section id="make-sure-the-right-ports-are-open" class="level3" data-number="C.8.3">
+<h3 data-number="C.8.3" class="anchored" data-anchor-id="make-sure-the-right-ports-are-open"><span class="header-section-number">C.8.3</span> Make sure the right ports are open</h3>
+<p>Networking is a complicated topic, which we’ll approach with great detail in <a href="../sec2/2-6-networking.html">Chapter&nbsp;<span>12</span></a>. Most often, you’ll want to check that the application you’re running is actually accessible to the outside world, assuming you want it to be.</p>
+<p>The main command to help you see what ports are being used and by what services is the <code>netstat</code> command. <code>netstat</code> returns the services that are running and their associated ports. <code>netstat</code> is generally most useful with the <code>-tlp</code> flags to show programs that are listening and the programs associated.</p>
+<p>Sometimes you <em>know</em> you’ve got a service running on your machine, but you just can’t seem to get the networking working. It can be useful to access the service directly without having to deal with networking.</p>
+<p>SSH port forwarding allows you to take the output of a port on a remote server, route it through SSH, and display it as if it were on a local port. For example, let’s say you’ve got RStudio Server running on my server but the web interface isn’t working. If you’ve got SSH working properly, you can double check that the service is working and the issue really is networking.</p>
+<p>I find that the syntax for port forwarding completely defies my memory and I have to google it every time I use it. For the kind of port forwarding you’ll use most often in debugging, you’ll use the <code>-L</code> flag to get a remote port locally.</p>
+<p><code>ssh -L &lt;local port&gt;:&lt;remote ip&gt;:&lt;remote port&gt; &lt;ssh hostname&gt;</code></p>
+<p>The local would be your laptop and the remote your server, so if you had RStudio Server running on a server on port <code>3939</code>. Then you could run <code>ssh -L 3939:localhost:3939 my-user@my-ds-workbench.com</code>. To get whatever is at port <code>3939</code> on the server (hopefully RStudio Workbench!) by going to <code>localhost:3939</code> in the laptop’s browser.</p>
+<p>Most often, you’ll use the same port locally and on the remote and the remote ip will be <code>localhost</code>.</p>
+</section>
+<section id="check-your-path" class="level3" data-number="C.8.4">
+<h3 data-number="C.8.4" class="anchored" data-anchor-id="check-your-path"><span class="header-section-number">C.8.4</span> Check your path</h3>
+<p>Let’s say you want to open Python on your command line. One option would be to type the complete path to a Python install every time. For example, I’ve got a version of Python in <code>/usr/bin</code>, so <code>/usr/bin/python3</code> works.</p>
+<p>But in most cases, it’s nice to just type <code>python3</code> and have the right version open up.</p>
+<div class="sourceCode" id="cb6"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb6-1"><a href="#cb6-1"></a><span class="ex">$</span> python3</span>
+<span id="cb6-2"><a href="#cb6-2"></a><span class="ex">Python</span> 3.9.6 <span class="er">(</span><span class="ex">default,</span> May  7 2023, 23:32:45<span class="kw">)</span> </span>
+<span id="cb6-3"><a href="#cb6-3"></a><span class="ex">[Clang</span> 14.0.3 <span class="er">(</span><span class="ex">clang-1403.0.22.14.1</span><span class="kw">)</span><span class="ex">]</span> on darwin</span>
+<span id="cb6-4"><a href="#cb6-4"></a><span class="ex">Type</span> <span class="st">"help"</span>, <span class="st">"copyright"</span>, <span class="st">"credits"</span> or <span class="st">"license"</span> for more information.</span>
+<span id="cb6-5"><a href="#cb6-5"></a><span class="op">&gt;&gt;&gt;</span> </span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+<p>In some cases, this isn’t optional. Certain applications will rely on others being available, like RStudio needing to find R. Or Jupyter Notebook finding your Python kernels.</p>
+<p>So how does the operating system know where to find those applications and files?</p>
+<p>If you ever want to check which actual executable is being used by a command, you can use the <code>which</code> command. For example, on my system this is the result of <code>which python3</code>.</p>
+<div class="sourceCode" id="cb7"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb7-1"><a href="#cb7-1"></a> <span class="ex">❯</span> which python3                                                    </span>
+<span id="cb7-2"><a href="#cb7-2"></a><span class="ex">/usr/bin/python3</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+<p>The operating system knows how to find the actual runnable programs on your system via the <em>path</em>. The path is a set of directories that the system knows to search when it tries to run a path. The path is stored in an environment variable conveniently named <code>PATH</code>.</p>
+<p>You can check your path at any time by echoing the <code>PATH</code> environment variable with <code>echo $PATH</code>. On my MacBook, this is what the path looks like.</p>
+<div class="sourceCode" id="cb8"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb8-1"><a href="#cb8-1"></a> <span class="ex">❯</span> echo <span class="va">$PATH</span>                                                      </span>
+<span id="cb8-2"><a href="#cb8-2"></a><span class="ex">/opt/homebrew/bin:/opt/homebrew/sbin:/usr/local/bin:/System/Cryptexes/App/usr/bin:/usr/bin:/bin:/usr/sbin:/sbin</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+<p>When you install a new piece of software you’ll need to add it two the path. Say I was to install a new version of Python in <code>/opt/python</code>. That’s not on my <code>PATH</code>, so my system wouldn’t be able to find it.</p>
+<p>I can get it on the path in one of two ways – the first option would be to add <code>/opt/python</code> to my <code>PATH</code> every time a terminal session starts usually via a file in <code>/etc</code> or the <code>.zshrc</code>. The other option is to create a <em>symlink</em> to the new application in a directory already on the <code>PATH</code>. A symlink does what it sounds like – creates a way to link to a file from a different directory without moving it.</p>
+<p>Symlinks are created with the <code>ln</code> command.</p>
+</section>
+</section>
+<section id="comprehension-questions" class="level2" data-number="C.9">
+<h2 data-number="C.9" class="anchored" data-anchor-id="comprehension-questions"><span class="header-section-number">C.9</span> Comprehension Questions</h2>
+<ol type="1">
+<li>How would you do the following?
+<ol type="1">
+<li><p>Find and kill the process IDs for all running <code>rstudio-server</code> processes.</p></li>
+<li><p>Figure out which port <code>JupyterHub</code> is running on.</p></li>
+<li><p>Create a file called <code>secrets.txt</code>, open it with vim, write something in, close and save it, and make it so that only you can read it.</p></li>
+</ol></li>
+</ol>
+
+
+</section>
+<section id="footnotes" class="footnotes footnotes-end-of-document" role="doc-endnotes">
+<hr>
+<ol>
+<li id="fn1"><p>This command actually cuts off the header line of the table. What I actually ran was <code>ps aux | grep "RStudio\|USER"</code>.<a href="#fnref1" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
+</ol>
+</section>
+
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- <span class="menu-text">IT/Admin Tools</span></a>
+ <span class="menu-text">IT/Admin for Data Science</span></a>
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- <span class="menu-text">IT/Admin for Data Science</span></a>
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-  <a href="../../chapters/sec3/3-1-cloud.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Getting Started with the Cloud</span></span></a>
+  <a href="../../chapters/sec2/2-4-app-admin.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Application administration</span></span></a>
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-  <a href="../../chapters/sec3/3-2-linux-admin.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Basic Linux SysAdmin</span></span></a>
+  <a href="../../chapters/sec2/2-5-scale.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Server Resources and Scaling</span></span></a>
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           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-3-networking.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-6-networking.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">12</span>&nbsp; <span class="chapter-title">Intro to Computer Networks</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-4-dns.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-7-dns.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">13</span>&nbsp; <span class="chapter-title">DNS allows for human-readable addresses</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-5-ssl.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-8-ssl.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">14</span>&nbsp; <span class="chapter-title">You should use SSL/HTTPS</span></span></a>
   </div>
-</li>
-          <li class="sidebar-item">
-  <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-6-servers.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Choosing the right server for you</span></span></a>
-  </div>
 </li>
       </ul>
   </li>
         <li class="sidebar-item sidebar-item-section">
       <div class="sidebar-item-container"> 
-            <a href="../../chapters/sec4/4-0-sec-intro.html" class="sidebar-item-text sidebar-link">
+            <a href="../../chapters/sec3/3-0-sec-intro.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text">Making it Enterprise-Grade</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true" aria-label="Toggle section">
+          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-3" aria-expanded="true" aria-label="Toggle section">
             <i class="bi bi-chevron-right ms-2"></i>
           </a> 
       </div>
-      <ul id="quarto-sidebar-section-4" class="collapse list-unstyled sidebar-section depth1 show">  
+      <ul id="quarto-sidebar-section-3" class="collapse list-unstyled sidebar-section depth1 show">  
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec4/4-1-os-ds-in-ent.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></a>
+  <a href="../../chapters/sec3/3-1-os-ds-in-ent.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec4/4-2-ent-networks.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></a>
+  <a href="../../chapters/sec3/3-2-ent-networks.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec4/4-3-auth.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></a>
+  <a href="../../chapters/sec3/3-3-auth.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></a>
   </div>
 </li>
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   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec4/4-4-ent-servers.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">19</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></a>
+  <a href="../../chapters/sec3/3-4-ent-servers.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></a>
   </div>
 </li>
       </ul>
   </li>
         <li class="sidebar-item sidebar-item-section">
       <div class="sidebar-item-container"> 
-            <a class="sidebar-item-text sidebar-link text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-5" aria-expanded="true">
+            <a class="sidebar-item-text sidebar-link text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true">
  <span class="menu-text">Appendices</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-5" aria-expanded="true" aria-label="Toggle section">
+          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true" aria-label="Toggle section">
             <i class="bi bi-chevron-right ms-2"></i>
           </a> 
       </div>
-      <ul id="quarto-sidebar-section-5" class="collapse list-unstyled sidebar-section depth1 show">  
+      <ul id="quarto-sidebar-section-4" class="collapse list-unstyled sidebar-section depth1 show">  
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
   <a href="../../chapters/append/auth.html" class="sidebar-item-text sidebar-link">
@@ -316,6 +300,12 @@
   <a href="../../chapters/append/lab-map.html" class="sidebar-item-text sidebar-link active">
  <span class="menu-text"><span class="chapter-number">B</span>&nbsp; <span class="chapter-title">Lab Map</span></span></a>
   </div>
+</li>
+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/append/cheatsheets.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">C</span>&nbsp; <span class="chapter-title">Cheatsheets</span></span></a>
+  </div>
 </li>
       </ul>
   </li>
@@ -350,8 +340,8 @@ <h1 class="title"><span id="sec-append-lab" class="quarto-section-identifier">Ap
 <p>This section aims to clarify the relationship between the assets you’ll make in each portfolio exercise and labs in this book.</p>
 <table class="table">
 <colgroup>
-<col style="width: 29%">
-<col style="width: 70%">
+<col style="width: 22%">
+<col style="width: 77%">
 </colgroup>
 <thead>
 <tr class="header">
@@ -381,32 +371,40 @@ <h1 class="title"><span id="sec-append-lab" class="quarto-section-identifier">Ap
 <td>Put a static Quarto site up on GitHub Pages using GitHub Actions that renders the project.</td>
 </tr>
 <tr class="even">
-<td><a href="../sec2/2-4-docker.html"><span>Chapter&nbsp;9</span></a>: Docker</td>
+<td><a href="../sec1/1-6-docker.html"><span>Chapter&nbsp;6</span></a>: Docker</td>
 <td>Put API from <a href="../sec1/1-2-proj-arch.html">Chapter&nbsp;<span>2</span></a> into Docker container.</td>
 </tr>
 <tr class="odd">
-<td><a href="../sec3/3-1-cloud.html"><span>Chapter&nbsp;10</span></a>: Cloud</td>
-<td>Stand up an EC2 instance. Put model into S3.</td>
+<td><a href="../sec2/2-1-cloud.html"><span>Chapter&nbsp;7</span></a>: Servers</td>
+<td>Stand up an EC2 instance. Put model from [Chapter @sec-proj-arch] into an S3 bucket.</td>
 </tr>
 <tr class="even">
-<td><a href="../sec3/3-2-linux-admin.html"><span>Chapter&nbsp;11</span></a>: Linux Admin</td>
-<td>Add R, Python, RStudio Server, JupyterHub, palmer penguin fastAPI + App.</td>
+<td><a href="../sec2/2-2-cmd-line.html"><span>Chapter&nbsp;8</span></a>: Command Line</td>
+<td>Log into your server with a <code>.pem</code> key and create an SSH key.</td>
 </tr>
 <tr class="odd">
-<td><a href="../sec3/3-3-networking.html"><span>Chapter&nbsp;12</span></a>: Networking</td>
-<td>Add proxy (nginx) to reach all services from the web.</td>
+<td><a href="../sec2/2-3-linux.html"><span>Chapter&nbsp;9</span></a>: Linux Admin</td>
+<td>Create a user on the server and add the SSH key from <a href="../sec2/2-2-cmd-line.html">Chapter&nbsp;<span>8</span></a>.</td>
 </tr>
 <tr class="even">
-<td><a href="../sec3/3-4-dns.html"><span>Chapter&nbsp;13</span></a>: DNS</td>
-<td>Add a real URL to the EC2 instance. Put the Shiny app into an iFrame on the site.</td>
+<td><a href="../sec2/2-4-app-admin.html"><span>Chapter&nbsp;10</span></a>: App Admin</td>
+<td>Add R, Python, RStudio Server, JupyterHub, palmer penguin fastAPI + App to the server.</td>
 </tr>
 <tr class="odd">
-<td><a href="../sec3/3-5-ssl.html"><span>Chapter&nbsp;14</span></a>: SSL</td>
-<td>Add SSL/HTTPS to the EC2 instance.</td>
+<td><a href="../sec2/2-5-scale.html"><span>Chapter&nbsp;11</span></a>: Servers</td>
+<td>Resize servers.</td>
 </tr>
 <tr class="even">
-<td><a href="../sec3/3-6-servers.html"><span>Chapter&nbsp;15</span></a>: Servers</td>
-<td>Resize servers.</td>
+<td><a href="../sec2/2-6-networking.html"><span>Chapter&nbsp;12</span></a>: Networking</td>
+<td>Set up a proxy (NGINX) to reach all services from the web.</td>
+</tr>
+<tr class="odd">
+<td><a href="../sec2/2-7-dns.html"><span>Chapter&nbsp;13</span></a>: DNS</td>
+<td>Add a real URL to the EC2 instance. Put the Shiny app into an iFrame on the Quarto site.</td>
+</tr>
+<tr class="even">
+<td><a href="../sec2/2-8-ssl.html"><span>Chapter&nbsp;14</span></a>: SSL</td>
+<td>Add SSL/HTTPS to the EC2 instance.</td>
 </tr>
 </tbody>
 </table>
@@ -654,6 +652,9 @@ <h1 class="title"><span id="sec-append-lab" class="quarto-section-identifier">Ap
       </a>          
   </div>
   <div class="nav-page nav-page-next">
+      <a href="../../chapters/append/cheatsheets.html" class="pagination-link">
+        <span class="nav-page-text"><span class="chapter-number">C</span>&nbsp; <span class="chapter-title">Cheatsheets</span></span> <i class="bi bi-arrow-right-short"></i>
+      </a>
   </div>
 </nav>
 </div> <!-- /content -->
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-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-5" aria-expanded="true" aria-label="Toggle section">
+          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true" aria-label="Toggle section">
             <i class="bi bi-chevron-right ms-2"></i>
           </a> 
       </div>
-      <ul id="quarto-sidebar-section-5" class="collapse list-unstyled sidebar-section depth1 show">  
+      <ul id="quarto-sidebar-section-4" class="collapse list-unstyled sidebar-section depth1 show">  
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
   <a href="../chapters/append/auth.html" class="sidebar-item-text sidebar-link">
@@ -320,6 +302,12 @@
   <a href="../chapters/append/lab-map.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">B</span>&nbsp; <span class="chapter-title">Lab Map</span></span></a>
   </div>
+</li>
+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../chapters/append/cheatsheets.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">C</span>&nbsp; <span class="chapter-title">Cheatsheets</span></span></a>
+  </div>
 </li>
       </ul>
   </li>
@@ -412,11 +400,10 @@ <h2 class="anchored" data-anchor-id="processes-and-people">Processes and People<
 <h2 class="anchored" data-anchor-id="about-this-book">About this book</h2>
 <p>Over the course of engaging with many organizations, I’ve seen which patterns work to grease the path to production for data scientists and which ones tend to impede it.</p>
 <p>My goal is that this book helps you create data science projects that are easier and simpler to deploy, and that you have the knowledge and skills to get them into production when it’s time.</p>
-<p>To that end this book is divided into four sections.</p>
+<p>To that end this book is divided into three sections.</p>
 <p><a href="@sec-1-intro">Section 1</a> is about applying DevOps best practices to a data science context. There’s a lot data scientists can learn from DevOps, but there are important differences between data science and general purpose software engineering that you’ll learn about.</p>
-<p><a href="@sec-2-intro">Section 2</a> is an introduction to the tools IT/Admins use in their work like the command line, bash, and Docker. These tools are all useful for you to understand as a data scientist and also will be useful if you end up having to do any IT/Admin tasks.</p>
-<p><a href="@sec-3-intro">Section 3</a> is a walk through of basic concepts in IT Administration that will get you to the point of being able to host and manage your own small server. If you are a hobbyist or have only a small data science team, this might make you able to operate without any IT/Admin support. Even if you do work at an organization with significant IT/Admin support, it will equip you with the vocabulary to talk to the IT/Admins at your organization and some basic skills of how to do IT/Admin tasks yourself.</p>
-<p><a href="@sec-4-intro">Section 4</a> is about how all of what you learned in Section 3 changes when you go to enterprise scale. If section 3 explains how to do IT/Admin tasks yourself, section 4 is my attempt to explain why you shouldn’t.</p>
+<p><a href="@sec-2-intro">Section 2</a> is a walk through of basic concepts in IT Administration that will get you to the point of being able to host and manage your own small server. If you are a hobbyist or have only a small data science team, this might make you able to operate without any IT/Admin support. Even if you do work at an organization with significant IT/Admin support, it will equip you with the vocabulary to talk to the IT/Admins at your organization and some basic skills of how to do IT/Admin tasks yourself.</p>
+<p><a href="@sec-3-intro">Section 3</a> is about how all of what you learned in Section 2 changes when you go to enterprise scale. If section 2 explains how to do IT/Admin tasks yourself, section 3 is my attempt to explain why you shouldn’t.</p>
 <section id="comprehension-questions" class="level3">
 <h3 class="anchored" data-anchor-id="comprehension-questions">Comprehension Questions</h3>
 <p>Each chapter in this book includes comprehension questions. As you get to the end of the chapter, take a moment to consider these questions. If you feel comfortable answering them, you’ve probably understood the content of the chapter pretty well.</p>
@@ -436,20 +423,7 @@ <h3 class="anchored" data-anchor-id="comprehension-questions">Comprehension Ques
 <p>In a mental map, you draw each of the nouns as nodes and connect them with arrows that are labelled to explain the relationship.</p>
 <p>Mental maps are a great way to test your mental models, so I’ll suggest them as comprehension questions in many chapters.</p>
 <p>Here’s an example about this book:</p>
-<div class="cell" data-eval="true">
-<div class="cell-output-display">
-<div>
-<div>
-<pre class="mermaid mermaid-js">graph LR
-    A[I] --&gt;|Wrote| B[DO4DS]
-    C[You] --&gt; |Are Reading| B
-    B --&gt; |Includes| D[Exercises]
-    D --&gt; |Some Are| E[Mind Maps]
-</pre>
-</div>
-</div>
-</div>
-</div>
+<p><img src="intro-images/mindmap.png" class="img-fluid" alt="A mindmap for this book: I *wrote* and YOU *read* DO4DS. DO4DS *includes* EXERCISES, *some are* MIND MAPS." width="600"></p>
 <p>Note how every node is a noun and the edges (labels on the arrows) are verbs. It’s pretty simple! But writing down the relationships between entities like this is a <strong>great</strong> check on understanding.</p>
 </div>
 </div>
@@ -464,49 +438,13 @@ <h3 class="anchored" data-anchor-id="labs">Labs</h3>
 <p>The whole thing will get auto-deployed from a git repo using GitHub Actions.</p>
 <p>From an architectural perspective, it’ll look something like this:</p>
 <p><img src="intro-images/lab-arch.png" class="img-fluid"></p>
-<div class="cell" data-eval="true">
-<div class="cell-output-display">
-<div>
-<div>
-<pre class="mermaid mermaid-js">graph LR
-    subgraph Palmer Penguins Site
-        A["EDA 
-        R Quarto"] 
-        B["Model Build 
-        Jupyter"] 
-        C["Model Explorer 
-        PyShiny"]
-    end
-    subgraph Git Repo
-        D[Repo] --&gt; |GHA| A
-        D --&gt; |GHA| B
-    end
-    subgraph AWS
-        subgraph EC2
-            F[Shiny]
-            G(RStudio Server)
-            H(Jupyter Hub)
-            I[FastAPI]
-            J[DuckDB]
-            J --&gt; I
-            F --&gt; C
-        end
-        subgraph S3
-            E[Model]
-        end
-    end
-
-</pre>
-</div>
-</div>
-</div>
-</div>
 <p>If you’re interested in exactly which pieces get completed in each chapter, check out <a href="append/lab-map.html">Appendix&nbsp;<span>B</span></a>.</p>
 </section>
 <section id="conventions" class="level3">
 <h3 class="anchored" data-anchor-id="conventions">Conventions</h3>
-<p>Throughout the book, I will <em>italicize</em> terms of art the first time I introduce them as well as the names of other publications. <strong>Bolding</strong> will be reserved for emphasis.</p>
-<p>R, Python, and system package names will be in <code>code font</code> and will have braces around them like <code>{package}</code>.</p>
+<p>Throughout the book, I will <em>italicize</em> terms of art the first time I introduce them as well as the names of other publications. Because so many of the technical terms in this book are usually referred to by abbreviations or acronyms, I’ll use the abbreviation or acronym in the text and include the full term in parentheses the first time it’s mentioned.</p>
+<p><strong>Bolding</strong> will be reserved for emphasis.</p>
+<p>R, Python, and system package names will be in <code>code font</code> and will have braces around them like <code>{package}</code>. Networking concepts and terms, including URLs, will appear in <span class="math inline">\(\text{equation font}\)</span>.</p>
 <p>Variables that you would replace with your own values will appear in <code>code font</code> inside angled brackets like <code>&lt;your-variable&gt;</code>.</p>
 
 
diff --git a/chapters/sec1/1-0-sec-intro.html b/chapters/sec1/1-0-sec-intro.html
index fc621bf7a..93bea9dbe 100644
--- a/chapters/sec1/1-0-sec-intro.html
+++ b/chapters/sec1/1-0-sec-intro.html
@@ -177,13 +177,19 @@
   <a href="../../chapters/sec1/1-5-deployments.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">5</span>&nbsp; <span class="chapter-title">Deployments and code promotion</span></span></a>
   </div>
+</li>
+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/sec1/1-6-docker.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">6</span>&nbsp; <span class="chapter-title">Demystifying Docker</span></span></a>
+  </div>
 </li>
       </ul>
   </li>
         <li class="sidebar-item sidebar-item-section">
       <div class="sidebar-item-container"> 
             <a href="../../chapters/sec2/2-0-sec-intro.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text">IT/Admin Tools</span></a>
+ <span class="menu-text">IT/Admin for Data Science</span></a>
           <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-2" aria-expanded="true" aria-label="Toggle section">
             <i class="bi bi-chevron-right ms-2"></i>
           </a> 
@@ -191,121 +197,98 @@
       <ul id="quarto-sidebar-section-2" class="collapse list-unstyled sidebar-section depth1 show">  
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec2/2-1-cmd-line.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">6</span>&nbsp; <span class="chapter-title">Opening the Command Line</span></span></a>
-  </div>
-</li>
-          <li class="sidebar-item">
-  <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec2/2-2-cmd-line-use.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">7</span>&nbsp; <span class="chapter-title">Using the Command Line</span></span></a>
+  <a href="../../chapters/sec2/2-1-cloud.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">7</span>&nbsp; <span class="chapter-title">The Cloud</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec2/2-3-ssh.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">8</span>&nbsp; <span class="chapter-title">Secure server connections with SSH</span></span></a>
+  <a href="../../chapters/sec2/2-2-cmd-line.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">8</span>&nbsp; <span class="chapter-title">Customizing the command line</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec2/2-4-docker.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">9</span>&nbsp; <span class="chapter-title">Demystifying Docker</span></span></a>
+  <a href="../../chapters/sec2/2-3-linux.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">9</span>&nbsp; <span class="chapter-title">Intro to Linux Administration</span></span></a>
   </div>
 </li>
-      </ul>
-  </li>
-        <li class="sidebar-item sidebar-item-section">
-      <div class="sidebar-item-container"> 
-            <a href="../../chapters/sec3/3-0-sec-intro.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text">IT/Admin for Data Science</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-3" aria-expanded="true" aria-label="Toggle section">
-            <i class="bi bi-chevron-right ms-2"></i>
-          </a> 
-      </div>
-      <ul id="quarto-sidebar-section-3" class="collapse list-unstyled sidebar-section depth1 show">  
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-1-cloud.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Getting Started with the Cloud</span></span></a>
+  <a href="../../chapters/sec2/2-4-app-admin.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Application administration</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-2-linux-admin.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Basic Linux SysAdmin</span></span></a>
+  <a href="../../chapters/sec2/2-5-scale.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Server Resources and Scaling</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-3-networking.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-6-networking.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">12</span>&nbsp; <span class="chapter-title">Intro to Computer Networks</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-4-dns.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-7-dns.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">13</span>&nbsp; <span class="chapter-title">DNS allows for human-readable addresses</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-5-ssl.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-8-ssl.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">14</span>&nbsp; <span class="chapter-title">You should use SSL/HTTPS</span></span></a>
   </div>
-</li>
-          <li class="sidebar-item">
-  <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-6-servers.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Choosing the right server for you</span></span></a>
-  </div>
 </li>
       </ul>
   </li>
         <li class="sidebar-item sidebar-item-section">
       <div class="sidebar-item-container"> 
-            <a href="../../chapters/sec4/4-0-sec-intro.html" class="sidebar-item-text sidebar-link">
+            <a href="../../chapters/sec3/3-0-sec-intro.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text">Making it Enterprise-Grade</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true" aria-label="Toggle section">
+          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-3" aria-expanded="true" aria-label="Toggle section">
             <i class="bi bi-chevron-right ms-2"></i>
           </a> 
       </div>
-      <ul id="quarto-sidebar-section-4" class="collapse list-unstyled sidebar-section depth1 show">  
+      <ul id="quarto-sidebar-section-3" class="collapse list-unstyled sidebar-section depth1 show">  
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec4/4-1-os-ds-in-ent.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></a>
+  <a href="../../chapters/sec3/3-1-os-ds-in-ent.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec4/4-2-ent-networks.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></a>
+  <a href="../../chapters/sec3/3-2-ent-networks.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec4/4-3-auth.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></a>
+  <a href="../../chapters/sec3/3-3-auth.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec4/4-4-ent-servers.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">19</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></a>
+  <a href="../../chapters/sec3/3-4-ent-servers.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></a>
   </div>
 </li>
       </ul>
   </li>
         <li class="sidebar-item sidebar-item-section">
       <div class="sidebar-item-container"> 
-            <a class="sidebar-item-text sidebar-link text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-5" aria-expanded="true">
+            <a class="sidebar-item-text sidebar-link text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true">
  <span class="menu-text">Appendices</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-5" aria-expanded="true" aria-label="Toggle section">
+          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true" aria-label="Toggle section">
             <i class="bi bi-chevron-right ms-2"></i>
           </a> 
       </div>
-      <ul id="quarto-sidebar-section-5" class="collapse list-unstyled sidebar-section depth1 show">  
+      <ul id="quarto-sidebar-section-4" class="collapse list-unstyled sidebar-section depth1 show">  
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
   <a href="../../chapters/append/auth.html" class="sidebar-item-text sidebar-link">
@@ -317,6 +300,12 @@
   <a href="../../chapters/append/lab-map.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">B</span>&nbsp; <span class="chapter-title">Lab Map</span></span></a>
   </div>
+</li>
+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/append/cheatsheets.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">C</span>&nbsp; <span class="chapter-title">Cheatsheets</span></span></a>
+  </div>
 </li>
       </ul>
   </li>
@@ -334,6 +323,7 @@ <h2 id="toc-title">Table of contents</h2>
   <li><a href="#app-architecture" id="toc-app-architecture" class="nav-link" data-scroll-target="#app-architecture">App Architecture</a></li>
   <li><a href="#monitoring-and-logging" id="toc-monitoring-and-logging" class="nav-link" data-scroll-target="#monitoring-and-logging">Monitoring and Logging</a></li>
   <li><a href="#deployments" id="toc-deployments" class="nav-link" data-scroll-target="#deployments">Deployments</a></li>
+  <li><a href="#docker-for-data-science" id="toc-docker-for-data-science" class="nav-link" data-scroll-target="#docker-for-data-science">Docker for Data Science</a></li>
   <li><a href="#labs-in-this-section" id="toc-labs-in-this-section" class="nav-link" data-scroll-target="#labs-in-this-section">Labs in this section</a></li>
   </ul>
 <div class="toc-actions"><div><i class="bi bi-github"></i></div><div class="action-links"><p><a href="https://github.com/akgold/do4ds/edit/main/chapters/sec1/1-0-sec-intro.qmd" class="toc-action">Edit this page</a></p></div></div></nav>
@@ -392,11 +382,15 @@ <h3 class="anchored" data-anchor-id="monitoring-and-logging">Monitoring and Logg
 <h3 class="anchored" data-anchor-id="deployments">Deployments</h3>
 <p>DevOps also addresses the “breaks on deployment” issue. Perhaps your code was thoroughly tested, but only locally, or perhaps you don’t test your code. DevOps patterns are designed to increase the likelihood your code will deploy right <em>the first time</em>. <a href="1-5-deployments.html">Chapter&nbsp;<span>5</span></a> gets into how to design a deployment and promotion system that is robust.</p>
 </section>
+<section id="docker-for-data-science" class="level3">
+<h3 class="anchored" data-anchor-id="docker-for-data-science">Docker for Data Science</h3>
+<p>Docker is an increasingly popular tool in the software development and data science world that allows for the easy capture and sharing of the environment around code. While Docker itself doesn’t solve these problems, it’s increasingly popular to use Docker in a data science context, which is why <a href="1-6-docker.html">Chapter&nbsp;<span>6</span></a> is a basic introduction to what Docker is and how to use it.</p>
+</section>
 <section id="labs-in-this-section" class="level2">
 <h2 class="anchored" data-anchor-id="labs-in-this-section">Labs in this section</h2>
 <p>Each chapter in this section has a lab so you can get hands-on experience implementing the best practices I propose.</p>
 <p>If you complete the labs, you’ll have stood up your Palmer Penguins website to explore the relationship between penguin bill length and mass. Your website will include pages on exploratory data analysis and model building. This website will automatically build and deploy based on changes in a git repo.</p>
-<p>By the end of the section, you’ll also create a Shiny app that visualizes model predictions and an API that hosts the model and provides real-time predictions to the app. We won’t get to standing up the app and API to live on your website – that’ll have to wait for <a href="@sec-3-intro">Section 3</a>.</p>
+<p>By the end of the section, you’ll also create a Shiny app that visualizes model predictions and an API that hosts the model and provides real-time predictions to the app. Additionally, you’ll get to practice putting that API inside a Docker Container to see how using Docker can make your life easier when moving code around.</p>
 <p>For more details on exactly what you’ll do in each chapter, see <a href="../append/lab-map.html">Appendix&nbsp;<span>B</span></a>.</p>
 
 
diff --git a/chapters/sec1/1-1-env-as-code.html b/chapters/sec1/1-1-env-as-code.html
index 4a11c3bfa..7c9b3d2ac 100644
--- a/chapters/sec1/1-1-env-as-code.html
+++ b/chapters/sec1/1-1-env-as-code.html
@@ -211,13 +211,19 @@
   <a href="../../chapters/sec1/1-5-deployments.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">5</span>&nbsp; <span class="chapter-title">Deployments and code promotion</span></span></a>
   </div>
+</li>
+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/sec1/1-6-docker.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">6</span>&nbsp; <span class="chapter-title">Demystifying Docker</span></span></a>
+  </div>
 </li>
       </ul>
   </li>
         <li class="sidebar-item sidebar-item-section">
       <div class="sidebar-item-container"> 
             <a href="../../chapters/sec2/2-0-sec-intro.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text">IT/Admin Tools</span></a>
+ <span class="menu-text">IT/Admin for Data Science</span></a>
           <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-2" aria-expanded="true" aria-label="Toggle section">
             <i class="bi bi-chevron-right ms-2"></i>
           </a> 
@@ -225,121 +231,98 @@
       <ul id="quarto-sidebar-section-2" class="collapse list-unstyled sidebar-section depth1 show">  
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec2/2-1-cmd-line.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">6</span>&nbsp; <span class="chapter-title">Opening the Command Line</span></span></a>
+  <a href="../../chapters/sec2/2-1-cloud.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">7</span>&nbsp; <span class="chapter-title">The Cloud</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec2/2-2-cmd-line-use.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">7</span>&nbsp; <span class="chapter-title">Using the Command Line</span></span></a>
+  <a href="../../chapters/sec2/2-2-cmd-line.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">8</span>&nbsp; <span class="chapter-title">Customizing the command line</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec2/2-3-ssh.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">8</span>&nbsp; <span class="chapter-title">Secure server connections with SSH</span></span></a>
+  <a href="../../chapters/sec2/2-3-linux.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">9</span>&nbsp; <span class="chapter-title">Intro to Linux Administration</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec2/2-4-docker.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">9</span>&nbsp; <span class="chapter-title">Demystifying Docker</span></span></a>
+  <a href="../../chapters/sec2/2-4-app-admin.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Application administration</span></span></a>
   </div>
 </li>
-      </ul>
-  </li>
-        <li class="sidebar-item sidebar-item-section">
-      <div class="sidebar-item-container"> 
-            <a href="../../chapters/sec3/3-0-sec-intro.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text">IT/Admin for Data Science</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-3" aria-expanded="true" aria-label="Toggle section">
-            <i class="bi bi-chevron-right ms-2"></i>
-          </a> 
-      </div>
-      <ul id="quarto-sidebar-section-3" class="collapse list-unstyled sidebar-section depth1 show">  
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-1-cloud.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Getting Started with the Cloud</span></span></a>
+  <a href="../../chapters/sec2/2-5-scale.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Server Resources and Scaling</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-2-linux-admin.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Basic Linux SysAdmin</span></span></a>
-  </div>
-</li>
-          <li class="sidebar-item">
-  <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-3-networking.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-6-networking.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">12</span>&nbsp; <span class="chapter-title">Intro to Computer Networks</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-4-dns.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-7-dns.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">13</span>&nbsp; <span class="chapter-title">DNS allows for human-readable addresses</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-5-ssl.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-8-ssl.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">14</span>&nbsp; <span class="chapter-title">You should use SSL/HTTPS</span></span></a>
   </div>
-</li>
-          <li class="sidebar-item">
-  <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-6-servers.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Choosing the right server for you</span></span></a>
-  </div>
 </li>
       </ul>
   </li>
         <li class="sidebar-item sidebar-item-section">
       <div class="sidebar-item-container"> 
-            <a href="../../chapters/sec4/4-0-sec-intro.html" class="sidebar-item-text sidebar-link">
+            <a href="../../chapters/sec3/3-0-sec-intro.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text">Making it Enterprise-Grade</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true" aria-label="Toggle section">
+          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-3" aria-expanded="true" aria-label="Toggle section">
             <i class="bi bi-chevron-right ms-2"></i>
           </a> 
       </div>
-      <ul id="quarto-sidebar-section-4" class="collapse list-unstyled sidebar-section depth1 show">  
+      <ul id="quarto-sidebar-section-3" class="collapse list-unstyled sidebar-section depth1 show">  
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec4/4-1-os-ds-in-ent.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></a>
+  <a href="../../chapters/sec3/3-1-os-ds-in-ent.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec4/4-2-ent-networks.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></a>
+  <a href="../../chapters/sec3/3-2-ent-networks.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec4/4-3-auth.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></a>
+  <a href="../../chapters/sec3/3-3-auth.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec4/4-4-ent-servers.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">19</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></a>
+  <a href="../../chapters/sec3/3-4-ent-servers.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></a>
   </div>
 </li>
       </ul>
   </li>
         <li class="sidebar-item sidebar-item-section">
       <div class="sidebar-item-container"> 
-            <a class="sidebar-item-text sidebar-link text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-5" aria-expanded="true">
+            <a class="sidebar-item-text sidebar-link text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true">
  <span class="menu-text">Appendices</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-5" aria-expanded="true" aria-label="Toggle section">
+          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true" aria-label="Toggle section">
             <i class="bi bi-chevron-right ms-2"></i>
           </a> 
       </div>
-      <ul id="quarto-sidebar-section-5" class="collapse list-unstyled sidebar-section depth1 show">  
+      <ul id="quarto-sidebar-section-4" class="collapse list-unstyled sidebar-section depth1 show">  
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
   <a href="../../chapters/append/auth.html" class="sidebar-item-text sidebar-link">
@@ -351,6 +334,12 @@
   <a href="../../chapters/append/lab-map.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">B</span>&nbsp; <span class="chapter-title">Lab Map</span></span></a>
   </div>
+</li>
+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/append/cheatsheets.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">C</span>&nbsp; <span class="chapter-title">Cheatsheets</span></span></a>
+  </div>
 </li>
       </ul>
   </li>
@@ -429,8 +418,8 @@ <h2 data-number="1.1" class="anchored" data-anchor-id="environments-have-layers"
 <p><strong>Layers of a Data Science Environments</strong></p>
 <table class="table">
 <colgroup>
-<col style="width: 20%">
-<col style="width: 33%">
+<col style="width: 19%">
+<col style="width: 37%">
 </colgroup>
 <thead>
 <tr class="header">
@@ -599,7 +588,7 @@ <h2 data-number="1.5" class="anchored" data-anchor-id="reproducing-the-rest-of-t
 </figure>
 </div>
 <p>In most cases, the only requirement to run any Docker container is having Docker installed. If you put your project in a Docker container and it runs today, you can be reasonably confident that the container itself can run almost anywhere else, irrespective of what else is running on that machine.<a href="#fn2" class="footnote-ref" id="fnref2" role="doc-noteref"><sup>2</sup></a></p>
-<p>In <a href="../sec2/2-4-docker.html">Chapter&nbsp;<span>9</span></a>, you’ll learn the basics of how to use Docker as a tool for reproducing a data science project and moving it around.</p>
+<p>In <a href="1-6-docker.html">Chapter&nbsp;<span>6</span></a>, you’ll learn the basics of how to use Docker as a tool for reproducing a data science project and moving it around.</p>
 </section>
 <section id="comprehension-questions" class="level2" data-number="1.6">
 <h2 data-number="1.6" class="anchored" data-anchor-id="comprehension-questions"><span class="header-section-number">1.6</span> Comprehension Questions</h2>
@@ -726,7 +715,7 @@ <h2 data-number="1.8" class="anchored" data-anchor-id="cheat-renv-venv"><span cl
 <h3 data-number="1.8.1" class="anchored" data-anchor-id="checking-library-repository-status"><span class="header-section-number">1.8.1</span> Checking library + repository status</h3>
 <table class="table">
 <colgroup>
-<col style="width: 51%">
+<col style="width: 54%">
 <col style="width: 22%">
 <col style="width: 22%">
 </colgroup>
@@ -751,9 +740,9 @@ <h3 data-number="1.8.2" class="anchored" data-anchor-id="creating-and-using-a-st
 <p>Make sure you’re in a standalone project library.</p>
 <table class="table">
 <colgroup>
-<col style="width: 29%">
-<col style="width: 29%">
-<col style="width: 29%">
+<col style="width: 30%">
+<col style="width: 30%">
+<col style="width: 30%">
 </colgroup>
 <thead>
 <tr class="header">
@@ -765,30 +754,30 @@ <h3 data-number="1.8.2" class="anchored" data-anchor-id="creating-and-using-a-st
 <tbody>
 <tr class="odd">
 <td>Make sure you’ve got <code>{r  env}/{venv}</code>.</td>
-<td><code>in s t a l l .packages("renv")</code></td>
+<td><code>in s t a l l  .packages("renv")</code></td>
 <td>Included w/ Python 3.5+</td>
 </tr>
 <tr class="even">
 <td>Create a standalone library.</td>
 <td><code>renv::init()</code></td>
-<td><p><code>p y t hon -m venv &lt;dir&gt;</code></p>
-<p>Convention: <code>u s e .venv for &lt;dir&gt;</code></p></td>
+<td><p><code>p y t  hon -m venv &lt;dir&gt;</code></p>
+<p>Convention: <code>u s  e .venv for &lt;dir&gt;</code></p></td>
 </tr>
 <tr class="odd">
 <td>Activate project library.</td>
 <td><p><code>renv::activate()</code></p>
 <p>Happens automatically if using projects.</p></td>
-<td><code>sou r c e &lt; d ir&gt; /bin/activate</code></td>
+<td><code>sou r c e &lt; d  ir&gt; /bin/activate</code></td>
 </tr>
 <tr class="even">
 <td>Install packages as normal.</td>
-<td><code>ins t a l l . packages("&lt;pkg&gt;")</code></td>
-<td><code>pyth o n - m pip install &lt;pkg&gt;</code></td>
+<td><code>ins t a l l .  packages("&lt;pkg&gt;")</code></td>
+<td><code>pyth o n - m  pip install &lt;pkg&gt;</code></td>
 </tr>
 <tr class="odd">
 <td>Snapshot package state.</td>
 <td><code>renv::snapshot()</code></td>
-<td><code>pip fr e e z e &gt;  requirements.txt</code></td>
+<td><code>pip fr e e z e &gt;   requirements.txt</code></td>
 </tr>
 <tr class="even">
 <td>Exit project environment.</td>
@@ -803,9 +792,9 @@ <h3 data-number="1.8.3" class="anchored" data-anchor-id="collaborating-on-someon
 <p>Start by downloading the project into a directory on your machine.</p>
 <table class="table">
 <colgroup>
-<col style="width: 29%">
-<col style="width: 29%">
-<col style="width: 29%">
+<col style="width: 30%">
+<col style="width: 30%">
+<col style="width: 30%">
 </colgroup>
 <thead>
 <tr class="header">
@@ -817,25 +806,25 @@ <h3 data-number="1.8.3" class="anchored" data-anchor-id="collaborating-on-someon
 <tbody>
 <tr class="odd">
 <td>Move into project directory.</td>
-<td><p><code>se t w d ("&lt;project-dir&gt;")</code></p>
+<td><p><code>set wd  ("&lt;project-dir&gt;")</code></p>
 <p>Or just open R project in RStudio.</p></td>
 <td><code>cd &lt;project-dir&gt;</code></td>
 </tr>
 <tr class="even">
 <td>Create project environment.</td>
 <td><code>renv::init()</code></td>
-<td><p><code>p y t hon -m venv &lt;dir&gt;</code></p>
-<p>Recommend: <code>u s e .venv for &lt;dir&gt;</code></p></td>
+<td><p><code>py thon -m venv &lt;dir&gt;</code></p>
+<p>Recommend: <code>u se .venv for &lt;dir&gt;</code></p></td>
 </tr>
 <tr class="odd">
 <td>Enter project environment.</td>
 <td>Happens automatically or <code>renv::activate()</code></td>
-<td><code>s o u rce &lt; d ir&gt; /bin/activate</code></td>
+<td><code>source &lt; dir&gt; /bin/activate</code></td>
 </tr>
 <tr class="even">
 <td>Restore packages.</td>
 <td>Happens automatically or <code>renv::restore()</code></td>
-<td><code>p ip i n s t all - r  requirements.txt</code></td>
+<td><code>pip install -r   requirements.txt</code></td>
 </tr>
 </tbody>
 </table>
diff --git a/chapters/sec1/1-2-proj-arch.html b/chapters/sec1/1-2-proj-arch.html
index ecf040d38..1536d542b 100644
--- a/chapters/sec1/1-2-proj-arch.html
+++ b/chapters/sec1/1-2-proj-arch.html
@@ -216,13 +216,19 @@
   <a href="../../chapters/sec1/1-5-deployments.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">5</span>&nbsp; <span class="chapter-title">Deployments and code promotion</span></span></a>
   </div>
+</li>
+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/sec1/1-6-docker.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">6</span>&nbsp; <span class="chapter-title">Demystifying Docker</span></span></a>
+  </div>
 </li>
       </ul>
   </li>
         <li class="sidebar-item sidebar-item-section">
       <div class="sidebar-item-container"> 
             <a href="../../chapters/sec2/2-0-sec-intro.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text">IT/Admin Tools</span></a>
+ <span class="menu-text">IT/Admin for Data Science</span></a>
           <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-2" aria-expanded="true" aria-label="Toggle section">
             <i class="bi bi-chevron-right ms-2"></i>
           </a> 
@@ -230,121 +236,98 @@
       <ul id="quarto-sidebar-section-2" class="collapse list-unstyled sidebar-section depth1 show">  
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec2/2-1-cmd-line.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">6</span>&nbsp; <span class="chapter-title">Opening the Command Line</span></span></a>
+  <a href="../../chapters/sec2/2-1-cloud.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">7</span>&nbsp; <span class="chapter-title">The Cloud</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec2/2-2-cmd-line-use.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">7</span>&nbsp; <span class="chapter-title">Using the Command Line</span></span></a>
+  <a href="../../chapters/sec2/2-2-cmd-line.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">8</span>&nbsp; <span class="chapter-title">Customizing the command line</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec2/2-3-ssh.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">8</span>&nbsp; <span class="chapter-title">Secure server connections with SSH</span></span></a>
+  <a href="../../chapters/sec2/2-3-linux.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">9</span>&nbsp; <span class="chapter-title">Intro to Linux Administration</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec2/2-4-docker.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">9</span>&nbsp; <span class="chapter-title">Demystifying Docker</span></span></a>
+  <a href="../../chapters/sec2/2-4-app-admin.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Application administration</span></span></a>
   </div>
 </li>
-      </ul>
-  </li>
-        <li class="sidebar-item sidebar-item-section">
-      <div class="sidebar-item-container"> 
-            <a href="../../chapters/sec3/3-0-sec-intro.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text">IT/Admin for Data Science</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-3" aria-expanded="true" aria-label="Toggle section">
-            <i class="bi bi-chevron-right ms-2"></i>
-          </a> 
-      </div>
-      <ul id="quarto-sidebar-section-3" class="collapse list-unstyled sidebar-section depth1 show">  
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-1-cloud.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Getting Started with the Cloud</span></span></a>
+  <a href="../../chapters/sec2/2-5-scale.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Server Resources and Scaling</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-2-linux-admin.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Basic Linux SysAdmin</span></span></a>
-  </div>
-</li>
-          <li class="sidebar-item">
-  <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-3-networking.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-6-networking.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">12</span>&nbsp; <span class="chapter-title">Intro to Computer Networks</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-4-dns.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-7-dns.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">13</span>&nbsp; <span class="chapter-title">DNS allows for human-readable addresses</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-5-ssl.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-8-ssl.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">14</span>&nbsp; <span class="chapter-title">You should use SSL/HTTPS</span></span></a>
   </div>
-</li>
-          <li class="sidebar-item">
-  <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-6-servers.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Choosing the right server for you</span></span></a>
-  </div>
 </li>
       </ul>
   </li>
         <li class="sidebar-item sidebar-item-section">
       <div class="sidebar-item-container"> 
-            <a href="../../chapters/sec4/4-0-sec-intro.html" class="sidebar-item-text sidebar-link">
+            <a href="../../chapters/sec3/3-0-sec-intro.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text">Making it Enterprise-Grade</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true" aria-label="Toggle section">
+          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-3" aria-expanded="true" aria-label="Toggle section">
             <i class="bi bi-chevron-right ms-2"></i>
           </a> 
       </div>
-      <ul id="quarto-sidebar-section-4" class="collapse list-unstyled sidebar-section depth1 show">  
+      <ul id="quarto-sidebar-section-3" class="collapse list-unstyled sidebar-section depth1 show">  
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec4/4-1-os-ds-in-ent.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></a>
+  <a href="../../chapters/sec3/3-1-os-ds-in-ent.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></a>
   </div>
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           <li class="sidebar-item">
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-  <a href="../../chapters/sec4/4-2-ent-networks.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></a>
+  <a href="../../chapters/sec3/3-2-ent-networks.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></a>
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-  <a href="../../chapters/sec4/4-3-auth.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></a>
+  <a href="../../chapters/sec3/3-3-auth.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></a>
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-  <a href="../../chapters/sec4/4-4-ent-servers.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">19</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></a>
+  <a href="../../chapters/sec3/3-4-ent-servers.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></a>
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       <div class="sidebar-item-container"> 
-            <a class="sidebar-item-text sidebar-link text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-5" aria-expanded="true">
+            <a class="sidebar-item-text sidebar-link text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true">
  <span class="menu-text">Appendices</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-5" aria-expanded="true" aria-label="Toggle section">
+          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true" aria-label="Toggle section">
             <i class="bi bi-chevron-right ms-2"></i>
           </a> 
       </div>
-      <ul id="quarto-sidebar-section-5" class="collapse list-unstyled sidebar-section depth1 show">  
+      <ul id="quarto-sidebar-section-4" class="collapse list-unstyled sidebar-section depth1 show">  
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@@ -356,6 +339,12 @@
   <a href="../../chapters/append/lab-map.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">B</span>&nbsp; <span class="chapter-title">Lab Map</span></span></a>
   </div>
+</li>
+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/append/cheatsheets.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">C</span>&nbsp; <span class="chapter-title">Cheatsheets</span></span></a>
+  </div>
 </li>
       </ul>
   </li>
@@ -629,7 +618,7 @@ <h2 data-number="2.7" class="anchored" data-anchor-id="consider-auth-to-data-up-
 <p>But if you need to provide different data access to different users, you’re much more constrained. First off, you probably need to use an app rather than a report so that you can respond to which user is accessing the app.</p>
 <p>Then you have to figure out how you’re actually going to change data access based on who’s viewing the app.</p>
 <p>Sometimes this can be accomplished in the app itself. Many app frameworks pass the username or user groups into the session, and you can write code that changes app behavior based on the user. For example, you can gate access to certain tabs or features of your app based on the user.</p>
-<p>Sometimes you’ll actually have to pass database credentials along to the database. If this is the case for you, you’ll need to figure out how to establish the user’s database credentials, how to make sure those credentials stay only in the user’s session, and how those credentials get passed along to the database. This is most commonly done with technologies like Kerberos or OAuth and require coordination with an IT/Admin. More on this topic in <a href="../sec4/4-3-auth.html">Chapter&nbsp;<span>18</span></a>.</p>
+<p>Sometimes you’ll actually have to pass database credentials along to the database. If this is the case for you, you’ll need to figure out how to establish the user’s database credentials, how to make sure those credentials stay only in the user’s session, and how those credentials get passed along to the database. This is most commonly done with technologies like Kerberos or OAuth and require coordination with an IT/Admin. More on this topic in <a href="../sec3/3-3-auth.html">Chapter&nbsp;<span>17</span></a>.</p>
 </section>
 <section id="create-an-api-if-you-need-it" class="level2" data-number="2.8">
 <h2 data-number="2.8" class="anchored" data-anchor-id="create-an-api-if-you-need-it"><span class="header-section-number">2.8</span> Create an API if you need it</h2>
diff --git a/chapters/sec1/1-3-data-access.html b/chapters/sec1/1-3-data-access.html
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   <a href="../../chapters/sec1/1-5-deployments.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">5</span>&nbsp; <span class="chapter-title">Deployments and code promotion</span></span></a>
   </div>
+</li>
+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/sec1/1-6-docker.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">6</span>&nbsp; <span class="chapter-title">Demystifying Docker</span></span></a>
+  </div>
 </li>
       </ul>
   </li>
         <li class="sidebar-item sidebar-item-section">
       <div class="sidebar-item-container"> 
             <a href="../../chapters/sec2/2-0-sec-intro.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text">IT/Admin Tools</span></a>
+ <span class="menu-text">IT/Admin for Data Science</span></a>
           <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-2" aria-expanded="true" aria-label="Toggle section">
             <i class="bi bi-chevron-right ms-2"></i>
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@@ -225,121 +231,98 @@
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-  <a href="../../chapters/sec2/2-1-cmd-line.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">6</span>&nbsp; <span class="chapter-title">Opening the Command Line</span></span></a>
+  <a href="../../chapters/sec2/2-1-cloud.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">7</span>&nbsp; <span class="chapter-title">The Cloud</span></span></a>
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-  <a href="../../chapters/sec2/2-2-cmd-line-use.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">7</span>&nbsp; <span class="chapter-title">Using the Command Line</span></span></a>
+  <a href="../../chapters/sec2/2-2-cmd-line.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">8</span>&nbsp; <span class="chapter-title">Customizing the command line</span></span></a>
   </div>
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-  <a href="../../chapters/sec2/2-3-ssh.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">8</span>&nbsp; <span class="chapter-title">Secure server connections with SSH</span></span></a>
+  <a href="../../chapters/sec2/2-3-linux.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">9</span>&nbsp; <span class="chapter-title">Intro to Linux Administration</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec2/2-4-docker.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">9</span>&nbsp; <span class="chapter-title">Demystifying Docker</span></span></a>
+  <a href="../../chapters/sec2/2-4-app-admin.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Application administration</span></span></a>
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-      </ul>
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-        <li class="sidebar-item sidebar-item-section">
-      <div class="sidebar-item-container"> 
-            <a href="../../chapters/sec3/3-0-sec-intro.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text">IT/Admin for Data Science</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-3" aria-expanded="true" aria-label="Toggle section">
-            <i class="bi bi-chevron-right ms-2"></i>
-          </a> 
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-      <ul id="quarto-sidebar-section-3" class="collapse list-unstyled sidebar-section depth1 show">  
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-  <a href="../../chapters/sec3/3-1-cloud.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Getting Started with the Cloud</span></span></a>
+  <a href="../../chapters/sec2/2-5-scale.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Server Resources and Scaling</span></span></a>
   </div>
 </li>
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   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-2-linux-admin.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Basic Linux SysAdmin</span></span></a>
-  </div>
-</li>
-          <li class="sidebar-item">
-  <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-3-networking.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-6-networking.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">12</span>&nbsp; <span class="chapter-title">Intro to Computer Networks</span></span></a>
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-  <a href="../../chapters/sec3/3-4-dns.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-7-dns.html" class="sidebar-item-text sidebar-link">
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 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-5-ssl.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-8-ssl.html" class="sidebar-item-text sidebar-link">
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-</li>
-          <li class="sidebar-item">
-  <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-6-servers.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Choosing the right server for you</span></span></a>
-  </div>
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-            <a href="../../chapters/sec4/4-0-sec-intro.html" class="sidebar-item-text sidebar-link">
+            <a href="../../chapters/sec3/3-0-sec-intro.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text">Making it Enterprise-Grade</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true" aria-label="Toggle section">
+          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-3" aria-expanded="true" aria-label="Toggle section">
             <i class="bi bi-chevron-right ms-2"></i>
           </a> 
       </div>
-      <ul id="quarto-sidebar-section-4" class="collapse list-unstyled sidebar-section depth1 show">  
+      <ul id="quarto-sidebar-section-3" class="collapse list-unstyled sidebar-section depth1 show">  
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec4/4-1-os-ds-in-ent.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></a>
+  <a href="../../chapters/sec3/3-1-os-ds-in-ent.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec4/4-2-ent-networks.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></a>
+  <a href="../../chapters/sec3/3-2-ent-networks.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec4/4-3-auth.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></a>
+  <a href="../../chapters/sec3/3-3-auth.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec4/4-4-ent-servers.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">19</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></a>
+  <a href="../../chapters/sec3/3-4-ent-servers.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></a>
   </div>
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       </ul>
   </li>
         <li class="sidebar-item sidebar-item-section">
       <div class="sidebar-item-container"> 
-            <a class="sidebar-item-text sidebar-link text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-5" aria-expanded="true">
+            <a class="sidebar-item-text sidebar-link text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true">
  <span class="menu-text">Appendices</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-5" aria-expanded="true" aria-label="Toggle section">
+          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true" aria-label="Toggle section">
             <i class="bi bi-chevron-right ms-2"></i>
           </a> 
       </div>
-      <ul id="quarto-sidebar-section-5" class="collapse list-unstyled sidebar-section depth1 show">  
+      <ul id="quarto-sidebar-section-4" class="collapse list-unstyled sidebar-section depth1 show">  
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
   <a href="../../chapters/append/auth.html" class="sidebar-item-text sidebar-link">
@@ -351,6 +334,12 @@
   <a href="../../chapters/append/lab-map.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">B</span>&nbsp; <span class="chapter-title">Lab Map</span></span></a>
   </div>
+</li>
+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/append/cheatsheets.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">C</span>&nbsp; <span class="chapter-title">Cheatsheets</span></span></a>
+  </div>
 </li>
       </ul>
   </li>
@@ -389,7 +378,7 @@ <h2 id="toc-title">Table of contents</h2>
   <li><a href="#step-2-call-the-model-api-from-code" id="toc-step-2-call-the-model-api-from-code" class="nav-link" data-scroll-target="#step-2-call-the-model-api-from-code"><span class="header-section-number">3.6.2</span> Step 2: Call the model API from code</a></li>
   <li><a href="#step-3-build-a-shiny-app" id="toc-step-3-build-a-shiny-app" class="nav-link" data-scroll-target="#step-3-build-a-shiny-app"><span class="header-section-number">3.6.3</span> Step 3: Build a shiny app</a></li>
   </ul></li>
-  <li><a href="#http-code-cheatsheet" id="toc-http-code-cheatsheet" class="nav-link" data-scroll-target="#http-code-cheatsheet"><span class="header-section-number">3.7</span> HTTP Code Cheatsheet</a></li>
+  <li><a href="#cheat-http" id="toc-cheat-http" class="nav-link" data-scroll-target="#cheat-http"><span class="header-section-number">3.7</span> HTTP Code Cheatsheet</a></li>
   </ul>
 <div class="toc-actions"><div><i class="bi bi-github"></i></div><div class="action-links"><p><a href="https://github.com/akgold/do4ds/edit/main/chapters/sec1/1-3-data-access.qmd" class="toc-action">Edit this page</a></p></div></div></nav>
     </div>
@@ -596,7 +585,7 @@ <h3 data-number="3.3.2" class="anchored" data-anchor-id="setting-environment-var
 <p>Setting environment variables in production is a little harder.</p>
 <p>Just moving your secrets from your code into a different file you push to prod is still bad. And using <code>{keyring}</code> in a production environment is quite cumbersome.</p>
 <p>Your production environment may provide environment management tools. For example, GitHub Actions and Posit Connect both provide you the ability to set secrets that aren’t visible to the users, but are accessible to the code at runtime in an environment variable.</p>
-<p>Increasingly, organizations are using token-based authorization schemes that just exchange one cryptographically secure token for another, never relying on credentials at all. The tradeoff for the enhanced security is that they can be difficult to implement, likely requiring coordination with an IT/Admin to use technologies like Kerberos or OAuth. There’s more on how to do that in <a href="../sec4/4-3-auth.html">Chapter&nbsp;<span>18</span></a>.</p>
+<p>Increasingly, organizations are using token-based authorization schemes that just exchange one cryptographically secure token for another, never relying on credentials at all. The tradeoff for the enhanced security is that they can be difficult to implement, likely requiring coordination with an IT/Admin to use technologies like Kerberos or OAuth. There’s more on how to do that in <a href="../sec3/3-3-auth.html">Chapter&nbsp;<span>17</span></a>.</p>
 </section>
 </section>
 <section id="data-connection-packages" class="level2" data-number="3.4">
@@ -910,8 +899,8 @@ <h3 data-number="3.6.3" class="anchored" data-anchor-id="step-3-build-a-shiny-ap
 <p>Over the next few chapters, we’re going to implement more architectural best practices for the app, and in <span class="citation" data-cites="env-as-code">[Chapter @env-as-code]</span> we’ll actually go to deployment.</p>
 </section>
 </section>
-<section id="http-code-cheatsheet" class="level2" data-number="3.7">
-<h2 data-number="3.7" class="anchored" data-anchor-id="http-code-cheatsheet"><span class="header-section-number">3.7</span> HTTP Code Cheatsheet</h2>
+<section id="cheat-http" class="level2" data-number="3.7">
+<h2 data-number="3.7" class="anchored" data-anchor-id="cheat-http"><span class="header-section-number">3.7</span> HTTP Code Cheatsheet</h2>
 <p>As you work more with <code>http</code> traffic, you’ll learn some of the common codes. Here’s a cheatsheet for some of the most frequent you’ll see.</p>
 <table class="table">
 <colgroup>
diff --git a/chapters/sec1/1-4-monitor-log.html b/chapters/sec1/1-4-monitor-log.html
index 57473c5f6..458e9ab81 100644
--- a/chapters/sec1/1-4-monitor-log.html
+++ b/chapters/sec1/1-4-monitor-log.html
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  <span class="menu-text"><span class="chapter-number">5</span>&nbsp; <span class="chapter-title">Deployments and code promotion</span></span></a>
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+</li>
+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/sec1/1-6-docker.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">6</span>&nbsp; <span class="chapter-title">Demystifying Docker</span></span></a>
+  </div>
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             <a href="../../chapters/sec2/2-0-sec-intro.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text">IT/Admin Tools</span></a>
+ <span class="menu-text">IT/Admin for Data Science</span></a>
           <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-2" aria-expanded="true" aria-label="Toggle section">
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-  <a href="../../chapters/sec2/2-1-cmd-line.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">6</span>&nbsp; <span class="chapter-title">Opening the Command Line</span></span></a>
+  <a href="../../chapters/sec2/2-1-cloud.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">7</span>&nbsp; <span class="chapter-title">The Cloud</span></span></a>
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-  <a href="../../chapters/sec2/2-2-cmd-line-use.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">7</span>&nbsp; <span class="chapter-title">Using the Command Line</span></span></a>
+  <a href="../../chapters/sec2/2-2-cmd-line.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">8</span>&nbsp; <span class="chapter-title">Customizing the command line</span></span></a>
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-  <a href="../../chapters/sec2/2-3-ssh.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">8</span>&nbsp; <span class="chapter-title">Secure server connections with SSH</span></span></a>
+  <a href="../../chapters/sec2/2-3-linux.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">9</span>&nbsp; <span class="chapter-title">Intro to Linux Administration</span></span></a>
   </div>
 </li>
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-  <a href="../../chapters/sec2/2-4-docker.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">9</span>&nbsp; <span class="chapter-title">Demystifying Docker</span></span></a>
+  <a href="../../chapters/sec2/2-4-app-admin.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Application administration</span></span></a>
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-      </ul>
-  </li>
-        <li class="sidebar-item sidebar-item-section">
-      <div class="sidebar-item-container"> 
-            <a href="../../chapters/sec3/3-0-sec-intro.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text">IT/Admin for Data Science</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-3" aria-expanded="true" aria-label="Toggle section">
-            <i class="bi bi-chevron-right ms-2"></i>
-          </a> 
-      </div>
-      <ul id="quarto-sidebar-section-3" class="collapse list-unstyled sidebar-section depth1 show">  
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-  <a href="../../chapters/sec3/3-1-cloud.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Getting Started with the Cloud</span></span></a>
+  <a href="../../chapters/sec2/2-5-scale.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Server Resources and Scaling</span></span></a>
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   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-2-linux-admin.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Basic Linux SysAdmin</span></span></a>
-  </div>
-</li>
-          <li class="sidebar-item">
-  <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-3-networking.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-6-networking.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">12</span>&nbsp; <span class="chapter-title">Intro to Computer Networks</span></span></a>
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-  <a href="../../chapters/sec3/3-4-dns.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-7-dns.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">13</span>&nbsp; <span class="chapter-title">DNS allows for human-readable addresses</span></span></a>
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 </li>
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   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-5-ssl.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-8-ssl.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">14</span>&nbsp; <span class="chapter-title">You should use SSL/HTTPS</span></span></a>
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-</li>
-          <li class="sidebar-item">
-  <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-6-servers.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Choosing the right server for you</span></span></a>
-  </div>
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   </li>
         <li class="sidebar-item sidebar-item-section">
       <div class="sidebar-item-container"> 
-            <a href="../../chapters/sec4/4-0-sec-intro.html" class="sidebar-item-text sidebar-link">
+            <a href="../../chapters/sec3/3-0-sec-intro.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text">Making it Enterprise-Grade</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true" aria-label="Toggle section">
+          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-3" aria-expanded="true" aria-label="Toggle section">
             <i class="bi bi-chevron-right ms-2"></i>
           </a> 
       </div>
-      <ul id="quarto-sidebar-section-4" class="collapse list-unstyled sidebar-section depth1 show">  
+      <ul id="quarto-sidebar-section-3" class="collapse list-unstyled sidebar-section depth1 show">  
           <li class="sidebar-item">
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-  <a href="../../chapters/sec4/4-1-os-ds-in-ent.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></a>
+  <a href="../../chapters/sec3/3-1-os-ds-in-ent.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></a>
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-  <a href="../../chapters/sec4/4-2-ent-networks.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></a>
+  <a href="../../chapters/sec3/3-2-ent-networks.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
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-  <a href="../../chapters/sec4/4-3-auth.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></a>
+  <a href="../../chapters/sec3/3-3-auth.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></a>
   </div>
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   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec4/4-4-ent-servers.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">19</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></a>
+  <a href="../../chapters/sec3/3-4-ent-servers.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></a>
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-            <a class="sidebar-item-text sidebar-link text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-5" aria-expanded="true">
+            <a class="sidebar-item-text sidebar-link text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true">
  <span class="menu-text">Appendices</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-5" aria-expanded="true" aria-label="Toggle section">
+          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true" aria-label="Toggle section">
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           </a> 
       </div>
-      <ul id="quarto-sidebar-section-5" class="collapse list-unstyled sidebar-section depth1 show">  
+      <ul id="quarto-sidebar-section-4" class="collapse list-unstyled sidebar-section depth1 show">  
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@@ -351,6 +334,12 @@
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  <span class="menu-text"><span class="chapter-number">B</span>&nbsp; <span class="chapter-title">Lab Map</span></span></a>
   </div>
+</li>
+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/append/cheatsheets.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">C</span>&nbsp; <span class="chapter-title">Cheatsheets</span></span></a>
+  </div>
 </li>
       </ul>
   </li>
@@ -493,7 +482,7 @@ <h3 data-number="4.2.2" class="anchored" data-anchor-id="configuring-log-formats
 <p>If you are emitting logs to file, you may also want to consider how long those logs stay around.</p>
 <p><em>Log rotation</em> is the process of periodically creating new log files, storing old logs for a set retention period, and deleting files outside that period. A common log rotation pattern is to have a log file that lasts for 24 hours, is retained for 30 days, and is then deleted.</p>
 <p>The Python <code>{logging}</code> library does log rotation itself. <code>{log4r}</code> does not, but there is a Linux library called <code>logrotate</code> that you can use in concert with <code>{log4r}</code>.<a href="#fn1" class="footnote-ref" id="fnref1" role="doc-noteref"><sup>1</sup></a></p>
-<p>If you’re running in a Docker container you don’t want to write to a file on disk. As you’ll learn more about in <a href="../sec2/2-4-docker.html">Chapter&nbsp;<span>9</span></a>, anything that lives inside a Docker container is ephemeral. This is obviously bad if you’re writing a log that might contain clues for why a Docker container was unexpectedly killed.</p>
+<p>If you’re running in a Docker container you don’t want to write to a file on disk. As you’ll learn more about in <a href="1-6-docker.html">Chapter&nbsp;<span>6</span></a>, anything that lives inside a Docker container is ephemeral. This is obviously bad if you’re writing a log that might contain clues for why a Docker container was unexpectedly killed.</p>
 <p>In that case, it’s common practice for a service running in a container to emit logs inside the container and then have some sort of more permanent service collecting the logs outside. This is usually accomplished by sending normal operating logs to go to <em>stdout</em> (usually pronounced standard out) and failures to go to <em>stderr</em> (standard error).</p>
 <p>It’s also possible you want to do something else completely custom with your logs. This is most common for critical or error logs. For example, you may want to send an email, slack, or text message immediately if your system emits a high-level log message.</p>
 <p>It’s also very common to have different format and location settings in development vs in production. The most common way to enable different logging configurations in different environments is with config files and environment variables. More on how to use these tools in <a href="1-1-env-as-code.html">Chapter&nbsp;<span>1</span></a>.</p>
diff --git a/chapters/sec1/1-5-deployments.html b/chapters/sec1/1-5-deployments.html
index 5f0b4ca45..d33d3fbba 100644
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-<link href="../../chapters/sec2/2-0-sec-intro.html" rel="next">
+<link href="../../chapters/sec1/1-6-docker.html" rel="next">
 <link href="../../chapters/sec1/1-4-monitor-log.html" rel="prev">
 <script src="../../site_libs/quarto-html/quarto.js"></script>
 <script src="../../site_libs/quarto-html/popper.min.js"></script>
@@ -211,13 +211,19 @@
   <a href="../../chapters/sec1/1-5-deployments.html" class="sidebar-item-text sidebar-link active">
  <span class="menu-text"><span class="chapter-number">5</span>&nbsp; <span class="chapter-title">Deployments and code promotion</span></span></a>
   </div>
+</li>
+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/sec1/1-6-docker.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">6</span>&nbsp; <span class="chapter-title">Demystifying Docker</span></span></a>
+  </div>
 </li>
       </ul>
   </li>
         <li class="sidebar-item sidebar-item-section">
       <div class="sidebar-item-container"> 
             <a href="../../chapters/sec2/2-0-sec-intro.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text">IT/Admin Tools</span></a>
+ <span class="menu-text">IT/Admin for Data Science</span></a>
           <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-2" aria-expanded="true" aria-label="Toggle section">
             <i class="bi bi-chevron-right ms-2"></i>
           </a> 
@@ -225,121 +231,98 @@
       <ul id="quarto-sidebar-section-2" class="collapse list-unstyled sidebar-section depth1 show">  
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec2/2-1-cmd-line.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">6</span>&nbsp; <span class="chapter-title">Opening the Command Line</span></span></a>
+  <a href="../../chapters/sec2/2-1-cloud.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">7</span>&nbsp; <span class="chapter-title">The Cloud</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec2/2-2-cmd-line-use.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">7</span>&nbsp; <span class="chapter-title">Using the Command Line</span></span></a>
+  <a href="../../chapters/sec2/2-2-cmd-line.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">8</span>&nbsp; <span class="chapter-title">Customizing the command line</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec2/2-3-ssh.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">8</span>&nbsp; <span class="chapter-title">Secure server connections with SSH</span></span></a>
+  <a href="../../chapters/sec2/2-3-linux.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">9</span>&nbsp; <span class="chapter-title">Intro to Linux Administration</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec2/2-4-docker.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">9</span>&nbsp; <span class="chapter-title">Demystifying Docker</span></span></a>
+  <a href="../../chapters/sec2/2-4-app-admin.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Application administration</span></span></a>
   </div>
 </li>
-      </ul>
-  </li>
-        <li class="sidebar-item sidebar-item-section">
-      <div class="sidebar-item-container"> 
-            <a href="../../chapters/sec3/3-0-sec-intro.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text">IT/Admin for Data Science</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-3" aria-expanded="true" aria-label="Toggle section">
-            <i class="bi bi-chevron-right ms-2"></i>
-          </a> 
-      </div>
-      <ul id="quarto-sidebar-section-3" class="collapse list-unstyled sidebar-section depth1 show">  
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-1-cloud.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Getting Started with the Cloud</span></span></a>
+  <a href="../../chapters/sec2/2-5-scale.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Server Resources and Scaling</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-2-linux-admin.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Basic Linux SysAdmin</span></span></a>
-  </div>
-</li>
-          <li class="sidebar-item">
-  <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-3-networking.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-6-networking.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">12</span>&nbsp; <span class="chapter-title">Intro to Computer Networks</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-4-dns.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-7-dns.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">13</span>&nbsp; <span class="chapter-title">DNS allows for human-readable addresses</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-5-ssl.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-8-ssl.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">14</span>&nbsp; <span class="chapter-title">You should use SSL/HTTPS</span></span></a>
   </div>
-</li>
-          <li class="sidebar-item">
-  <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-6-servers.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Choosing the right server for you</span></span></a>
-  </div>
 </li>
       </ul>
   </li>
         <li class="sidebar-item sidebar-item-section">
       <div class="sidebar-item-container"> 
-            <a href="../../chapters/sec4/4-0-sec-intro.html" class="sidebar-item-text sidebar-link">
+            <a href="../../chapters/sec3/3-0-sec-intro.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text">Making it Enterprise-Grade</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true" aria-label="Toggle section">
+          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-3" aria-expanded="true" aria-label="Toggle section">
             <i class="bi bi-chevron-right ms-2"></i>
           </a> 
       </div>
-      <ul id="quarto-sidebar-section-4" class="collapse list-unstyled sidebar-section depth1 show">  
+      <ul id="quarto-sidebar-section-3" class="collapse list-unstyled sidebar-section depth1 show">  
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec4/4-1-os-ds-in-ent.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></a>
+  <a href="../../chapters/sec3/3-1-os-ds-in-ent.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></a>
   </div>
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   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec4/4-2-ent-networks.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></a>
+  <a href="../../chapters/sec3/3-2-ent-networks.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></a>
   </div>
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-  <a href="../../chapters/sec4/4-3-auth.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></a>
+  <a href="../../chapters/sec3/3-3-auth.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></a>
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-  <a href="../../chapters/sec4/4-4-ent-servers.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">19</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></a>
+  <a href="../../chapters/sec3/3-4-ent-servers.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></a>
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+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/append/cheatsheets.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">C</span>&nbsp; <span class="chapter-title">Cheatsheets</span></span></a>
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-        <span class="nav-page-text">IT/Admin Tools</span> <i class="bi bi-arrow-right-short"></i>
+      <a href="../../chapters/sec1/1-6-docker.html" class="pagination-link">
+        <span class="nav-page-text"><span class="chapter-number">6</span>&nbsp; <span class="chapter-title">Demystifying Docker</span></span> <i class="bi bi-arrow-right-short"></i>
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-<link href="../../chapters/sec2/2-3-ssh.html" rel="prev">
+<link href="../../chapters/sec2/2-0-sec-intro.html" rel="next">
+<link href="../../chapters/sec1/1-5-deployments.html" rel="prev">
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- <span class="menu-text">IT/Admin Tools</span></a>
+ <span class="menu-text">IT/Admin for Data Science</span></a>
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+  <a href="../../chapters/sec2/2-1-cloud.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">7</span>&nbsp; <span class="chapter-title">The Cloud</span></span></a>
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- <span class="menu-text"><span class="chapter-number">7</span>&nbsp; <span class="chapter-title">Using the Command Line</span></span></a>
+  <a href="../../chapters/sec2/2-2-cmd-line.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">8</span>&nbsp; <span class="chapter-title">Customizing the command line</span></span></a>
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- <span class="menu-text"><span class="chapter-number">8</span>&nbsp; <span class="chapter-title">Secure server connections with SSH</span></span></a>
+  <a href="../../chapters/sec2/2-3-linux.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">9</span>&nbsp; <span class="chapter-title">Intro to Linux Administration</span></span></a>
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-  <a href="../../chapters/sec2/2-4-docker.html" class="sidebar-item-text sidebar-link active">
- <span class="menu-text"><span class="chapter-number">9</span>&nbsp; <span class="chapter-title">Demystifying Docker</span></span></a>
+  <a href="../../chapters/sec2/2-4-app-admin.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Application administration</span></span></a>
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- <span class="menu-text">IT/Admin for Data Science</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-3" aria-expanded="true" aria-label="Toggle section">
-            <i class="bi bi-chevron-right ms-2"></i>
-          </a> 
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-  <a href="../../chapters/sec3/3-1-cloud.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Getting Started with the Cloud</span></span></a>
+  <a href="../../chapters/sec2/2-5-scale.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Server Resources and Scaling</span></span></a>
   </div>
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-  <a href="../../chapters/sec3/3-2-linux-admin.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Basic Linux SysAdmin</span></span></a>
-  </div>
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-          <li class="sidebar-item">
-  <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-3-networking.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-6-networking.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">12</span>&nbsp; <span class="chapter-title">Intro to Computer Networks</span></span></a>
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   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-4-dns.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-7-dns.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">13</span>&nbsp; <span class="chapter-title">DNS allows for human-readable addresses</span></span></a>
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-  <a href="../../chapters/sec3/3-5-ssl.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-8-ssl.html" class="sidebar-item-text sidebar-link">
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- <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Choosing the right server for you</span></span></a>
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+            <a href="../../chapters/sec3/3-0-sec-intro.html" class="sidebar-item-text sidebar-link">
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-  <a href="../../chapters/sec4/4-1-os-ds-in-ent.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></a>
+  <a href="../../chapters/sec3/3-1-os-ds-in-ent.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></a>
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-  <a href="../../chapters/sec4/4-2-ent-networks.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></a>
+  <a href="../../chapters/sec3/3-2-ent-networks.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></a>
   </div>
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   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec4/4-3-auth.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></a>
+  <a href="../../chapters/sec3/3-3-auth.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></a>
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-  <a href="../../chapters/sec4/4-4-ent-servers.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">19</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></a>
+  <a href="../../chapters/sec3/3-4-ent-servers.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></a>
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       <div class="sidebar-item-container"> 
-            <a class="sidebar-item-text sidebar-link text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-5" aria-expanded="true">
+            <a class="sidebar-item-text sidebar-link text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true">
  <span class="menu-text">Appendices</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-5" aria-expanded="true" aria-label="Toggle section">
+          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true" aria-label="Toggle section">
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           </a> 
       </div>
-      <ul id="quarto-sidebar-section-5" class="collapse list-unstyled sidebar-section depth1 show">  
+      <ul id="quarto-sidebar-section-4" class="collapse list-unstyled sidebar-section depth1 show">  
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   <div class="sidebar-item-container"> 
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@@ -351,6 +334,12 @@
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  <span class="menu-text"><span class="chapter-number">B</span>&nbsp; <span class="chapter-title">Lab Map</span></span></a>
   </div>
+</li>
+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/append/cheatsheets.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">C</span>&nbsp; <span class="chapter-title">Cheatsheets</span></span></a>
+  </div>
 </li>
       </ul>
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@@ -364,36 +353,30 @@
     <h2 id="toc-title">Table of contents</h2>
    
   <ul>
-  <li><a href="#container-lifecycle" id="toc-container-lifecycle" class="nav-link active" data-scroll-target="#container-lifecycle"><span class="header-section-number">9.1</span> Container lifecycle</a>
-  <ul class="collapse">
-  <li><a href="#image-names" id="toc-image-names" class="nav-link" data-scroll-target="#image-names"><span class="header-section-number">9.1.1</span> Image Names</a></li>
-  </ul></li>
-  <li><a href="#running-containers" id="toc-running-containers" class="nav-link" data-scroll-target="#running-containers"><span class="header-section-number">9.2</span> Running Containers</a>
+  <li><a href="#container-lifecycle" id="toc-container-lifecycle" class="nav-link active" data-scroll-target="#container-lifecycle"><span class="header-section-number">6.1</span> Container lifecycle</a>
   <ul class="collapse">
-  <li><a href="#getting-information-in-and-out" id="toc-getting-information-in-and-out" class="nav-link" data-scroll-target="#getting-information-in-and-out"><span class="header-section-number">9.2.1</span> Getting information in and out</a></li>
-  <li><a href="#other-runtime-commands" id="toc-other-runtime-commands" class="nav-link" data-scroll-target="#other-runtime-commands"><span class="header-section-number">9.2.2</span> Other runtime commands</a></li>
+  <li><a href="#image-names" id="toc-image-names" class="nav-link" data-scroll-target="#image-names"><span class="header-section-number">6.1.1</span> Image Names</a></li>
   </ul></li>
-  <li><a href="#building-images-from-dockerfiles" id="toc-building-images-from-dockerfiles" class="nav-link" data-scroll-target="#building-images-from-dockerfiles"><span class="header-section-number">9.3</span> Building Images from Dockerfiles</a></li>
-  <li><a href="#comprehension-questions" id="toc-comprehension-questions" class="nav-link" data-scroll-target="#comprehension-questions"><span class="header-section-number">9.4</span> Comprehension Questions</a></li>
-  <li><a href="#lab-putting-an-api-in-a-container" id="toc-lab-putting-an-api-in-a-container" class="nav-link" data-scroll-target="#lab-putting-an-api-in-a-container"><span class="header-section-number">9.5</span> Lab: Putting an API in a Container</a>
+  <li><a href="#running-containers" id="toc-running-containers" class="nav-link" data-scroll-target="#running-containers"><span class="header-section-number">6.2</span> Running Containers</a>
   <ul class="collapse">
-  <li><a href="#lab-extension" id="toc-lab-extension" class="nav-link" data-scroll-target="#lab-extension"><span class="header-section-number">9.5.1</span> Lab Extension</a></li>
+  <li><a href="#getting-information-in-and-out" id="toc-getting-information-in-and-out" class="nav-link" data-scroll-target="#getting-information-in-and-out"><span class="header-section-number">6.2.1</span> Getting information in and out</a></li>
+  <li><a href="#other-runtime-commands" id="toc-other-runtime-commands" class="nav-link" data-scroll-target="#other-runtime-commands"><span class="header-section-number">6.2.2</span> Other runtime commands</a></li>
   </ul></li>
-  <li><a href="#cheat-docker" id="toc-cheat-docker" class="nav-link" data-scroll-target="#cheat-docker"><span class="header-section-number">9.6</span> Cheatsheet: Docker</a>
+  <li><a href="#building-images-from-dockerfiles" id="toc-building-images-from-dockerfiles" class="nav-link" data-scroll-target="#building-images-from-dockerfiles"><span class="header-section-number">6.3</span> Building Images from Dockerfiles</a></li>
+  <li><a href="#comprehension-questions" id="toc-comprehension-questions" class="nav-link" data-scroll-target="#comprehension-questions"><span class="header-section-number">6.4</span> Comprehension Questions</a></li>
+  <li><a href="#lab-putting-an-api-in-a-container" id="toc-lab-putting-an-api-in-a-container" class="nav-link" data-scroll-target="#lab-putting-an-api-in-a-container"><span class="header-section-number">6.5</span> Lab: Putting an API in a Container</a>
   <ul class="collapse">
-  <li><a href="#docker-cli-commands" id="toc-docker-cli-commands" class="nav-link" data-scroll-target="#docker-cli-commands"><span class="header-section-number">9.6.1</span> Docker CLI Commands</a></li>
-  <li><a href="#flags-for-docker-run" id="toc-flags-for-docker-run" class="nav-link" data-scroll-target="#flags-for-docker-run"><span class="header-section-number">9.6.2</span> <strong>Flags for <code>docker run</code></strong></a></li>
-  <li><a href="#dockerfile-commands" id="toc-dockerfile-commands" class="nav-link" data-scroll-target="#dockerfile-commands"><span class="header-section-number">9.6.3</span> Dockerfile Commands</a></li>
+  <li><a href="#lab-extension" id="toc-lab-extension" class="nav-link" data-scroll-target="#lab-extension"><span class="header-section-number">6.5.1</span> Lab Extension</a></li>
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   </ul>
-<div class="toc-actions"><div><i class="bi bi-github"></i></div><div class="action-links"><p><a href="https://github.com/akgold/do4ds/edit/main/chapters/sec2/2-4-docker.qmd" class="toc-action">Edit this page</a></p></div></div></nav>
+<div class="toc-actions"><div><i class="bi bi-github"></i></div><div class="action-links"><p><a href="https://github.com/akgold/do4ds/edit/main/chapters/sec1/1-6-docker.qmd" class="toc-action">Edit this page</a></p></div></div></nav>
     </div>
 <!-- main -->
 <main class="content" id="quarto-document-content">
 
 <header id="title-block-header" class="quarto-title-block default">
 <div class="quarto-title">
-<h1 class="title"><span id="sec-docker" class="quarto-section-identifier"><span class="chapter-number">9</span>&nbsp; <span class="chapter-title">Demystifying Docker</span></span></h1>
+<h1 class="title"><span id="sec-docker" class="quarto-section-identifier"><span class="chapter-number">6</span>&nbsp; <span class="chapter-title">Demystifying Docker</span></span></h1>
 </div>
 
 
@@ -425,12 +408,12 @@ <h1 class="title"><span id="sec-docker" class="quarto-section-identifier"><span
 </div>
 </div>
 <div class="callout-body-container callout-body">
-<p>This chapter is solely on the local use of Docker for building and running containers. For more on running containers in a production context, including using Kubernetes, see <a href="../sec4/4-4-ent-servers.html">Chapter&nbsp;<span>19</span></a>.</p>
+<p>This chapter is solely on the local use of Docker for building and running containers. For more on running containers in a production context, including using Kubernetes, see <a href="../sec3/3-4-ent-servers.html">Chapter&nbsp;<span>18</span></a>.</p>
 </div>
 </div>
 <p>Really learning to use Docker is the subject of many books and online tutorials. In this chapter, I’m just aiming to give you a little familiarity with basic terminology and concepts for how to run other people’s Docker containers and how to create your own. In the lab at the end of the chapter, we’ll practice hosting an API inside a container.</p>
-<section id="container-lifecycle" class="level2" data-number="9.1">
-<h2 data-number="9.1" class="anchored" data-anchor-id="container-lifecycle"><span class="header-section-number">9.1</span> Container lifecycle</h2>
+<section id="container-lifecycle" class="level2" data-number="6.1">
+<h2 data-number="6.1" class="anchored" data-anchor-id="container-lifecycle"><span class="header-section-number">6.1</span> Container lifecycle</h2>
 <p>Docker is primarily concerned with the creation, movement, and running of <em>containers</em>. A container is a software entity that packages code and its dependencies down to the operating system. Containers make it possible to have completely different environments coexisting side by side on one physical machine.</p>
 <div class="callout callout-style-default callout-note callout-titled">
 <div class="callout-header d-flex align-content-center">
@@ -466,9 +449,9 @@ <h2 data-number="9.1" class="anchored" data-anchor-id="container-lifecycle"><spa
 <p>I’ve included <code>docker pull</code> on the graphic for completeness, but you’ll almost never run it. <code>docker run</code> auto-pulls the container(s) it needs.</p>
 </div>
 </div>
-<p>There’s a <a href="#cheat-docker">cheatsheet</a> for Docker CLI commands at the end of this chapter.</p>
-<section id="image-names" class="level3" data-number="9.1.1">
-<h3 data-number="9.1.1" class="anchored" data-anchor-id="image-names"><span class="header-section-number">9.1.1</span> Image Names</h3>
+<p>There’s a <a href="../append/cheatsheets.html#cheat-docker">cheatsheet</a> for Docker CLI commands at the end of this chapter.</p>
+<section id="image-names" class="level3" data-number="6.1.1">
+<h3 data-number="6.1.1" class="anchored" data-anchor-id="image-names"><span class="header-section-number">6.1.1</span> Image Names</h3>
 <p>In order to build, push, pull, or run an image, you’ll need to know which image you’re talking about. Every image has a name that consists of an <em>id</em> and a <em>tag</em>.</p>
 <div class="callout callout-style-default callout-note callout-titled">
 <div class="callout-header d-flex align-content-center">
@@ -489,15 +472,15 @@ <h3 data-number="9.1.1" class="anchored" data-anchor-id="image-names"><span clas
 <p>Other tags are relative to the point in time. If you don’t see a tag on a container name, it’s using the default <code>latest</code>. Other common relative tags refer to the current development state of the software inside like <code>devel</code>, <code>release</code>, or <code>stable</code>.</p>
 </section>
 </section>
-<section id="running-containers" class="level2" data-number="9.2">
-<h2 data-number="9.2" class="anchored" data-anchor-id="running-containers"><span class="header-section-number">9.2</span> Running Containers</h2>
+<section id="running-containers" class="level2" data-number="6.2">
+<h2 data-number="6.2" class="anchored" data-anchor-id="running-containers"><span class="header-section-number">6.2</span> Running Containers</h2>
 <p>The <code>docker run</code> command runs container images as an instance. You can run <code>docker run &lt;image name&gt;</code> to get a running container. However, most things you want to do with your instance require several command line flags.</p>
 <p>There are a few flags that are useful to manage how your containers run and get cleaned up.</p>
 <p>The <code>-name &lt;name&gt;</code> flag names an instance. It’s not required, but can be useful to give the instance a name you can remember or use in code. If you don’t provide a name, each instance gets a random alphanumeric id on start.</p>
 <p>The <code>-rm</code> flag automatically removes the container after its done. If you don’t use the <code>-rm</code> flag, the container will stick around until you clean it up manually with <code>docker rm</code>. The <code>-rm</code> flag can be useful when you’re iterating quickly – especially because you can’t re-use names until you remove the container.</p>
 <p>The <code>-d</code> flag will run your container in detached mode. This is useful when you want your container to run in the background and not block your terminal session. It’s useful when running containers in production, but you probably don’t want to use it when you’re trying things out and want to see logs streaming out as the container runs.</p>
-<section id="getting-information-in-and-out" class="level3" data-number="9.2.1">
-<h3 data-number="9.2.1" class="anchored" data-anchor-id="getting-information-in-and-out"><span class="header-section-number">9.2.1</span> Getting information in and out</h3>
+<section id="getting-information-in-and-out" class="level3" data-number="6.2.1">
+<h3 data-number="6.2.1" class="anchored" data-anchor-id="getting-information-in-and-out"><span class="header-section-number">6.2.1</span> Getting information in and out</h3>
 <p>When a container runs, it is isolated from the host. This is a great feature – it means programs running inside the container can address the container’s filesystem and networking without worrying about the host outside. But it also means that using resources on the host requires explicit declarations as part of the <code>docker run</code> command.</p>
 <p>In order to get data in or out of a container, you need to mount a shared <em>volume</em> (directory) between the container and host with the <code>-v</code> flag. You specify a host directory and a container directory separated by <code>:</code>. Anything in the volume will be available to both the host and the container at the file paths specified.</p>
 <p>For example, maybe you’ve got a container that runs a job against data it expects in the <code>/data</code> directory. On your host machine, this data lives at <code>/home/alex/data</code>. You could make this happen with</p>
@@ -506,8 +489,8 @@ <h3 data-number="9.2.1" class="anchored" data-anchor-id="getting-information-in-
 <p><img src="images/docker-on-host.png" class="img-fluid" alt="A diagram showing how the flag -v /home/data:/data mounts the /home/data directory of the host to /data in the container." width="450"></p>
 <p>Similarly, if you have a service running in a container on a particular port, you’ll need to map the container port to a host port with the <code>-p</code> flag.</p>
 </section>
-<section id="other-runtime-commands" class="level3" data-number="9.2.2">
-<h3 data-number="9.2.2" class="anchored" data-anchor-id="other-runtime-commands"><span class="header-section-number">9.2.2</span> Other runtime commands</h3>
+<section id="other-runtime-commands" class="level3" data-number="6.2.2">
+<h3 data-number="6.2.2" class="anchored" data-anchor-id="other-runtime-commands"><span class="header-section-number">6.2.2</span> Other runtime commands</h3>
 <p>If you want to see what containers you’ve got, <code>docker ps</code> lists them. This is especially useful to get instance ids if you didn’t bother with names.</p>
 <p>To stop a running container <code>docker stop</code> does so nicely and <code>docker kill</code> terminates a container immediately.</p>
 <p>You can view the logs from a container with <code>docker logs</code>.</p>
@@ -515,8 +498,8 @@ <h3 data-number="9.2.2" class="anchored" data-anchor-id="other-runtime-commands"
 <p>While it’s normal to SSH into a server to poke around, it’s somewhat of an anti-pattern to do the same in a container. In general you should prefer to review logs and adjust Dockerfiles and <code>run</code> commands rather than <code>exec</code> in.</p>
 </section>
 </section>
-<section id="building-images-from-dockerfiles" class="level2" data-number="9.3">
-<h2 data-number="9.3" class="anchored" data-anchor-id="building-images-from-dockerfiles"><span class="header-section-number">9.3</span> Building Images from Dockerfiles</h2>
+<section id="building-images-from-dockerfiles" class="level2" data-number="6.3">
+<h2 data-number="6.3" class="anchored" data-anchor-id="building-images-from-dockerfiles"><span class="header-section-number">6.3</span> Building Images from Dockerfiles</h2>
 <p>A Dockerfile is a set of instructions that you use to build a Docker Image. If you know how to accomplish something from the command line, you shouldn’t have too much trouble building a Dockerfile to do the same.</p>
 <p>One thing to consider when creating Dockerfiles is that the resulting image is immutable. That means anything you build into the image is forever frozen in time. So you’ll definitely want to set up the versions of R and Python and install system requirements. Depending on the purpose of your container, you may want to copy in code, data, and/or R and Python packages, or you may want to mount those in a volume at runtime.</p>
 <p>There are many Dockerfile commands. You can review them all in the <a href="https://docs.docker.com/engine/reference/builder/">Dockerfile documentation</a>, but here are the handful that are enough to build most images.</p>
@@ -537,8 +520,8 @@ <h2 data-number="9.3" class="anchored" data-anchor-id="building-images-from-dock
 <p>Once you’ve created your Dockerfile, you build it into an image using <code>docker build -t &lt;image name&gt; &lt;build directory&gt;</code>. If you don’t provide a tag, the default tag is <code>latest</code>.</p>
 <p>You can then push the image to DockerHub or another registry using <code>docker push &lt;image name&gt;</code>.</p>
 </section>
-<section id="comprehension-questions" class="level2" data-number="9.4">
-<h2 data-number="9.4" class="anchored" data-anchor-id="comprehension-questions"><span class="header-section-number">9.4</span> Comprehension Questions</h2>
+<section id="comprehension-questions" class="level2" data-number="6.4">
+<h2 data-number="6.4" class="anchored" data-anchor-id="comprehension-questions"><span class="header-section-number">6.4</span> Comprehension Questions</h2>
 <ol type="1">
 <li>Draw a mental map of the relationship between the following: Dockerfile, Docker Image, Docker Registry, Docker Container</li>
 <li>When would you want to use each of the following flags for <code>docker run</code>? When wouldn’t you?
@@ -548,9 +531,9 @@ <h2 data-number="9.4" class="anchored" data-anchor-id="comprehension-questions">
 <li>What are the most important Dockerfile commands?</li>
 </ol>
 </section>
-<section id="lab-putting-an-api-in-a-container" class="level2" data-number="9.5">
-<h2 data-number="9.5" class="anchored" data-anchor-id="lab-putting-an-api-in-a-container"><span class="header-section-number">9.5</span> Lab: Putting an API in a Container</h2>
-<p>Putting an API into a container is popular way to host them. In this lab, we’re going to put the Penguin Model Prediction API from <a href="../sec1/1-2-proj-arch.html">Chapter&nbsp;<span>2</span></a> into a container.</p>
+<section id="lab-putting-an-api-in-a-container" class="level2" data-number="6.5">
+<h2 data-number="6.5" class="anchored" data-anchor-id="lab-putting-an-api-in-a-container"><span class="header-section-number">6.5</span> Lab: Putting an API in a Container</h2>
+<p>Putting an API into a container is popular way to host them. In this lab, we’re going to put the Penguin Model Prediction API from <a href="1-2-proj-arch.html">Chapter&nbsp;<span>2</span></a> into a container.</p>
 <p>If you’ve never used Docker before, start by installing <a href="https://www.docker.com/products/docker-desktop">Docker Desktop</a> on your computer.</p>
 <p>You should feel free to write your own Dockerfile to put the API in a container. If you want to make it easy, the <code>{vetiver}</code> package, which you’ll remember auto-generated the API for us, can also auto-generate a Dockerfile. Look at the package documentation for details.</p>
 <p>I’m using this code to generate my Dockerfile</p>
@@ -597,7 +580,7 @@ <h2 data-number="9.5" class="anchored" data-anchor-id="lab-putting-an-api-in-a-c
 </div>
 </div>
 <div class="callout-body-container callout-body">
-<p>This container follows the best practices from <a href="../sec1/1-2-proj-arch.html">Chapter&nbsp;<span>2</span></a>. We’d expect the model to be updated much more frequently than the container itself, so the model <strong>isn’t</strong> built into the container. Instead, the container knows how to fetch the model using the <code>{pins}</code> package.</p>
+<p>This container follows the best practices from <a href="1-2-proj-arch.html">Chapter&nbsp;<span>2</span></a>. We’d expect the model to be updated much more frequently than the container itself, so the model <strong>isn’t</strong> built into the container. Instead, the container knows how to fetch the model using the <code>{pins}</code> package.</p>
 </div>
 </div>
 <p>Now build the container using <code>docker build -t penguin-model .</code>.</p>
@@ -632,167 +615,10 @@ <h2 data-number="9.5" class="anchored" data-anchor-id="lab-putting-an-api-in-a-c
 <span id="cb6-4"><a href="#cb6-4"></a>  <span class="at">-v</span> /data/model:/data/model <span class="dt">\</span></span>
 <span id="cb6-5"><a href="#cb6-5"></a>  penguin-model-local</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <p>And NOW you should be able to get your model up in no time.</p>
-<section id="lab-extension" class="level3" data-number="9.5.1">
-<h3 data-number="9.5.1" class="anchored" data-anchor-id="lab-extension"><span class="header-section-number">9.5.1</span> Lab Extension</h3>
+<section id="lab-extension" class="level3" data-number="6.5.1">
+<h3 data-number="6.5.1" class="anchored" data-anchor-id="lab-extension"><span class="header-section-number">6.5.1</span> Lab Extension</h3>
 <p>Right now, logs from the API just stay inside the container instance. But that means that the logs go away when the container does. That’s obviously bad if the container dies because something goes wrong.</p>
 <p>How might you make sure that the container’s logs get written somewhere more permanent?</p>
-</section>
-</section>
-<section id="cheat-docker" class="level2" data-number="9.6">
-<h2 data-number="9.6" class="anchored" data-anchor-id="cheat-docker"><span class="header-section-number">9.6</span> Cheatsheet: Docker</h2>
-<section id="docker-cli-commands" class="level3" data-number="9.6.1">
-<h3 data-number="9.6.1" class="anchored" data-anchor-id="docker-cli-commands"><span class="header-section-number">9.6.1</span> Docker CLI Commands</h3>
-<table class="table">
-<colgroup>
-<col style="width: 22%">
-<col style="width: 22%">
-<col style="width: 22%">
-<col style="width: 31%">
-</colgroup>
-<thead>
-<tr class="header">
-<th>Stage</th>
-<th>Command</th>
-<th>What it does</th>
-<th>Notes and helpful options</th>
-</tr>
-</thead>
-<tbody>
-<tr class="odd">
-<td>Build</td>
-<td><code>docker build &lt;directory&gt;</code></td>
-<td>Builds a directory containing a Dockerfile into an image.</td>
-<td><code>-t &lt;name:tag&gt;</code> provide a name to the container. <code>tag</code> is optional, defaults to <code>latest</code>.</td>
-</tr>
-<tr class="even">
-<td>Move</td>
-<td><code>docker push &lt;image&gt;</code></td>
-<td>Push a container to a registry.</td>
-<td></td>
-</tr>
-<tr class="odd">
-<td>Move</td>
-<td><code>docker pull &lt;image&gt;</code></td>
-<td>Pull a container from a registry.</td>
-<td>Rarely used because <code>run</code> pulls the container if needed.</td>
-</tr>
-<tr class="even">
-<td>Run</td>
-<td><code>docker run &lt;image&gt;</code></td>
-<td>Run a container.</td>
-<td>See flags in next table.</td>
-</tr>
-<tr class="odd">
-<td>Run</td>
-<td><code>docker stop &lt;container&gt;</code></td>
-<td>Stop a running container.</td>
-<td><code>docker kill</code> can be used if <code>stop</code> fails.</td>
-</tr>
-<tr class="even">
-<td>Run</td>
-<td><code>docker ps</code></td>
-<td>List containers.</td>
-<td>Useful to get running container id to do things to it.</td>
-</tr>
-<tr class="odd">
-<td>Run</td>
-<td><code>docker exec &lt;container&gt; &lt;command&gt;</code></td>
-<td>Run a command inside a running container.</td>
-<td>Basically always used to open a shell in a container with <code>docker exec -it &lt;container&gt; /bin/bash</code></td>
-</tr>
-<tr class="even">
-<td>Run</td>
-<td><code>docker logs &lt;container&gt;</code></td>
-<td>Views logs for a container.</td>
-<td></td>
-</tr>
-</tbody>
-</table>
-</section>
-<section id="flags-for-docker-run" class="level3" data-number="9.6.2">
-<h3 data-number="9.6.2" class="anchored" data-anchor-id="flags-for-docker-run"><span class="header-section-number">9.6.2</span> <strong>Flags for <code>docker run</code></strong></h3>
-<table class="table">
-<caption><em>Reminder: Order for <code>-p</code> and <code>-v</code> is <code>&lt;host&gt;:&lt;container&gt;</code></em></caption>
-<colgroup>
-<col style="width: 26%">
-<col style="width: 36%">
-<col style="width: 37%">
-</colgroup>
-<thead>
-<tr class="header">
-<th>Flag</th>
-<th>Effect</th>
-<th>Notes</th>
-</tr>
-</thead>
-<tbody>
-<tr class="odd">
-<td><code>--name &lt;name&gt;</code></td>
-<td>Give a name to the running container.</td>
-<td>Optional. Will be auto-assigned if not provided.</td>
-</tr>
-<tr class="even">
-<td><code>--rm</code></td>
-<td>Remove container when its stopped.</td>
-<td>Don’t use in production. You probably want to inspect failed containers.</td>
-</tr>
-<tr class="odd">
-<td><code>-d</code></td>
-<td>Detach container (don’t block the terminal).</td>
-<td>Almost always used in production.</td>
-</tr>
-<tr class="even">
-<td><code>-p &lt;port&gt;:&lt;port&gt;</code></td>
-<td>Publish port from inside container to outside.</td>
-<td>Needed if you want to access an app or API running inside the container.</td>
-</tr>
-<tr class="odd">
-<td><code>-v &lt;dir&gt;:&lt;dir&gt;</code></td>
-<td>Mount volume into the container.</td>
-<td></td>
-</tr>
-</tbody>
-</table>
-</section>
-<section id="dockerfile-commands" class="level3" data-number="9.6.3">
-<h3 data-number="9.6.3" class="anchored" data-anchor-id="dockerfile-commands"><span class="header-section-number">9.6.3</span> Dockerfile Commands</h3>
-<p>These are the commands that go in a Dockerfile when you’re building it.</p>
-<table class="table">
-<colgroup>
-<col style="width: 26%">
-<col style="width: 42%">
-<col style="width: 31%">
-</colgroup>
-<thead>
-<tr class="header">
-<th>Command</th>
-<th>Purpose</th>
-<th>Example</th>
-</tr>
-</thead>
-<tbody>
-<tr class="odd">
-<td><code>FROM</code></td>
-<td>Indicate base container.</td>
-<td><code>FROM rocker/r-ver:4.1.0</code></td>
-</tr>
-<tr class="even">
-<td><code>RUN</code></td>
-<td>Run a command when building.</td>
-<td><code>RUN apt-get update</code></td>
-</tr>
-<tr class="odd">
-<td><code>COPY</code></td>
-<td>Copy from build directory into the container.</td>
-<td><code>COPY . /app/</code></td>
-</tr>
-<tr class="even">
-<td><code>CMD</code></td>
-<td>Specify the command to run when the container starts.</td>
-<td><code>CMD quarto render .</code></td>
-</tr>
-</tbody>
-</table>
 
 
 </section>
@@ -1042,12 +868,12 @@ <h3 data-number="9.6.3" class="anchored" data-anchor-id="dockerfile-commands"><s
 </script>
 <nav class="page-navigation">
   <div class="nav-page nav-page-previous">
-      <a href="../../chapters/sec2/2-3-ssh.html" class="pagination-link">
-        <i class="bi bi-arrow-left-short"></i> <span class="nav-page-text"><span class="chapter-number">8</span>&nbsp; <span class="chapter-title">Secure server connections with SSH</span></span>
+      <a href="../../chapters/sec1/1-5-deployments.html" class="pagination-link">
+        <i class="bi bi-arrow-left-short"></i> <span class="nav-page-text"><span class="chapter-number">5</span>&nbsp; <span class="chapter-title">Deployments and code promotion</span></span>
       </a>          
   </div>
   <div class="nav-page nav-page-next">
-      <a href="../../chapters/sec3/3-0-sec-intro.html" class="pagination-link">
+      <a href="../../chapters/sec2/2-0-sec-intro.html" class="pagination-link">
         <span class="nav-page-text">IT/Admin for Data Science</span> <i class="bi bi-arrow-right-short"></i>
       </a>
   </div>
diff --git a/chapters/sec2/images/docker-lifecycle.png b/chapters/sec1/images/docker-lifecycle.png
similarity index 100%
rename from chapters/sec2/images/docker-lifecycle.png
rename to chapters/sec1/images/docker-lifecycle.png
diff --git a/chapters/sec2/images/docker-on-host.png b/chapters/sec1/images/docker-on-host.png
similarity index 100%
rename from chapters/sec2/images/docker-on-host.png
rename to chapters/sec1/images/docker-on-host.png
diff --git a/chapters/sec1/images/repro-spectrum.png b/chapters/sec1/images/repro-spectrum.png
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+      <nav class="quarto-page-breadcrumbs" aria-label="breadcrumb"><ol class="breadcrumb"><li class="breadcrumb-item"><a href="../../chapters/sec2/2-0-sec-intro.html">IT/Admin for Data Science</a></li></ol></nav>
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  <span class="menu-text"><span class="chapter-number">5</span>&nbsp; <span class="chapter-title">Deployments and code promotion</span></span></a>
   </div>
+</li>
+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/sec1/1-6-docker.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">6</span>&nbsp; <span class="chapter-title">Demystifying Docker</span></span></a>
+  </div>
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- <span class="menu-text">IT/Admin Tools</span></a>
+ <span class="menu-text">IT/Admin for Data Science</span></a>
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-  <a href="../../chapters/sec2/2-1-cmd-line.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">6</span>&nbsp; <span class="chapter-title">Opening the Command Line</span></span></a>
+  <a href="../../chapters/sec2/2-1-cloud.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">7</span>&nbsp; <span class="chapter-title">The Cloud</span></span></a>
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-  <a href="../../chapters/sec2/2-2-cmd-line-use.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">7</span>&nbsp; <span class="chapter-title">Using the Command Line</span></span></a>
+  <a href="../../chapters/sec2/2-2-cmd-line.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">8</span>&nbsp; <span class="chapter-title">Customizing the command line</span></span></a>
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-  <a href="../../chapters/sec2/2-3-ssh.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">8</span>&nbsp; <span class="chapter-title">Secure server connections with SSH</span></span></a>
+  <a href="../../chapters/sec2/2-3-linux.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">9</span>&nbsp; <span class="chapter-title">Intro to Linux Administration</span></span></a>
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-  <a href="../../chapters/sec2/2-4-docker.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">9</span>&nbsp; <span class="chapter-title">Demystifying Docker</span></span></a>
+  <a href="../../chapters/sec2/2-4-app-admin.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Application administration</span></span></a>
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- <span class="menu-text">IT/Admin for Data Science</span></a>
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- <span class="menu-text"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Getting Started with the Cloud</span></span></a>
+  <a href="../../chapters/sec2/2-5-scale.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Server Resources and Scaling</span></span></a>
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-  <a href="../../chapters/sec3/3-2-linux-admin.html" class="sidebar-item-text sidebar-link">
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-  </div>
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-          <li class="sidebar-item">
-  <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-3-networking.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-6-networking.html" class="sidebar-item-text sidebar-link">
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-  <a href="../../chapters/sec3/3-4-dns.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-7-dns.html" class="sidebar-item-text sidebar-link">
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-  <a href="../../chapters/sec3/3-5-ssl.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-8-ssl.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">14</span>&nbsp; <span class="chapter-title">You should use SSL/HTTPS</span></span></a>
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-  <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-6-servers.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Choosing the right server for you</span></span></a>
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+            <a href="../../chapters/sec3/3-0-sec-intro.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text">Making it Enterprise-Grade</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true" aria-label="Toggle section">
+          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-3" aria-expanded="true" aria-label="Toggle section">
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+      <ul id="quarto-sidebar-section-3" class="collapse list-unstyled sidebar-section depth1 show">  
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-  <a href="../../chapters/sec4/4-1-os-ds-in-ent.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></a>
+  <a href="../../chapters/sec3/3-1-os-ds-in-ent.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></a>
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-  <a href="../../chapters/sec4/4-2-ent-networks.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></a>
+  <a href="../../chapters/sec3/3-2-ent-networks.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></a>
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-  <a href="../../chapters/sec4/4-3-auth.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></a>
+  <a href="../../chapters/sec3/3-3-auth.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></a>
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- <span class="menu-text"><span class="chapter-number">19</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></a>
+  <a href="../../chapters/sec3/3-4-ent-servers.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></a>
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-            <a class="sidebar-item-text sidebar-link text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-5" aria-expanded="true">
+            <a class="sidebar-item-text sidebar-link text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true">
  <span class="menu-text">Appendices</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-5" aria-expanded="true" aria-label="Toggle section">
+          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true" aria-label="Toggle section">
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+      <ul id="quarto-sidebar-section-4" class="collapse list-unstyled sidebar-section depth1 show">  
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  <span class="menu-text"><span class="chapter-number">B</span>&nbsp; <span class="chapter-title">Lab Map</span></span></a>
   </div>
+</li>
+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/append/cheatsheets.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">C</span>&nbsp; <span class="chapter-title">Cheatsheets</span></span></a>
+  </div>
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     <h2 id="toc-title">Table of contents</h2>
    
   <ul>
-  <li><a href="#labs-in-this-section" id="toc-labs-in-this-section" class="nav-link active" data-scroll-target="#labs-in-this-section">Labs in this Section</a></li>
+  <li><a href="#getting-and-running-a-server" id="toc-getting-and-running-a-server" class="nav-link active" data-scroll-target="#getting-and-running-a-server">Getting and running a server</a></li>
+  <li><a href="#making-it-safely-accessible" id="toc-making-it-safely-accessible" class="nav-link" data-scroll-target="#making-it-safely-accessible">Making it (safely) accessible</a></li>
+  <li><a href="#labs-in-this-section" id="toc-labs-in-this-section" class="nav-link" data-scroll-target="#labs-in-this-section">Labs in this Section</a></li>
   </ul>
 <div class="toc-actions"><div><i class="bi bi-github"></i></div><div class="action-links"><p><a href="https://github.com/akgold/do4ds/edit/main/chapters/sec2/2-0-sec-intro.qmd" class="toc-action">Edit this page</a></p></div></div></nav>
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@@ -339,7 +330,7 @@ <h2 id="toc-title">Table of contents</h2>
 
 <header id="title-block-header" class="quarto-title-block default">
 <div class="quarto-title">
-<h1 class="title"><span id="sec-2-intro" class="quarto-section-identifier">IT/Admin Tools</span></h1>
+<h1 class="title"><span id="sec-2-intro" class="quarto-section-identifier">IT/Admin for Data Science</span></h1>
 </div>
 
 
@@ -354,14 +345,40 @@ <h1 class="title"><span id="sec-2-intro" class="quarto-section-identifier">IT/Ad
 
 </header>
 
-<p><a href="@sec-1-intro">Section 1</a> was all about how to apply DevOps principles and best practices to your work as a data scientist. <a href="@sec-3-intro">Section 3</a> will start to introduce you to a baseline of IT/Admin knowledge.</p>
-<p>This section is the bridge between the two.</p>
-<p>In this section, you’ll learn about the tools that IT/Admins use every day like the command line, SSH, and Docker. It turns out that these tools can also be really useful for day-to-day work as a data scientist, so I’d encourage you to read even if you never plan to do any IT/Admin work.</p>
-<p>As this section is focused on tooling, it’s much lighter on conceptual content than any other section. I’m not really going to explain why you might use these tools – just how. You might call it downright boring.</p>
-<p>You should at least skim this section so you know what’s here. Then, when we get into Linux and network administration in Section 3 and you’re lost, you’ll remember that there’s some help to be had here. Even if you’re comfortable SSH-ing into a server and using the command line and Docker, there might be some useful tricks or details.</p>
+<p>Welcome to the section of the book where you’ll learn about the basics of doing IT/Admin tasks yourself – the section I wish I hadn’t written.</p>
+<p>Taking data science work to production involves getting that work hosted somewhere. As a data scientist, you want to share a development environment with other data professionals or publish a data science project to non-technical stakeholders. That sharing requires that your work live on a centralized server somewhere, and someone has to administer that server.</p>
+<p>In my experience, data scientists are at their best when a professional IT/Admin takes responsibility for those administration tasks. But that partnership often isn’t achievable.</p>
+<p>Some data professionals work at small organizations that lack dedicated IT/Admins. Others are students or hobbyists trying to DIY something cheaply. And others work at organizations with IT/Admin teams, but that team lacks the time, interest, or expertise necessary to be helpful.</p>
+<p>Sometimes, a data scientist has to be their own IT/Admin to avoid being competely blocked from taking their work to production, which is the worst outcome. Many – if not most – data scientists find themselves responsible for administering the servers where their work runs at some point in their career.</p>
+<p>That’s a scary place to be. Administering a server as a novice admin is a little like jumping from a Honda Civic to wrangling a tractor-trailer. You’re going from managing personal devices for your own use to managing a work machine that people make a whole career out of.</p>
+<p>Even with the many online resources, the amount to learn can be completely overwhelming. And being a bad IT/Admin can mean security vulnerabilities, system instability, and general annoyance.</p>
+<p>So in this section, you’re going to learn the basics of being your own IT/Admin. You’ll be introduced to the topics in IT/Administration that are relevant for a data science project. By the end, you’ll be pretty comfortable administering a simple data science workbench or server to host a data science project.</p>
+<p>If you don’t have to be your own IT/Admin, that’s even better. Reading this section will give you an appreciation for what an IT/Admin does and help you be a better partner to them.</p>
+<section id="getting-and-running-a-server" class="level2">
+<h2 class="anchored" data-anchor-id="getting-and-running-a-server">Getting and running a server</h2>
+<p>The most common way to get a server for data science is to rent one from a cloud provider. In order to do data science tasks, many people combine their server with other services from the cloud provider. That’s why <a href="2-1-cloud.html">Chapter&nbsp;<span>7</span></a> is an introduction to what the cloud is and how you might want to use it for data science purposes.</p>
+<p>Unlike your phone or personal computer, you’ll never touch this cloud server you’ve rented. Instead, you’ll administer the server via a virtual interface from your computer. Moreover, servers generally don’t even have the kind of point-and-click interface you’re used to on your personal devices.</p>
+<p>Instead, you’ll access and manage your server from the text-only command line.That’s why <a href="2-2-cmd-line.html">Chapter&nbsp;<span>8</span></a> is all about how to set up the command line on your local machine to make it convenient and ergonomic and how to connect to your server for administration purposes using a technology called SSH.</p>
+<p>Unlike your Apple, Windows, or Android operating systems you’re used to on your personal devices, most servers run the Linux operating system. <a href="2-3-linux.html">Chapter&nbsp;<span>9</span></a> will teach you a little about what Linux is and will introduce you to the basics of Linux administration including how to think about files and users on a multi-tenant server.</p>
+<p>But you’re not interested in just running a Linux server. You want to use it to accomplish data science tasks. In particular, you’ll want to install data science tools like R, Python, RStudio, JupyterHub, and more. So you’ll need to learn how to install, run, and configure applications on your server. That’s why <a href="2-4-app-admin.html">Chapter&nbsp;<span>10</span></a> is about application administration.</p>
+<p>When your phone or computer gets slow or you run out of storage, it’s probably time for a new one. But a server is a working machine that can be scaled up or down to accommodate more people or heavier workloads over time. That means that you may have to manage the server’s resources much more actively than your personal devices. That’s why <a href="2-5-scale.html">Chapter&nbsp;<span>11</span></a> is all about managing and scaling server resources.</p>
+</section>
+<section id="making-it-safely-accessible" class="level2">
+<h2 class="anchored" data-anchor-id="making-it-safely-accessible">Making it (safely) accessible</h2>
+<p>Unless you’re doing something really silly, your personal devices aren’t accessible to anyone who isn’t physically touching the device. In contrast, most servers are only useful <strong>because</strong> they’re addressable on a computer network, perhaps even the open internet.</p>
+<p>Making a server accessible to people over the internet makes it useful, but it also introduces risk. Many dastardly plans for your personal devices are thwarted because a villain would have to physically steal it to get access. For a server, allowing digital access means there are many more potential threats looking to steal data or hijack your computational resources for nefarious ends. You’ve got to be careful about how you’re providing access to the machine.</p>
+<p>Moreover, risk aside, computer networking is a complicated topic, and making it work right can be somewhat difficult. Following random tutorials on the internet is a great way to eventually get your server working, but have no idea what happened or why it suddenly works.</p>
+<p>The good news is that it’s not magic. <a href="2-6-networking.html">Chapter&nbsp;<span>12</span></a> is all about how computers find each other across a network. Once you understand the basic structure and operations of a computer network, making only the things you intend to be public on your server will be much easier.</p>
+<p>Aside from a basic introduction to computer networking, there are two other things you’ll want to configure to make your server safe and accessible. The first is to host your server at a human-friendly URL, which you’ll learn how to configure in <a href="2-7-dns.html">Chapter&nbsp;<span>13</span></a>. The second is to add SSL/TLS to your server to secure the traffic going to and from your server. You’ll learn how to do that in <a href="2-8-ssl.html">Chapter&nbsp;<span>14</span></a>.</p>
+<p>Once you’ve finished these chapters, you’ll have a basic understanding of all the main topics in IT/Admin that are likely to come up as you try to administer a simple data science workbench or project hosting platform.</p>
+</section>
 <section id="labs-in-this-section" class="level2">
 <h2 class="anchored" data-anchor-id="labs-in-this-section">Labs in this Section</h2>
-<p>There’s only one lab in this section in <a href="2-4-docker.html">Chapter&nbsp;<span>9</span></a> on using Docker. Docker is a hot enough topic that I felt it was worth spending some more time on. In this chapter, you’ll take the Palmer Penguins mass prediction API and app and learn how to Docker-ize them.</p>
+<p>In the first section of the book, the labs involved creating a DevOps-friendly data science project. In this section, the labs will revolve around actually putting that project into production.</p>
+<p>You’ll start by standing up an AWS EC2 instance, configuring your local command line, and connecting to the server via SSH. Once you’ve done that, you’ll learn how to create users on the server and access the server as a particular user.</p>
+<p>At that point, you’ll be ready to transition into data science work. You’ll add R, Python, RStudio Server, and JupyterHub to your server and get them configured for work. Additionally, you’ll deploy the Shiny App and API you created in the book’s first section onto the server.</p>
+<p>Once the server itself is configured, you’ll need to configure the server’s networking to make it accessible and secure. You’ll learn how to open the proper ports and configure a proxy to access multiple services on the same server, and you’ll learn to configure DNS records so your server is available at a real URL and SSL so it can all be done securely.</p>
+<p>By the time you’ve finished the labs in this section, you’ll be able to use your EC2 instance as a data science workbench and add your penguin mass prediction Shiny App to the Quarto website you created in the book’s first section.</p>
 <p>For more details on what you’ll do in each chapter, see <a href="../append/lab-map.html">Appendix&nbsp;<span>B</span></a>.</p>
 
 
@@ -603,13 +620,13 @@ <h2 class="anchored" data-anchor-id="labs-in-this-section">Labs in this Section<
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-        <i class="bi bi-arrow-left-short"></i> <span class="nav-page-text"><span class="chapter-number">5</span>&nbsp; <span class="chapter-title">Deployments and code promotion</span></span>
+      <a href="../../chapters/sec1/1-6-docker.html" class="pagination-link">
+        <i class="bi bi-arrow-left-short"></i> <span class="nav-page-text"><span class="chapter-number">6</span>&nbsp; <span class="chapter-title">Demystifying Docker</span></span>
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-        <span class="nav-page-text"><span class="chapter-number">6</span>&nbsp; <span class="chapter-title">Opening the Command Line</span></span> <i class="bi bi-arrow-right-short"></i>
+      <a href="../../chapters/sec2/2-1-cloud.html" class="pagination-link">
+        <span class="nav-page-text"><span class="chapter-number">7</span>&nbsp; <span class="chapter-title">The Cloud</span></span> <i class="bi bi-arrow-right-short"></i>
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+ <span class="menu-text"><span class="chapter-number">12</span>&nbsp; <span class="chapter-title">Intro to Computer Networks</span></span></a>
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+ <span class="menu-text"><span class="chapter-number">13</span>&nbsp; <span class="chapter-title">DNS allows for human-readable addresses</span></span></a>
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+ <span class="menu-text"><span class="chapter-number">14</span>&nbsp; <span class="chapter-title">You should use SSL/HTTPS</span></span></a>
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+      <div class="sidebar-item-container"> 
+            <a href="../../chapters/sec3/3-0-sec-intro.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text">Making it Enterprise-Grade</span></a>
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+ <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></a>
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+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/sec3/3-2-ent-networks.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></a>
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+  <a href="../../chapters/sec3/3-3-auth.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></a>
+  </div>
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+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/sec3/3-4-ent-servers.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></a>
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+        <nav id="TOC" role="doc-toc" class="toc-active">
+    <h2 id="toc-title">Table of contents</h2>
+   
+  <ul>
+  <li><a href="#the-cloud-is-rental-servers" id="toc-the-cloud-is-rental-servers" class="nav-link active" data-scroll-target="#the-cloud-is-rental-servers"><span class="header-section-number">7.1</span> The cloud is rental servers</a></li>
+  <li><a href="#real-and-fake-cloud-benefits" id="toc-real-and-fake-cloud-benefits" class="nav-link" data-scroll-target="#real-and-fake-cloud-benefits"><span class="header-section-number">7.2</span> Real (and fake) cloud benefits</a></li>
+  <li><a href="#understanding-cloud-services" id="toc-understanding-cloud-services" class="nav-link" data-scroll-target="#understanding-cloud-services"><span class="header-section-number">7.3</span> Understanding cloud services</a>
+  <ul class="collapse">
+  <li><a href="#iaas-offerings" id="toc-iaas-offerings" class="nav-link" data-scroll-target="#iaas-offerings"><span class="header-section-number">7.3.1</span> IaaS Offerings</a></li>
+  <li><a href="#paas-offerings" id="toc-paas-offerings" class="nav-link" data-scroll-target="#paas-offerings"><span class="header-section-number">7.3.2</span> PaaS Offerings</a></li>
+  <li><a href="#saas-offerings" id="toc-saas-offerings" class="nav-link" data-scroll-target="#saas-offerings"><span class="header-section-number">7.3.3</span> SaaS Offerings</a></li>
+  <li><a href="#common-services" id="toc-common-services" class="nav-link" data-scroll-target="#common-services"><span class="header-section-number">7.3.4</span> Common Services</a></li>
+  </ul></li>
+  <li><a href="#comprehension-questions" id="toc-comprehension-questions" class="nav-link" data-scroll-target="#comprehension-questions"><span class="header-section-number">7.4</span> Comprehension Questions</a></li>
+  <li><a href="#introduction-to-labs" id="toc-introduction-to-labs" class="nav-link" data-scroll-target="#introduction-to-labs"><span class="header-section-number">7.5</span> Introduction to Labs</a></li>
+  <li><a href="#lab-getting-started-with-aws" id="toc-lab-getting-started-with-aws" class="nav-link" data-scroll-target="#lab-getting-started-with-aws"><span class="header-section-number">7.6</span> Lab: Getting started with AWS</a>
+  <ul class="collapse">
+  <li><a href="#step-1-login-to-the-aws-console" id="toc-step-1-login-to-the-aws-console" class="nav-link" data-scroll-target="#step-1-login-to-the-aws-console"><span class="header-section-number">7.6.1</span> Step 1: Login to the AWS Console</a></li>
+  <li><a href="#step-2-stand-up-an-ec2-instance" id="toc-step-2-stand-up-an-ec2-instance" class="nav-link" data-scroll-target="#step-2-stand-up-an-ec2-instance"><span class="header-section-number">7.6.2</span> Step 2: Stand up an EC2 instance</a></li>
+  <li><a href="#step-3-start-the-server" id="toc-step-3-start-the-server" class="nav-link" data-scroll-target="#step-3-start-the-server"><span class="header-section-number">7.6.3</span> Step 3: Start the Server</a></li>
+  <li><a href="#optional-stop-the-server" id="toc-optional-stop-the-server" class="nav-link" data-scroll-target="#optional-stop-the-server"><span class="header-section-number">7.6.4</span> Optional: Stop the Server</a></li>
+  </ul></li>
+  <li><a href="#lab-put-the-penguins-data-and-model-in-s3" id="toc-lab-put-the-penguins-data-and-model-in-s3" class="nav-link" data-scroll-target="#lab-put-the-penguins-data-and-model-in-s3"><span class="header-section-number">7.7</span> Lab: Put the penguins data and model in S3</a>
+  <ul class="collapse">
+  <li><a href="#step-1-create-an-s3-bucket" id="toc-step-1-create-an-s3-bucket" class="nav-link" data-scroll-target="#step-1-create-an-s3-bucket"><span class="header-section-number">7.7.1</span> Step 1: Create an S3 bucket</a></li>
+  <li><a href="#step-2-push-new-models-to-s3" id="toc-step-2-push-new-models-to-s3" class="nav-link" data-scroll-target="#step-2-push-new-models-to-s3"><span class="header-section-number">7.7.2</span> Step 2: Push new models to S3</a></li>
+  <li><a href="#step-3-pull-the-api-model-from-s3" id="toc-step-3-pull-the-api-model-from-s3" class="nav-link" data-scroll-target="#step-3-pull-the-api-model-from-s3"><span class="header-section-number">7.7.3</span> Step 3: Pull the API model from S3</a></li>
+  <li><a href="#step-4-give-github-actions-s3-credentials" id="toc-step-4-give-github-actions-s3-credentials" class="nav-link" data-scroll-target="#step-4-give-github-actions-s3-credentials"><span class="header-section-number">7.7.4</span> Step 4: Give GitHub Actions S3 credentials</a></li>
+  <li><a href="#lab-extensions" id="toc-lab-extensions" class="nav-link" data-scroll-target="#lab-extensions"><span class="header-section-number">7.7.5</span> Lab Extensions</a></li>
+  </ul></li>
+  </ul>
+<div class="toc-actions"><div><i class="bi bi-github"></i></div><div class="action-links"><p><a href="https://github.com/akgold/do4ds/edit/main/chapters/sec2/2-1-cloud.qmd" class="toc-action">Edit this page</a></p></div></div></nav>
+    </div>
+<!-- main -->
+<main class="content" id="quarto-document-content">
+
+<header id="title-block-header" class="quarto-title-block default">
+<div class="quarto-title">
+<h1 class="title"><span id="sec-cloud" class="quarto-section-identifier"><span class="chapter-number">7</span>&nbsp; <span class="chapter-title">The Cloud</span></span></h1>
+</div>
+
+
+
+<div class="quarto-title-meta">
+
+    
+  
+    
+  </div>
+  
+
+</header>
+
+<p>Nearly every data science organization is already working in the cloud or is considering a cloud transition. As someone who doesn’t spend your day working directly with cloud services, trying to understand what the cloud is can feel like trying to catch a – well, you know – and pin it down.<a href="#fn1" class="footnote-ref" id="fnref1" role="doc-noteref"><sup>1</sup></a></p>
+<p>But the cloud is very real and very important to the way production data science gets done. In this chapter, you’ll learn about what the cloud is and get an introduction to important cloud services for data science.</p>
+<p>This chapter has two labs. In the first, you’ll get started with a server in <em>AWS (Amazon Web Services)</em> – getting it stood up and learning how to start and stop it. In the second lab, you’ll put the model from our penguin mass modeling lab into an S3 bucket (more on what that is in a bit).</p>
+<section id="the-cloud-is-rental-servers" class="level2" data-number="7.1">
+<h2 data-number="7.1" class="anchored" data-anchor-id="the-cloud-is-rental-servers"><span class="header-section-number">7.1</span> The cloud is rental servers</h2>
+<p>At one time, the only way to get servers was to buy physical machines and hire someone to install and maintain them. This is called running the servers <em>on-prem</em> (short for premises). There are some organizations, especially those with highly sensitive data, that still run on-prem servers.</p>
+<p>The problem is that on-prem servers require a large up-front investment in server hardware and professional capacity. If your company has a use case that only requires a single server or one with uncertain payoff, it probably isn’t worth it to hire someone and buy a bunch of hardware.</p>
+<p>Around the year 2000, Amazon took all the server farms across the company and centralized them so teams would use this central server capacity instead of running their own. Over the next few years, Amazon execs (correctly) realized that other companies and organizations would value this ability to rent server capacity. They launched this “rent a server” business as AWS in 2006.</p>
+<p>These days, the cloud platform business is enormous – collectively nearly a quarter of a trillion dollars. It’s also highly profitable. AWS was only 13% of Amazon’s revenue in 2021, but a whopping 74% of the company’s profits for that year.<a href="#fn2" class="footnote-ref" id="fnref2" role="doc-noteref"><sup>2</sup></a></p>
+<p>AWS is still the biggest cloud platform by a considerable margin, but it’s far from alone. Approximately 2/3 of the market consists of <em>the big three</em> – AWS, Microsoft Azure, and Google Cloud Platform (GCP) with the final third made up of numerous smaller companies.<a href="#fn3" class="footnote-ref" id="fnref3" role="doc-noteref"><sup>3</sup></a></p>
+</section>
+<section id="real-and-fake-cloud-benefits" class="level2" data-number="7.2">
+<h2 data-number="7.2" class="anchored" data-anchor-id="real-and-fake-cloud-benefits"><span class="header-section-number">7.2</span> Real (and fake) cloud benefits</h2>
+<p>The cloud arrived with an avalanche of marketing fluff. Over a decade after the cloud went mainstream, it’s clear that some of the purported benefits are real and some are less so. You can be a much more intelligent cloud consumer if you understand which is which.</p>
+<p>The most important cloud benefit is flexibility. Moving to the cloud allows you to get a new server or re-scale an existing one in minutes, and you only pay for what you use, often on an hourly basis.<a href="#fn4" class="footnote-ref" id="fnref4" role="doc-noteref"><sup>4</sup></a> The risk of incorrectly guessing how much capacity you’ll need is drastically reduced, making it way less risky to get started on a server.</p>
+<p>The other big benefit of the cloud is that it allows IT/Admin teams to narrow their scope and focus. For most organizations, managing physical servers isn’t part of their core competency and outsourcing that work to a cloud provider is a great choice.</p>
+<div class="callout callout-style-default callout-note callout-titled">
+<div class="callout-header d-flex align-content-center">
+<div class="callout-icon-container">
+<i class="callout-icon"></i>
+</div>
+<div class="callout-title-container flex-fill">
+Note
+</div>
+</div>
+<div class="callout-body-container callout-body">
+<p>One other dynamic is the incentives of individual IT/Admins. As technical professionals, IT/Admins want evidence on their resumes that they have experience with the latest and greatest technologies, which are generally cloud services these days rather than managing physical hardware.</p>
+</div>
+</div>
+<p>Along with these very real benefits, the cloud was supposed to enable big time savings relative to on-prem operations. For the most part, that hasn’t materialized.</p>
+<p>The theory was that the cloud would enable organiations to scale their capacity to match need at any given moment. So even if the hourly price was higher, the organization would turn servers off at night or during slow periods and save money.</p>
+<p>It turns out that dynamic server scaling loads takes a fair amount of engineering effort and only the most sophisticated IT/Admin organizations have implemented effective autoscaling. And even for the organizations that do autoscale, cloud providers are very good at pricing their products to capture a lot of those savings.</p>
+<p>Some large organizations with stable workloads have actually started doing <em>cloud repatriations</em> – bringing workloads back on-prem for significant cost savings. An <a href="https://a16z.com/2021/05/27/cost-of-cloud-paradox-market-cap-cloud-lifecycle-scale-growth-repatriation-optimization/">a16z study</a> found that for certain organizations, the total cost of repatriated workloads, including staffing, could be 1/3 to 1/2 the cost of using a cloud provider.<a href="#fn5" class="footnote-ref" id="fnref5" role="doc-noteref"><sup>5</sup></a></p>
+<p>That said, even if the cash savings aren’t meaningful, the cloud is a key enabler for many businesses. The ability to start small, focus on what matters, and scale up quickly is more than worth it.</p>
+<p>You may be interested in buying a physical server or re-purposing an old computer just for fun. You’re in good company; I’ve run Ubuntu Server on more than one old laptop. But if you’re trying to spend more time getting important things done and less time playing, getting a server from the cloud is the way to go.</p>
+</section>
+<section id="understanding-cloud-services" class="level2" data-number="7.3">
+<h2 data-number="7.3" class="anchored" data-anchor-id="understanding-cloud-services"><span class="header-section-number">7.3</span> Understanding cloud services</h2>
+<p>In the beginning, cloud providers did just one thing – rent you a server. But they didn’t stop there. Instead, they started building layers and layers of services that abstract away more IT/Admin tasks.</p>
+<p>At the end of the day, all cloud services boil down to “rent me an <span class="math inline">\(\text{X}\)</span>”. As a data scientist, you should start by decoding “What is the <span class="math inline">\(\text{X}\)</span>?”</p>
+<p>Unfortunately, cloud marketing materials aren’t usually oriented to the data scientist trying to decide whether to use the services, instead they’re oriented at your boss and your boss’s boss, who wants to hear about benefits of using the service. That can make it difficult to decode what <span class="math inline">\(\text{X}\)</span> is.</p>
+<p>It’s helpful to keep in mind that, at the end of the day, every service that isn’t directly renting a server is just renting server that already has certain software pre-installed and configured.<a href="#fn6" class="footnote-ref" id="fnref6" role="doc-noteref"><sup>6</sup></a></p>
+<div class="callout callout-style-default callout-note callout-titled">
+<div class="callout-header d-flex align-content-center">
+<div class="callout-icon-container">
+<i class="callout-icon"></i>
+</div>
+<div class="callout-title-container flex-fill">
+Less of serverless computing
+</div>
+</div>
+<div class="callout-body-container callout-body">
+<p>You might hear people talking about going <em>serverless</em>. There is no such thing as serverless computing. Serverless is a marketing term meant to convey that <strong>you</strong> don’t have to manage the servers. The cloud provider manages them for you, but they’re still there.</p>
+</div>
+</div>
+<p>Cloud services are sometimes grouped into three layers to indicate whether you’re renting a basic computing service or something more complete.</p>
+<p>An analogy to a more familiar layered object may serve to make things clear. Let’s say you’re throwing a birthday party for a friend. You’re planning to bring a chocolate layer cake with vanilla frosting topped with lavender rosettes and “Happy Birthday!” in teal.<a href="#fn7" class="footnote-ref" id="fnref7" role="doc-noteref"><sup>7</sup></a></p>
+<div class="callout callout-style-default callout-note callout-titled">
+<div class="callout-header d-flex align-content-center">
+<div class="callout-icon-container">
+<i class="callout-icon"></i>
+</div>
+<div class="callout-title-container flex-fill">
+Big Three Service Naming
+</div>
+</div>
+<div class="callout-body-container callout-body">
+<p>In this next section, I’ll mention services for common tasks from the big three. AWS tends use cutesy names that have a tangential relationship to the task at hand. Azure and GCP name their offerings more literally.</p>
+<p>This makes AWS names a little harder to learn, but much easier to recall once you’ve learned them. A table of all the services mentioned in this chapter is in <a href="../append/cheatsheets.html">Appendix&nbsp;<span>C</span></a>.</p>
+</div>
+</div>
+<section id="iaas-offerings" class="level3" data-number="7.3.1">
+<h3 data-number="7.3.1" class="anchored" data-anchor-id="iaas-offerings"><span class="header-section-number">7.3.1</span> IaaS Offerings</h3>
+<p><em>Infrastructure as a service</em> (<em>IaaS</em>, pronounced eye-ahzz) is the basic rent a server premise from the earliest days of the cloud.</p>
+<p>From a data science perspective, a IaaS offering might look like what we’re doing in the lab in this book – acquiring a server, networking, and storage from the cloud provider and assembling it into a data science workbench. This is definitely the best way to learn how to administer a data science environment and it’s the cheapest option, but it’s also the most time-consuming.</p>
+<p>This would be like choosing to go to the grocery store, buy all the ingredients, and bake and decorate your friend’s cake from scratch.</p>
+<p>Along with a server, you’ll rent storage and networking to make everything work properly.</p>
+<p>Some common IaaS services you’re likely to use include:</p>
+<ul>
+<li><p>Renting a server from AWS with <em>EC2 (Elastic Cloud Compute)</em>, from Azure with <em>Azure VMs</em>, and from GCP with <em>Google Compute Engine Instances</em>.</p></li>
+<li><p>Unlike your laptop, rented servers don’t include a hard drive, so you’ll have to attach storage with AWS’s <em>EBS (Elastic Block Store)</em>, <em>Azure Managed Disk</em>, or <em>Google Persistent Disk</em>.</p></li>
+<li><p>Creating and managing the networking where your servers sit with AWS’s <em>VPC (Virtual Private Cloud)</em>, Azure’s<em>Virtual Network</em>, and GCP’s <em>Virtual Private Cloud</em>.</p></li>
+<li><p>Managing DNS records via AWS’s <em>Route 53</em>, <em>Azure</em> <em>DNS</em>, and <em>Google Cloud DNS</em>. (More on what this means in <a href="2-7-dns.html">Chapter&nbsp;<span>13</span></a>.</p></li>
+</ul>
+<p>While IaaS means the IT/Admins don’t have to be responsible for physical management of servers, they’re responsible for everything else, including keeping the servers updated and secured. For that reason, many organizations are moving away from IaaS towards something more managed these days.</p>
+</section>
+<section id="paas-offerings" class="level3" data-number="7.3.2">
+<h3 data-number="7.3.2" class="anchored" data-anchor-id="paas-offerings"><span class="header-section-number">7.3.2</span> PaaS Offerings</h3>
+<p>In a <em>PaaS (Platform as a Service)</em> solution, you hand off management of the servers, but manage the applications you need via an API specific to that service. From a data science perspective, a PaaS setup might look like hosting a JupyterHub, RStudio, or Posit implementation in EKS, or running an ML API in Lambda.</p>
+<p>In the cake baking world, PaaS would be like buying a pre-made cake and some tins of frosting and doing only the writing and rosettes yourself.</p>
+<p>One PaaS service that already came up in the book is <em>blob (Binary Large Object)</em> storage. Blob storage allows you to store individual objects somewhere and recall them to any other machine that has access to the blob store. The major blob stores are AWS’s <em>S3 (Simple Storage Service)</em>, <em>Azure Blob Storage</em>, and <em>Google Cloud Storage</em>.</p>
+<p>You’re also likely to make use of cloud-based database, data lake, and data warehouse offerings. There are numerous different offerings, and the ones that you use will depend a lot on your use case and your organization. The ones I’ve seen used most frequently are <em>RDS</em> or <em>Redshift</em> from AWS, <em>Azure Database</em>, and <em>Google BigQuery.</em> This category also includes a number of offerings from outside the big three, most notably <em>Snowflake</em> and <em>Databricks</em>.</p>
+<p>Depending on your organization, you may also use services that run APIs or applications from containers or machine images like AWS’s <em>ECS (Elastic Container Service)</em>, <em>Elastic Beanstalk</em>, or <em>Lambda</em>, Azure’s <em>Container Apps</em> or <em>Functions</em>, or GCP’s <em>App Engine</em> or <em>Cloud Functions</em>.</p>
+<p>Increasingly, organizations are turning to <em>Kubernetes</em> as a way to host services. (More on that in <a href="../sec3/3-4-ent-servers.html">Chapter&nbsp;<span>18</span></a>.) Most organizations who do so use a cloud provider’s Kubernetes cluster as a service: AWS’s <em>EKS (Elastic Kubernetes Service)</em> or <em>Fargate</em>, Azure’s <em>AKS (Azure Kubernetes Service)</em>, or GCP’s <em>GKE (Google Kubernetes Engine)</em>.</p>
+<p>Many organizations are moving to PaaS solutions for hosting applications for internal use. It takes away the hassle of managing and updating actual servers. On the flipside, these offerings are somewhat less flexible than just renting a server, and some applications don’t run well in these environments.</p>
+</section>
+<section id="saas-offerings" class="level3" data-number="7.3.3">
+<h3 data-number="7.3.3" class="anchored" data-anchor-id="saas-offerings"><span class="header-section-number">7.3.3</span> SaaS Offerings</h3>
+<p>SaaS (Software as a Service) is where you just rent the end-user software for usage, often on the basis of seats or usage. You’re already used to consumer SaaS software like Gmail, Slack, and Office365.</p>
+<p>The cake equivalent of SaaS would be just going to a bakery and buying a cake for your friend.</p>
+<p>Depending on your organization, you might use a SaaS data science offering like AWS’s <em>SageMaker</em>, Azure’s <em>Azure ML</em>, or GCP’s <em>Vertex AI</em> or <em>Cloud Workstations</em>.</p>
+<p>The great thing about SaaS offerings is that you get immediate access to the end-user application and it’s usually trivial (aside from cost) to add more users. IT/Admin configuration is generally limited to hooking up integrations, most often authentication and/or data sources.</p>
+<p>The tradeoff for this ease is that they’re generally more expensive and you’re at the mercy of the provider for configuration and upgrades.</p>
+</section>
+<section id="common-services" class="level3" data-number="7.3.4">
+<h3 data-number="7.3.4" class="anchored" data-anchor-id="common-services"><span class="header-section-number">7.3.4</span> Common Services</h3>
+<p>Irrespective of the particular services you want to use, there are a few basic services you’ll almost certainly have to interact with.</p>
+<p>Regardless of what you’re trying to do, if you’re working in the cloud, you have to make sure that the right people have the right permissions. In order to manage these permissions, AWS has <em>IAM (Identity and Access Management)</em>, GCP has <em>Identity Access Management</em>, and Azure has <em>Microsoft Entra ID</em>, which was called <em>Azure Active Directory</em> until the summer of 2023. Your organization might integrate these services with a SaaS identity management solution like Okta or OneLogin.</p>
+<p>Additionally, some cloud services are geographically specific. Each of the cloud providers has split the world into a number of geographic areas, which they all call <em>regions</em>.</p>
+<p>Some services are region-specific and can only interact with other services in that region by default. If you’re doing things yourself, I recommend just choosing the region where you live and putting everything there. Costs and service availability does vary somewhat across region, but it shouldn’t be materially different for what you’re trying to do.</p>
+<p>Regions are subdivided into <em>availability zones</em> (AZs). AZs are subdivisions of regions that are designed to be independent. Some organizations want to run services that span multiple availability zones to provide protection against outages in any particular geography. If you’re running something sophisticated enough to need multi-AZ configuration, you should really be working with a professional IT/Admin.</p>
+</section>
+</section>
+<section id="comprehension-questions" class="level2" data-number="7.4">
+<h2 data-number="7.4" class="anchored" data-anchor-id="comprehension-questions"><span class="header-section-number">7.4</span> Comprehension Questions</h2>
+<ol type="1">
+<li>What are two reasons you should consider going to the cloud? What’s one reason you shouldn’t?</li>
+<li>What is the difference between PaaS, IaaS, and SaaS? What’s an example of each that you’re familiar with?</li>
+<li>What are the names for AWS’s services for: renting a server, file system storage, blob storage</li>
+</ol>
+</section>
+<section id="introduction-to-labs" class="level2" data-number="7.5">
+<h2 data-number="7.5" class="anchored" data-anchor-id="introduction-to-labs"><span class="header-section-number">7.5</span> Introduction to Labs</h2>
+<p>Welcome to the lab!</p>
+<p>The point of these exercises is to get you hands on with running servers and get you practicing the things you’re learning in the rest of the book.</p>
+<p>If you walk through the labs sequentially, you’ll end up with a working data science workbench. It won’t suffice for any enterprise-level requirements, but it’ll be secure enough for a hobby project or even a small team.</p>
+<p>For this lab, we’re going to use services from AWS, as they’re the biggest cloud provider and the one you’re most likely to run into in the real world. Because we’ll be mostly using IaaS services, there are very close analogs from Azure and GCP should you want to use one of them instead.</p>
+</section>
+<section id="lab-getting-started-with-aws" class="level2" data-number="7.6">
+<h2 data-number="7.6" class="anchored" data-anchor-id="lab-getting-started-with-aws"><span class="header-section-number">7.6</span> Lab: Getting started with AWS</h2>
+<p>In this first lab, we’re going to get you up and running with an AWS account and show you how to manage, start, and stop EC2 instances in AWS.</p>
+<p>The server we’ll stand up will be from AWS’s <em>free tier</em> – so there will be no cost involved as long as you haven’t used up all your AWS free tier credits before now.</p>
+<div class="callout callout-style-default callout-tip callout-titled">
+<div class="callout-header d-flex align-content-center">
+<div class="callout-icon-container">
+<i class="callout-icon"></i>
+</div>
+<div class="callout-title-container flex-fill">
+Tip
+</div>
+</div>
+<div class="callout-body-container callout-body">
+<p>Throughout the labs, I’ll suggest you name things in certain ways. You can do what you want, but I’ll be consistent with those names, so you can copy commands straight from the book if you use the same name.</p>
+<p>If you want to follow along in that way, start by creating a standalone directory for this lab, named <code>do4ds-lab</code>.</p>
+</div>
+</div>
+<section id="step-1-login-to-the-aws-console" class="level3" data-number="7.6.1">
+<h3 data-number="7.6.1" class="anchored" data-anchor-id="step-1-login-to-the-aws-console"><span class="header-section-number">7.6.1</span> Step 1: Login to the AWS Console</h3>
+<p>We’re going to start by logging into AWS at <a href="https://aws.amazon.com" class="uri">https://aws.amazon.com</a>.</p>
+<div class="callout callout-style-default callout-note callout-titled">
+<div class="callout-header d-flex align-content-center">
+<div class="callout-icon-container">
+<i class="callout-icon"></i>
+</div>
+<div class="callout-title-container flex-fill">
+Note
+</div>
+</div>
+<div class="callout-body-container callout-body">
+<p>An AWS account is separate from an Amazon account for ordering stuff online and watching movies. You’ll have to create one if you’ve never used AWS before.</p>
+</div>
+</div>
+<p>Once you’ve logged in, you’ll be confronted by the AWS console. There are a ton of things here. Poke around if you want and then continue when you’re ready.</p>
+</section>
+<section id="step-2-stand-up-an-ec2-instance" class="level3" data-number="7.6.2">
+<h3 data-number="7.6.2" class="anchored" data-anchor-id="step-2-stand-up-an-ec2-instance"><span class="header-section-number">7.6.2</span> Step 2: Stand up an EC2 instance</h3>
+<p>There are five attributes about your EC2 instance you’ll want to configure. If it’s not mentioned here, just stick with the defaults for now.</p>
+<p>In particular, just stick with the default <em>Security Group</em>. We’ll get into what they are and how to configure them later.</p>
+<section id="name-tags" class="level4" data-number="7.6.2.1">
+<h4 data-number="7.6.2.1" class="anchored" data-anchor-id="name-tags"><span class="header-section-number">7.6.2.1</span> Name + Tags</h4>
+<p>Instance <em>name and tags</em> are human-readable labels so you can remember what this instance is. Neither name nor tag are required, but I’d recommend you name the server something like <code>do4ds-lab</code> in case you stand up others later.</p>
+<p>If you’re doing this at work, there may be tagging policies so that the IT/Admin team can figure out who servers belong to later.</p>
+</section>
+<section id="image" class="level4" data-number="7.6.2.2">
+<h4 data-number="7.6.2.2" class="anchored" data-anchor-id="image"><span class="header-section-number">7.6.2.2</span> Image</h4>
+<p>An <em>image</em> is a snapshot of a system and serves as the starting point for your server. AWS’s are called <em>AMIs</em> (<em>Amazon Machine Images</em>). They range from free images of bare operating system to paid images that come bundled with software you might want.</p>
+<p>Choose an AMI that’s just the newest LTS Ubuntu operating system. As of this writing, that’s 22.04. It should say <em>free tier eligible</em>.</p>
+</section>
+<section id="instance-type" class="level4" data-number="7.6.2.3">
+<h4 data-number="7.6.2.3" class="anchored" data-anchor-id="instance-type"><span class="header-section-number">7.6.2.3</span> Instance Type</h4>
+<p>The <em>instance type</em> identifies the capability of the machine you’re renting. An instance type is made up of a <em>family</em> and a <em>size</em>. The family is the category of server and is denoted by letters and numbers, so there are T2s and T3s, C4s, R5s, and many more.</p>
+<p>Within each family, there are different sizes. Possible sizes vary by the family, but generally range from <em>nano</em> to multiples of <em>xlarge</em> like <em>24.xlarge</em>.</p>
+<p>For now, I’d recommend you get the largest server that is free tier eligible. As of this writing, that’s a <em>t2.micro</em> with 1 CPU and 1 Gb of memory.</p>
+<div class="callout callout-style-default callout-note callout-titled">
+<div class="callout-header d-flex align-content-center">
+<div class="callout-icon-container">
+<i class="callout-icon"></i>
+</div>
+<div class="callout-title-container flex-fill">
+Server sizing for the lab
+</div>
+</div>
+<div class="callout-body-container callout-body">
+<p>A <em>t2.micro</em> with 1 CPU and 1 Gb of memory is a very small server. For example, your laptop probably has at least 8 CPUs and 16 Gb of memory.</p>
+<p>A t2.micro should be sufficient for finishing the lab, but you’ll need a substantially larger server to do any real data science work.</p>
+<p>Luckily, it’s easy to upgrade cloud server sizes later. More on how, as well as advice on sizing servers for real data science work in <a href="2-5-scale.html">Chapter&nbsp;<span>11</span></a>.</p>
+</div>
+</div>
+</section>
+<section id="keypair" class="level4" data-number="7.6.2.4">
+<h4 data-number="7.6.2.4" class="anchored" data-anchor-id="keypair"><span class="header-section-number">7.6.2.4</span> Keypair</h4>
+<p>The <em>keypair</em> is the skeleton key to your server. We’ll get more into how to use and configure it in <a href="2-2-cmd-line.html">Chapter&nbsp;<span>8</span></a>. For now, create a new keypair. I’d recommend naming it <code>do4ds-lab-key</code>. Download the <code>.pem</code> version and put it in your <code>do4ds-lab</code> directory.</p>
+</section>
+<section id="storage" class="level4" data-number="7.6.2.5">
+<h4 data-number="7.6.2.5" class="anchored" data-anchor-id="storage"><span class="header-section-number">7.6.2.5</span> Storage</h4>
+<p>Bump up the storage to as much as you can get under the free tier, because why not? As of this writing, that’s 30 Gb.</p>
+</section>
+</section>
+<section id="step-3-start-the-server" class="level3" data-number="7.6.3">
+<h3 data-number="7.6.3" class="anchored" data-anchor-id="step-3-start-the-server"><span class="header-section-number">7.6.3</span> Step 3: Start the Server</h3>
+<p>If you followed these instructions, you should now be looking at a summary that lists the operating system, server type, firewall, and storage. Go ahead an launch your instance.</p>
+<p>If you go back to the EC2 page and click on <code>Instances</code> you can see your instance as it comes up. When it’s up, it will transition to <code>State: Running</code>.</p>
+</section>
+<section id="optional-stop-the-server" class="level3" data-number="7.6.4">
+<h3 data-number="7.6.4" class="anchored" data-anchor-id="optional-stop-the-server"><span class="header-section-number">7.6.4</span> Optional: Stop the Server</h3>
+<p>Whenever you’re stopping for the day, you may want to suspend your server so you’re not using up your free tier hours or paying for it. You can suspend an instance in the state it’s in so it can be restarted later. Suspended instances aren’t always free, but they’re generally very cheap.</p>
+<p>Whenever you want to suspend your instance, go to the EC2 page for your server. Under the <code>Instance State</code> drop down in the upper right, choose <code>Stop Instance</code>.</p>
+<p>After a couple minutes the instance will stop. Before you come back to the next lab, you’ll need to start the instance back up so it’s ready to go.</p>
+<p>If you want to completely delete the instance at any point, you can choose to <code>Terminate Instance</code> from that same <code>Instance State</code> dropdown.</p>
+</section>
+</section>
+<section id="lab-put-the-penguins-data-and-model-in-s3" class="level2" data-number="7.7">
+<h2 data-number="7.7" class="anchored" data-anchor-id="lab-put-the-penguins-data-and-model-in-s3"><span class="header-section-number">7.7</span> Lab: Put the penguins data and model in S3</h2>
+<p>Whether or not you’re hosting your own server, most data scientists working at an organization that uses AWS will run into S3, AWS’s blob store.</p>
+<p>One really common thing to store in S3 is an ML model. So we’re going to store the mass prediction model we created in Chapters <a href="../sec1/1-2-proj-arch.html"><span>Chapter&nbsp;2</span></a> and <a href="../sec1/1-3-data-access.html"><span>Chapter&nbsp;3</span></a> in an S3 bucket.</p>
+<section id="step-1-create-an-s3-bucket" class="level3" data-number="7.7.1">
+<h3 data-number="7.7.1" class="anchored" data-anchor-id="step-1-create-an-s3-bucket"><span class="header-section-number">7.7.1</span> Step 1: Create an S3 bucket</h3>
+<p>To start off with, you’ll have to create a bucket, most commonly from the AWS console. I’m naming mine <code>do4ds-lab</code>.</p>
+</section>
+<section id="step-2-push-new-models-to-s3" class="level3" data-number="7.7.2">
+<h3 data-number="7.7.2" class="anchored" data-anchor-id="step-2-push-new-models-to-s3"><span class="header-section-number">7.7.2</span> Step 2: Push new models to S3</h3>
+<p>Let’s change the code in our Quarto doc to push the model into S3 when the model rebuilds, instead of just saving it locally.</p>
+<p>There are a variety of different ways to access an S3 bucket. The simplest way is by using the AWS CLI on the command line. There are also R and Python packages for interacting with S3 (and other AWS services). The most common are Python’s <code>{boto3}</code> package or R’s <code>{paws}</code> and <code>{aws.s3}</code>.</p>
+<p>Regardless of what tooling you’re using, you’ll generally configure your credentials in three environment variables – <code>AWS_ACCESS_KEY_ID</code>, <code>AWS_SECRET_ACCESS_KEY</code>, and <code>AWS_REGION</code>. You can get the access key and secret access key from the AWS console and you should know the region.</p>
+<p>As always, when you’re developing in Python or R, I’d recommend putting these into a <code>.env</code> or a <code>config.yml</code> file and loading them from there.</p>
+<p>Since we built the model using <code>{vetiver}</code>, it’s really easy to push the model to S3 just by changing the board type to <code>board_s3</code> and making sure our credentials are defined in an environment variable.</p>
+<p>It’ll look something like this.</p>
+<div class="code-with-filename">
+<div class="code-with-filename-file">
+<pre><strong>model.qmd</strong></pre>
+</div>
+<div class="sourceCode" id="cb1" data-startfrom="64"><pre class="sourceCode numberSource python number-lines code-with-copy"><code class="sourceCode python" style="counter-reset: source-line 63;"><span id="cb1-64"><a href="#cb1-64"></a><span class="im">from</span> pins <span class="im">import</span> board_s3</span>
+<span id="cb1-65"><a href="#cb1-65"></a><span class="im">from</span> vetiver <span class="im">import</span> vetiver_pin_write</span>
+<span id="cb1-66"><a href="#cb1-66"></a></span>
+<span id="cb1-67"><a href="#cb1-67"></a>board <span class="op">=</span> board_s3(<span class="st">"do4ds-lab"</span>, allow_pickle_read<span class="op">=</span><span class="va">True</span>)</span>
+<span id="cb1-68"><a href="#cb1-68"></a>vetiver_pin_write(board, v)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+</div>
+<p>Under the hood, <code>{vetiver}</code> is making use of standard R and Python tooling to access an S3 bucket.</p>
+<p>Instead of using credentials, you could configure an <em>instance profile</em> using IAM, so the entire EC2 instance has access to the S3 bucket without needing credentials. Configuring instance profiles is the kind of thing you should work with a real IT/Admin to do.</p>
+</section>
+<section id="step-3-pull-the-api-model-from-s3" class="level3" data-number="7.7.3">
+<h3 data-number="7.7.3" class="anchored" data-anchor-id="step-3-pull-the-api-model-from-s3"><span class="header-section-number">7.7.3</span> Step 3: Pull the API model from S3</h3>
+<p>You’ll also have to configure the API to load the model from the S3 bucket. Luckily, this is very easy. Just update the script you used to build your <code>Dockerfile</code> so it pulls from the pin in the S3 bucket rather than the local folder.</p>
+<p>Now, the script to build the <code>Dockerfile</code> looks like this:</p>
+<div class="sourceCode" id="cb2" data-start_line="11" data-end_line="19"><pre class="sourceCode numberSource python number-lines code-with-copy"><code class="sourceCode python"><span id="cb2-1"><a href="#cb2-1"></a><span class="op">---</span></span>
+<span id="cb2-2"><a href="#cb2-2"></a>title: <span class="st">"Prepare Dockerfile"</span></span>
+<span id="cb2-3"><a href="#cb2-3"></a><span class="bu">format</span>:</span>
+<span id="cb2-4"><a href="#cb2-4"></a>  html:</span>
+<span id="cb2-5"><a href="#cb2-5"></a>    code<span class="op">-</span>fold: true</span>
+<span id="cb2-6"><a href="#cb2-6"></a><span class="op">---</span></span>
+<span id="cb2-7"><a href="#cb2-7"></a></span>
+<span id="cb2-8"><a href="#cb2-8"></a><span class="co">## Load Environment</span></span>
+<span id="cb2-9"><a href="#cb2-9"></a></span>
+<span id="cb2-10"><a href="#cb2-10"></a>```{python}</span>
+<span id="cb2-11"><a href="#cb2-11"></a><span class="im">from</span> dotenv <span class="im">import</span> load_dotenv</span>
+<span id="cb2-12"><a href="#cb2-12"></a></span>
+<span id="cb2-13"><a href="#cb2-13"></a>load_dotenv()</span>
+<span id="cb2-14"><a href="#cb2-14"></a></span>
+<span id="cb2-15"><a href="#cb2-15"></a><span class="im">from</span> pins <span class="im">import</span> board_s3</span>
+<span id="cb2-16"><a href="#cb2-16"></a><span class="im">from</span> vetiver <span class="im">import</span> vetiver_prepare_docker</span>
+<span id="cb2-17"><a href="#cb2-17"></a></span>
+<span id="cb2-18"><a href="#cb2-18"></a>board <span class="op">=</span> board_s3(<span class="st">"do4ds-lab"</span>, allow_pickle_read<span class="op">=</span><span class="va">True</span>)</span>
+<span id="cb2-19"><a href="#cb2-19"></a>vetiver_prepare_docker(board, <span class="st">"penguin_model"</span>)</span>
+<span id="cb2-20"><a href="#cb2-20"></a>```</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+</section>
+<section id="step-4-give-github-actions-s3-credentials" class="level3" data-number="7.7.4">
+<h3 data-number="7.7.4" class="anchored" data-anchor-id="step-4-give-github-actions-s3-credentials"><span class="header-section-number">7.7.4</span> Step 4: Give GitHub Actions S3 credentials</h3>
+<p>We want our model building to correctly push to S3 even when it’s running in GitHub Actions, but GitHub doesn’t have our S3 credentials by default, so we’ll need to provide them.</p>
+<p>We’re going to declare the variables we need in the <code>Render and Publish</code> step of the Action.</p>
+<p>Once you’re done, that section of the <code>publish.yml</code> should look something like this.</p>
+<div class="code-with-filename">
+<div class="code-with-filename-file">
+<pre><strong>.github/workflows/publish.yml</strong></pre>
+</div>
+<div class="sourceCode" id="cb3" data-start_line="45" data-end_line="49"><pre class="sourceCode numberSource yaml number-lines code-with-copy"><code class="sourceCode yaml"><span id="cb3-1"><a href="#cb3-1"></a><span class="fu">on</span><span class="kw">:</span></span>
+<span id="cb3-2"><a href="#cb3-2"></a><span class="at">  </span><span class="fu">workflow_dispatch</span><span class="kw">:</span></span>
+<span id="cb3-3"><a href="#cb3-3"></a><span class="at">  </span><span class="fu">push</span><span class="kw">:</span></span>
+<span id="cb3-4"><a href="#cb3-4"></a><span class="at">    </span><span class="fu">branches</span><span class="kw">:</span><span class="at"> main</span></span>
+<span id="cb3-5"><a href="#cb3-5"></a></span>
+<span id="cb3-6"><a href="#cb3-6"></a><span class="fu">name</span><span class="kw">:</span><span class="at"> Quarto Publish</span></span>
+<span id="cb3-7"><a href="#cb3-7"></a></span>
+<span id="cb3-8"><a href="#cb3-8"></a><span class="fu">jobs</span><span class="kw">:</span></span>
+<span id="cb3-9"><a href="#cb3-9"></a><span class="at">  </span><span class="fu">build-deploy</span><span class="kw">:</span></span>
+<span id="cb3-10"><a href="#cb3-10"></a><span class="at">    </span><span class="fu">runs-on</span><span class="kw">:</span><span class="at"> ubuntu-latest</span></span>
+<span id="cb3-11"><a href="#cb3-11"></a><span class="at">    </span><span class="fu">permissions</span><span class="kw">:</span></span>
+<span id="cb3-12"><a href="#cb3-12"></a><span class="at">      </span><span class="fu">contents</span><span class="kw">:</span><span class="at"> write</span></span>
+<span id="cb3-13"><a href="#cb3-13"></a><span class="at">    </span><span class="fu">steps</span><span class="kw">:</span></span>
+<span id="cb3-14"><a href="#cb3-14"></a><span class="at">      </span><span class="kw">-</span><span class="at"> </span><span class="fu">name</span><span class="kw">:</span><span class="at"> Check out repository</span></span>
+<span id="cb3-15"><a href="#cb3-15"></a><span class="at">        </span><span class="fu">uses</span><span class="kw">:</span><span class="at"> actions/checkout@v2</span></span>
+<span id="cb3-16"><a href="#cb3-16"></a></span>
+<span id="cb3-17"><a href="#cb3-17"></a><span class="at">      </span><span class="kw">-</span><span class="at"> </span><span class="fu">name</span><span class="kw">:</span><span class="at"> Set up Quarto</span></span>
+<span id="cb3-18"><a href="#cb3-18"></a><span class="at">        </span><span class="fu">uses</span><span class="kw">:</span><span class="at"> quarto-dev/quarto-actions/setup@v2</span></span>
+<span id="cb3-19"><a href="#cb3-19"></a></span>
+<span id="cb3-20"><a href="#cb3-20"></a><span class="at">      </span><span class="kw">-</span><span class="at"> </span><span class="fu">name</span><span class="kw">:</span><span class="at"> Install R</span></span>
+<span id="cb3-21"><a href="#cb3-21"></a><span class="at">        </span><span class="fu">uses</span><span class="kw">:</span><span class="at"> r-lib/actions/setup-r@v2</span></span>
+<span id="cb3-22"><a href="#cb3-22"></a><span class="at">        </span><span class="fu">with</span><span class="kw">:</span></span>
+<span id="cb3-23"><a href="#cb3-23"></a><span class="at">          </span><span class="fu">r-version</span><span class="kw">:</span><span class="at"> </span><span class="st">'4.2.0'</span></span>
+<span id="cb3-24"><a href="#cb3-24"></a><span class="at">          </span><span class="fu">use-public-rspm</span><span class="kw">:</span><span class="at"> </span><span class="ch">true</span></span>
+<span id="cb3-25"><a href="#cb3-25"></a></span>
+<span id="cb3-26"><a href="#cb3-26"></a><span class="at">      </span><span class="kw">-</span><span class="at"> </span><span class="fu">name</span><span class="kw">:</span><span class="at"> Setup renv and install packages</span></span>
+<span id="cb3-27"><a href="#cb3-27"></a><span class="at">        </span><span class="fu">uses</span><span class="kw">:</span><span class="at"> r-lib/actions/setup-renv@v2</span></span>
+<span id="cb3-28"><a href="#cb3-28"></a><span class="at">        </span><span class="fu">with</span><span class="kw">:</span></span>
+<span id="cb3-29"><a href="#cb3-29"></a><span class="at">          </span><span class="fu">cache-version</span><span class="kw">:</span><span class="at"> </span><span class="dv">1</span></span>
+<span id="cb3-30"><a href="#cb3-30"></a><span class="at">        </span><span class="fu">env</span><span class="kw">:</span></span>
+<span id="cb3-31"><a href="#cb3-31"></a><span class="at">          </span><span class="fu">RENV_CONFIG_REPOS_OVERRIDE</span><span class="kw">:</span><span class="at"> https://packagemanager.rstudio.com/all/latest</span></span>
+<span id="cb3-32"><a href="#cb3-32"></a></span>
+<span id="cb3-33"><a href="#cb3-33"></a><span class="at">      </span><span class="kw">-</span><span class="at"> </span><span class="fu">name</span><span class="kw">:</span><span class="at"> Install Python and Dependencies</span></span>
+<span id="cb3-34"><a href="#cb3-34"></a><span class="at">        </span><span class="fu">uses</span><span class="kw">:</span><span class="at"> actions/setup-python@v4</span></span>
+<span id="cb3-35"><a href="#cb3-35"></a><span class="at">        </span><span class="fu">with</span><span class="kw">:</span></span>
+<span id="cb3-36"><a href="#cb3-36"></a><span class="at">          </span><span class="fu">python-version</span><span class="kw">:</span><span class="at"> </span><span class="st">'3.10'</span></span>
+<span id="cb3-37"><a href="#cb3-37"></a><span class="at">          </span><span class="fu">cache</span><span class="kw">:</span><span class="at"> </span><span class="st">'pip'</span></span>
+<span id="cb3-38"><a href="#cb3-38"></a><span class="at">      </span><span class="kw">-</span><span class="at"> </span><span class="fu">run</span><span class="kw">:</span><span class="at"> pip install jupyter</span></span>
+<span id="cb3-39"><a href="#cb3-39"></a><span class="at">      </span><span class="kw">-</span><span class="at"> </span><span class="fu">run</span><span class="kw">:</span><span class="at"> pip install -r requirements.txt</span></span>
+<span id="cb3-40"><a href="#cb3-40"></a></span>
+<span id="cb3-41"><a href="#cb3-41"></a><span class="at">      </span><span class="kw">-</span><span class="at"> </span><span class="fu">name</span><span class="kw">:</span><span class="at"> Render and Publish</span></span>
+<span id="cb3-42"><a href="#cb3-42"></a><span class="at">        </span><span class="fu">uses</span><span class="kw">:</span><span class="at"> quarto-dev/quarto-actions/publish@v2</span></span>
+<span id="cb3-43"><a href="#cb3-43"></a><span class="at">        </span><span class="fu">with</span><span class="kw">:</span></span>
+<span id="cb3-44"><a href="#cb3-44"></a><span class="at">          </span><span class="fu">target</span><span class="kw">:</span><span class="at"> gh-pages</span></span>
+<span id="cb3-45"><a href="#cb3-45"></a><span class="at">        </span><span class="fu">env</span><span class="kw">:</span></span>
+<span id="cb3-46"><a href="#cb3-46"></a><span class="at">          </span><span class="fu">GITHUB_TOKEN</span><span class="kw">:</span><span class="at"> ${{ secrets.GITHUB_TOKEN }}</span></span>
+<span id="cb3-47"><a href="#cb3-47"></a><span class="at">          </span><span class="fu">AWS_ACCESS_KEY_ID</span><span class="kw">:</span><span class="at"> ${{ secrets.AWS_ACCESS_KEY_ID }}</span></span>
+<span id="cb3-48"><a href="#cb3-48"></a><span class="at">          </span><span class="fu">AWS_SECRET_ACCESS_KEY</span><span class="kw">:</span><span class="at"> ${{ secrets.AWS_SECRET_ACCESS_KEY }}</span></span>
+<span id="cb3-49"><a href="#cb3-49"></a><span class="at">          </span><span class="fu">AWS_REGION</span><span class="kw">:</span><span class="at"> us-east-1</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+</div>
+<p>Now, unlike the <code>GITHUB_TOKEN</code> secret, which GitHub Actions automatically provides to itself, we’ll have to provide these secrets to the GitHub interface.</p>
+</section>
+<section id="lab-extensions" class="level3" data-number="7.7.5">
+<h3 data-number="7.7.5" class="anchored" data-anchor-id="lab-extensions"><span class="header-section-number">7.7.5</span> Lab Extensions</h3>
+<p>You might also want to put the actual data you’re using into S3. This can be a great way to separate the data from the project, as recommended in <a href="../sec1/1-2-proj-arch.html">Chapter&nbsp;<span>2</span></a>.</p>
+<p>Putting the data in S3 is such a common pattern that DuckDB allows you to directly interface with parquet files stored in S3.</p>
+
+
+</section>
+</section>
+<section id="footnotes" class="footnotes footnotes-end-of-document" role="doc-endnotes">
+<hr>
+<ol>
+<li id="fn1"><p>Yes, that is a Sound of Music reference.<a href="#fnref1" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
+<li id="fn2"><p>https://www.visualcapitalist.com/aws-powering-the-internet-and-amazons-profits/<a href="#fnref2" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
+<li id="fn3"><p>https://www.statista.com/chart/18819/worldwide-market-share-of-leading-cloud-infrastructure-service-providers/<a href="#fnref3" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
+<li id="fn4"><p>Although these days a huge amount of cloud spending is done via annual pre-commitments. The cloud providers offer big discounts for making an up-front commitment, which the organization then spends down over the course of the year.<a href="#fnref4" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
+<li id="fn5"><p>https://a16z.com/2021/05/27/cost-of-cloud-paradox-market-cap-cloud-lifecycle-scale-growth-repatriation-optimization/<a href="#fnref5" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
+<li id="fn6"><p>There are also some wild services that do specific things, like let you rent you satellite ground station infrastructure or do Internet of Things (IoT) workloads. Those services are really cool, but so far outside the scope of this book that I’m fine with talking like they don’t exist.<a href="#fnref6" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
+<li id="fn7"><p>If you’re planning my birthday party, this is the correct cake configuration.<a href="#fnref7" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
+</ol>
+</section>
+
+</main> <!-- /main -->
+<script id="quarto-html-after-body" type="application/javascript">
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-  <li><a href="#comprehension-questions" id="toc-comprehension-questions" class="nav-link" data-scroll-target="#comprehension-questions"><span class="header-section-number">6.5</span> Comprehension Questions</a></li>
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-<h1 class="title"><span id="sec-cmd-line" class="quarto-section-identifier"><span class="chapter-number">6</span>&nbsp; <span class="chapter-title">Opening the Command Line</span></span></h1>
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-<p>When you want to open a file on your computer or adjust settings, you just click through a file tree or open your preferences pane.</p>
-<p>IT/Admins spend most of their time working with servers, which generally have no <em>graphical user interfaces (GUIs)</em> at all. On a server, interaction is via the command line – an all-text interface where you type commands.</p>
-<p>Even if you’re just a data scientist, it’s worth learning your way around the command line as there are a variety of tasks that are quicker and easier that way. Plus you get to feel like a hacker.</p>
-<p>The command line itself seems like a pretty simple thing. It’s just a blank line where you can tell your computer what to do.</p>
-<p>Pretty soon after getting started on the command line, you’ll realize that some customization is in order. Maybe the colors aren’t quite right, or you want shortcuts for commands you type a lot, or you want more information in the default display.</p>
-<p>You’ll soon find yourself neck deep in Stack Overflow posts on how to customize your <code>.bashrc</code>. Or wait, is it the <code>.zshrc</code>? Or…</p>
-<p>Some people might argue that expending so much energy customizing your command line isn’t the best use of your time.</p>
-<p>Those people are no fun. Having a command line that’s super customized to what you like is awesome and will make you feel super legit.</p>
-<p>This chapter is all about the command line itself – by the end of the chapter, you’ll understand what it is, how to get it open on your machine, and how to customize it to your liking.</p>
-<p>In later chapters we’ll get into how to actually do things there.</p>
-<section id="getting-the-command-line-you-want" class="level2" data-number="6.1">
-<h2 data-number="6.1" class="anchored" data-anchor-id="getting-the-command-line-you-want"><span class="header-section-number">6.1</span> Getting the command line you want</h2>
-<p>The reason customizing your command line is somewhat confusing is that the command line you interact with is actually two or three programs that sit on top of each other. You can mix-and-match options for each of them and configure them in a variety of ways.</p>
-<div class="callout callout-style-default callout-note callout-titled">
-<div class="callout-header d-flex align-content-center">
-<div class="callout-icon-container">
-<i class="callout-icon"></i>
-</div>
-<div class="callout-title-container flex-fill">
-Notes on operating systems
-</div>
-</div>
-<div class="callout-body-container callout-body">
-<p>I’ve been using the command line in MacOS for many years, so I have strong opinions to share in this chapter.</p>
-<p>I haven’t used a Windows machine in many years. I’ve collected some recommendations here, but I can’t personally vouch for them the same way.</p>
-<p>I don’t include recommendations for Linux because Linux desktop users already have strong opinions on these topics and are probably already composing screeds that my opinions are wrong.</p>
-</div>
-</div>
-</section>
-<section id="the-terminal" class="level2" data-number="6.2">
-<h2 data-number="6.2" class="anchored" data-anchor-id="the-terminal"><span class="header-section-number">6.2</span> The terminal</h2>
-<p>The terminal is the GUI where you’ll type in commands. The terminal program you use will dictate the colors and themes available for the window, how tabs and panes work, and the keyboard shortcuts you’ll use to manage them.</p>
-<p>Some programs you might use, like RStudio or VSCode have terminals built into them. If you do basically all your terminal work from one of these environments, you may not need another. But it can often be nice to have a standalone terminal program you like.</p>
-<div class="tabset-margin-container"></div><div class="panel-tabset">
-<ul class="nav nav-tabs" role="tablist"><li class="nav-item" role="presentation"><a class="nav-link active" id="tabset-1-1-tab" data-bs-toggle="tab" data-bs-target="#tabset-1-1" role="tab" aria-controls="tabset-1-1" aria-selected="true" aria-current="page">MacOS</a></li><li class="nav-item" role="presentation"><a class="nav-link" id="tabset-1-2-tab" data-bs-toggle="tab" data-bs-target="#tabset-1-2" role="tab" aria-controls="tabset-1-2" aria-selected="false">Windows</a></li></ul>
-<div class="tab-content">
-<div id="tabset-1-1" class="tab-pane active" role="tabpanel" aria-labelledby="tabset-1-1-tab">
-<p>I’d recommend against using the built-in terminal app (called <em>Terminal</em>). It’s fine, but there are better options.</p>
-<p>My personal favorite is the free <a href="https://iterm2.com/"><em>iTerm2</em></a>, which adds a bunch of niceties like better theming and multiple tabs.</p>
-</div>
-<div id="tabset-1-2" class="tab-pane" role="tabpanel" aria-labelledby="tabset-1-2-tab">
-<p>The built-in terminal is the favorite of many users. There are a variety of alternatives you can try, but feel free to stick with the default.</p>
-</div>
-</div>
-</div>
-</section>
-<section id="the-shell" class="level2" data-number="6.3">
-<h2 data-number="6.3" class="anchored" data-anchor-id="the-shell"><span class="header-section-number">6.3</span> The shell</h2>
-<p>The shell is the program that takes the commands you’re typing and runs them. It’s what matches the words you type to actual commands or programs on your system. Depending on which shell you choose, you’ll get different options for plugins and themes.</p>
-<p>The shell runs anywhere you’ve got a running operating system. So your computer has one shell, your server would have a different one. Even a Docker Container has a shell available. That means that if you do a lot of work on a server, you may need to configure your shell twice – once locally and once on the server.</p>
-<div class="tabset-margin-container"></div><div class="panel-tabset">
-<ul class="nav nav-tabs" role="tablist"><li class="nav-item" role="presentation"><a class="nav-link active" id="tabset-2-1-tab" data-bs-toggle="tab" data-bs-target="#tabset-2-1" role="tab" aria-controls="tabset-2-1" aria-selected="true">MacOS</a></li><li class="nav-item" role="presentation"><a class="nav-link" id="tabset-2-2-tab" data-bs-toggle="tab" data-bs-target="#tabset-2-2" role="tab" aria-controls="tabset-2-2" aria-selected="false">Windows</a></li></ul>
-<div class="tab-content">
-<div id="tabset-2-1" class="tab-pane active" role="tabpanel" aria-labelledby="tabset-2-1-tab">
-<p>The default shell for MacOS (and Linux) is called <em>bash</em>. I’d advise you to switch it out for <em>zsh</em>, which is the most popular <em>bash alternative</em>.<a href="#fn1" class="footnote-ref" id="fnref1" role="doc-noteref"><sup>1</sup></a></p>
-<p>Relative to bash, zsh has a few advantages out of the box, like better auto-completion. It also has a huge ecosystem of themes to enhance visual appeal and functionality, and plugins that let your command line do everything from displaying your git status to controlling your Spotify playlist.</p>
-<p>All so-called bash alternatives are just bash with some extra bells and whistles, so they’re very similar. So if you log into a server that’s running bash rather than zsh, you might be annoyed that some of your shortcuts don’t work, but you won’t be lost.</p>
-<p>I’d recommend looking up instructions for how to install zsh using <em>Homebrew</em>, which you should also install if you haven’t already.</p>
-</div>
-<div id="tabset-2-2" class="tab-pane" role="tabpanel" aria-labelledby="tabset-2-2-tab">
-<p>Windows comes with two shells built in, the <em>Command Shell</em> (<code>cmd</code>) and the <em>PowerShell</em>.</p>
-<p>The Command Shell is older and has been superseded by PowerShell. If you’re just getting started, you absolutely should just work with PowerShell. If you’ve been using Command Shell on a Windows machine for a long time, most Command Shell commands work in PowerShell, so it may be worth switching over.</p>
-</div>
-</div>
-</div>
-</section>
-<section id="make-it-look-and-work-great" class="level2" data-number="6.4">
-<h2 data-number="6.4" class="anchored" data-anchor-id="make-it-look-and-work-great"><span class="header-section-number">6.4</span> Make it look and work great</h2>
-<p>Now that you’ve got your shell and terminal installed, let’s get it customized just for you. It is possible to directly customize both zsh and PowerShell. In most cases, you’ll want to use a configuration manager to manage your themes and plugins.</p>
-<div class="tabset-margin-container"></div><div class="panel-tabset">
-<ul class="nav nav-tabs" role="tablist"><li class="nav-item" role="presentation"><a class="nav-link active" id="tabset-3-1-tab" data-bs-toggle="tab" data-bs-target="#tabset-3-1" role="tab" aria-controls="tabset-3-1" aria-selected="true">MacOS</a></li><li class="nav-item" role="presentation"><a class="nav-link" id="tabset-3-2-tab" data-bs-toggle="tab" data-bs-target="#tabset-3-2" role="tab" aria-controls="tabset-3-2" aria-selected="false">Windows</a></li></ul>
-<div class="tab-content">
-<div id="tabset-3-1" class="tab-pane active" role="tabpanel" aria-labelledby="tabset-3-1-tab">
-<p><em>Prezto</em> is my favorite configuration and plugin manager for zsh. <em>OhMyZsh</em> is popular and also very good. Feel free to choose either – but you can only use one.</p>
-<p>Once you’ve installed Prezto, you’ve got (at least) three different places you could configure your command line – iTerm2 preferences, <code>.zshrc</code>, and <code>.zpreztorc</code>. I’d recommend leaving <code>.zshrc</code> alone, customizing the look of the window and the tab behavior in the iTerm2 preferences, and customizing the text theme and plugins via prezto in the <code>.zpreztorc</code> file.</p>
-<p>I tend to be a pretty light on customizations, but I’d recommend looking into git plugins and some of the advanced auto-completion and command history search functionality.</p>
-</div>
-<div id="tabset-3-2" class="tab-pane" role="tabpanel" aria-labelledby="tabset-3-2-tab">
-<p>Many people like customizing PowerShell with <a href="https://ohmyposh.dev/"><em>Oh My Posh</em></a>.</p>
-</div>
-</div>
-</div>
-</section>
-<section id="comprehension-questions" class="level2" data-number="6.5">
-<h2 data-number="6.5" class="anchored" data-anchor-id="comprehension-questions"><span class="header-section-number">6.5</span> Comprehension Questions</h2>
-<ol type="1">
-<li>Draw a mental map that includes the following: terminal, shell, theme manager, operating system, my laptop</li>
-</ol>
-
-
-</section>
-<section id="footnotes" class="footnotes footnotes-end-of-document" role="doc-endnotes">
-<hr>
-<ol>
-<li id="fn1"><p>zsh is pronounced by just speaking the letters aloud, <em>zee-ess-aitch</em>. Some people might disagree and say it’s <em>zeesh</em>, but they’re not writing this book, are they?<a href="#fnref1" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
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-  <li><a href="#cheat-cli" id="toc-cheat-cli" class="nav-link" data-scroll-target="#cheat-cli"><span class="header-section-number">7.8</span> Cheatsheet: Command Line</a>
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-  <li><a href="#general-command-line" id="toc-general-command-line" class="nav-link" data-scroll-target="#general-command-line"><span class="header-section-number">7.8.1</span> General Command Line</a></li>
-  <li><a href="#linux-navigation" id="toc-linux-navigation" class="nav-link" data-scroll-target="#linux-navigation"><span class="header-section-number">7.8.2</span> Linux Navigation</a></li>
-  <li><a href="#reading-text-files-1" id="toc-reading-text-files-1" class="nav-link" data-scroll-target="#reading-text-files-1"><span class="header-section-number">7.8.3</span> Reading Text Files</a></li>
-  <li><a href="#manipulating-files" id="toc-manipulating-files" class="nav-link" data-scroll-target="#manipulating-files"><span class="header-section-number">7.8.4</span> Manipulating Files</a></li>
-  <li><a href="#move-things-tofrom-server" id="toc-move-things-tofrom-server" class="nav-link" data-scroll-target="#move-things-tofrom-server"><span class="header-section-number">7.8.5</span> Move things to/from server</a></li>
-  <li><a href="#write-files-from-the-command-line" id="toc-write-files-from-the-command-line" class="nav-link" data-scroll-target="#write-files-from-the-command-line"><span class="header-section-number">7.8.6</span> Write files from the command line</a></li>
-  <li><a href="#command-line-text-editors-vim-nano" id="toc-command-line-text-editors-vim-nano" class="nav-link" data-scroll-target="#command-line-text-editors-vim-nano"><span class="header-section-number">7.8.7</span> Command Line Text Editors (Vim + Nano)</a></li>
-  </ul></li>
-  </ul>
-<div class="toc-actions"><div><i class="bi bi-github"></i></div><div class="action-links"><p><a href="https://github.com/akgold/do4ds/edit/main/chapters/sec2/2-2-cmd-line-use.qmd" class="toc-action">Edit this page</a></p></div></div></nav>
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-<h1 class="title"><span id="sec-cmd-line-use" class="quarto-section-identifier"><span class="chapter-number">7</span>&nbsp; <span class="chapter-title">Using the Command Line</span></span></h1>
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-<p>If you’ve never worked much on the command line, it takes some getting used to. You have no mouse or keyboard to work with – all you’ve got is written commands.</p>
-<p>The good news is that the command line is conceptually pretty simple. You’ve got directories you can traverse, files that you can read, move, or edit, and settings you can change. That’s pretty much it.</p>
-<p>In this chapter, we’ll spend some time on how a bash command works (or zsh or ksh or fish – they’re all the same) and then get into how to do common tasks on the command line including looking at directories and files, and reading, moving, and writing files.</p>
-<p>If you just want reference materials, there’s a <a href="#cheat-cli">cheatsheet</a> with all the content at the end of the chapter.</p>
-<section id="using-bash" class="level2" data-number="7.1">
-<h2 data-number="7.1" class="anchored" data-anchor-id="using-bash"><span class="header-section-number">7.1</span> Using bash</h2>
-<p>The philosophy behind bash and its derivatives says that you should be able to accomplish anything you want with small programs invoked via a <em>bash</em> <em>command</em>. Each command should do just one thing, and complicated things should be accomplished by <em>composing</em> commands – taking the output from one as the input to the next.</p>
-<div class="callout callout-style-default callout-note callout-titled">
-<div class="callout-header d-flex align-content-center">
-<div class="callout-icon-container">
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-Note
-</div>
-</div>
-<div class="callout-body-container callout-body">
-<p>I’m mostly targeting using Linux servers in this chapter, so you won’t see much about Windows PowerShell commands in this chapter. If you have a Windows machine and you want to use bash, you can with the increasingly powerful <em>Windows Subsystem for Linux (WSL)</em>.</p>
-</div>
-</div>
-<p>Calling a command is as simple as typing the command on the command line and hitting <code>enter</code>.</p>
-<p>Helpfully, most bash commands are an abbreviation of the word for what the command does. Unhelpfully, the letters often seem somewhat random. For example, the command to <em>list</em> the contents of a directory is <code>ls</code>, which sorta makes sense. Over time the commands you use frequently will become second hand.</p>
-<p>Bash commands can be modified with <em>command arguments</em>, <em>flags</em>, and <em>flag arguments</em>. Bash commands are always formatted as <code>&lt;command&gt; &lt;flags + flag args&gt; &lt;command args&gt;</code>. It’s nice that this structure is standard. The downside is that having the main argument come all the way at the end, after all the flags, can make it hard to mentally parse commands.</p>
-<p>Command arguments provide details to the command. They come after the command with a space in between. For example, if I want to run <code>ls</code> on the directory <code>/home/alex</code>, I can run <code>ls /home/alex</code> on the command line.</p>
-<p>Some commands have default arguments. For example the default argument for the <code>ls</code> command is the current directory. So if I’m in <code>/home/alex</code>, I’d get the same thing from either <code>ls</code> or <code>ls /home/alex</code>.</p>
-<p>Options or flags modify how the command operates and come between the command and arguments. Flags are denoted by having one or more dashes before them. For example, <code>ls</code> allows the <code>-l</code> flag, which displays the output as a list. So, <code>ls -l /home/alex</code> would get the files in <code>/home/alex</code> as a list.</p>
-<p>Some flags themselves have arguments. For example, the <code>-D</code> flag allows specifying a format for how the datetime is displayed from <code>ls -l</code>. So running <code>ls -l -D %Y-%m-%dT%H:%M:%S /home/alex</code> lists all the files in <code>/home/alex</code> with the date-time of the last update formatted in <em>ISO-8601</em> format, which is always the correct format for dates.</p>
-<p>Because there can be so many arguments and flags, bash commands can get long. It’s often nice to include one flag or argument per line to make it more readable. You can tell bash you want it to keep reading after a line break by ending the line with a space and a <code>\</code>.</p>
-<p>For example, here’s that long <code>ls</code> command more nicely formatted:</p>
-<div class="code-with-filename">
-<div class="code-with-filename-file">
-<pre><strong>Terminal</strong></pre>
-</div>
-<div class="sourceCode" id="cb1"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb1-1"><a href="#cb1-1"></a><span class="op">&gt;</span> ls <span class="ex">-l</span> <span class="dt">\</span></span>
-<span id="cb1-2"><a href="#cb1-2"></a>  <span class="at">-D</span> %Y-%m-%dT%H:%M:%S <span class="dt">\</span></span>
-<span id="cb1-3"><a href="#cb1-3"></a>  /home/alex</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-</div>
-<p>There is also help available!</p>
-<p>All of the flags and arguments for commands can be found in the program’s <em>man page</em> (short for manual). You can access the man page for any command with <code>man &lt;command&gt;</code>. You can scroll the man page with arrow keys and exit with <code>q</code>.</p>
-<p>If you ever can’t figure out how to quit, <code>ctrl + c</code> will quit from most command line situations.</p>
-<p>For the most part, you’ll write commands directly on the command line. It’s also possible to write and run bash scripts, which usually end in <code>.sh</code>. The advantage of writing bash scripts is that they can run basically anywhere. The disadvantage is that the ergonomics of scripting bash are terrible, but sometimes it’s worth it.</p>
-</section>
-<section id="file-paths" class="level2" data-number="7.2">
-<h2 data-number="7.2" class="anchored" data-anchor-id="file-paths"><span class="header-section-number">7.2</span> File paths</h2>
-<p>You’re probably used to clicking around your computer’s filesystem to find files and folders. On the command line, you have to traverse the filesystem via written commands, so getting comfortable reading and writing file paths is important.</p>
-<div class="callout callout-style-default callout-note callout-titled">
-<div class="callout-header d-flex align-content-center">
-<div class="callout-icon-container">
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-Note
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-<div class="callout-body-container callout-body">
-<p>Since this chapter is just on tooling, I’m skipping a lot of background about the filesystem and how it’s structured.</p>
-<p>You’ll find that material in <a href="../sec3/3-2-linux-admin.html">Chapter&nbsp;<span>11</span></a> on Linux Administration.</p>
-</div>
-</div>
-<p>Whenever you’re on the command line, you are at a particular place in the filesystem called the <em>working directory</em>. File paths can be <em>absolute</em> so they operate the same irrespective of the current working directory. An absolute file path is easy to recognize because it starts with <code>/</code>.</p>
-<p>You can also use a <em>relative</em> file path, which starts at the current working directory, <code>.</code></p>
-<p>Depending on what you’re doing, absolute or relative paths might make more sense. Absolute file paths are useful when you want to access the same resource regardless of where a command is run, and relative file paths make more sense when you want the command to be contextual to the working directory.</p>
-<p>The working directory’s parent is at <code>..</code>. So, for example, you could see everything in the parent directory of your current working directory with <code>ls ..</code> or its parent with <code>ls ../..</code>. The users’s home directory is always easily accessible at <code>~</code>.</p>
-<p>You can get the full path to your working directory with the <code>pwd</code> command, which is an abbreviation for <em>print working directory</em>.</p>
-<p>Along with being able to inspect directories, it’s useful to be able to change your working directory with the <code>cd</code> command, short for <em>change directory</em>. You can use either absolute or relative file paths with <code>cd</code>. So if you were in <code>/home/alex</code> and wanted to navigate to <code>/home</code>, either <code>cd ..</code> or <code>cd /home</code> would work.</p>
-<p>Some files or directories are <em>hidden</em> so they don’t appear in a normal <code>ls</code>. You know a file or directory is hidden because its name starts with <code>.</code>. Hidden files are usually configuration files that you aren’t manipulating in normal usage. These aren’t secret or protected in any way, they’re just skipped by <code>ls</code> for convenience.</p>
-<p>You’ve already seen a couple in this book – your GitHub Action was configured in the <code>.github</code> directory and your Prezto configuration was done in the <code>.zpreztorc</code> file. You might also be familiar with <code>.gitignore</code>, <code>.Rprofile</code>, and <code>.Renviron</code>. If you want to display hidden files in a directory, you can use the <code>-a</code> flag (for all) with <code>ls</code>.</p>
-</section>
-<section id="reading-text-files" class="level2" data-number="7.3">
-<h2 data-number="7.3" class="anchored" data-anchor-id="reading-text-files"><span class="header-section-number">7.3</span> Reading text files</h2>
-<p>On a server, a huge fraction of what you’ll be doing is reading configuration and log files from the server, so being comfortable with the commands to do so is essential.</p>
-<p>There are a few different commands I frequently use for reading files:</p>
-<ul>
-<li><p><code>cat</code> is the basic command to print a file, starting at the beginning.</p></li>
-<li><p><code>less</code> prints a file, starting at the beginning, but only a few lines at a time.</p></li>
-<li><p><code>head</code> prints only the first few lines and exits. It is especially useful to peer at the beginning of a large file, like a <code>csv</code> file – so you can quickly preview the column heads and the first few values.</p></li>
-<li><p><code>tail</code> prints a file going up from the end. This is especially useful for log files, as the newest logs are appended to the end of a file. This is such a common practice that “tailing a log file” is a common phrase.</p>
-<ul>
-<li>Sometimes, you’ll want to use the <code>-f</code> flag (for <em>follow</em>) to tail a file with a live view as it updates.</li>
-</ul></li>
-</ul>
-<p>Sometimes you want to search around inside a text file. You’re probably familiar with the power of <em>regular expressions (regex)</em> to search for specific character sequences in text strings. The Linux command <code>grep</code> is the main regex command.</p>
-<p>In addition to searching in text files, <code>grep</code> is often useful in combination with other commands. For example, it’s often useful to put the output of <code>ls</code> into <code>grep</code> to search for a particular file in a big directory.</p>
-<p>The Linux <em>pipe operator</em>, <code>|</code>, takes the output of the previous command and sends it into the next one. So if I was searching for a file whose name contained the word <code>data</code>, that might look something like <code>ls ~/projects/my-project | grep data</code>.</p>
-<div class="callout callout-style-default callout-note callout-titled">
-<div class="callout-header d-flex align-content-center">
-<div class="callout-icon-container">
-<i class="callout-icon"></i>
-</div>
-<div class="callout-title-container flex-fill">
-Ceci n’est pas une pipe?
-</div>
-</div>
-<div class="callout-body-container callout-body">
-<p>The pipe should feel extremely familiar to R users.</p>
-<p>The pipe from the <code>{magrittr}</code> package, <code>%&gt;%</code>, was introduced in 2013, and is a popular part of the <code>{tidyverse}</code>.<a href="#fn1" class="footnote-ref" id="fnref1" role="doc-noteref"><sup>1</sup></a> The <code>{magrittr}</code> pipe was inspired by both the Unix (Linux) pipe and the pipe operator in the <code>F#</code> programming language.</p>
-<p>Due to its popularity, the pipe <code>|&gt;</code> was formally added to the base R language in R 4.1 in 2021.</p>
-</div>
-</div>
-</section>
-<section id="manipulating-files-and-directories" class="level2" data-number="7.4">
-<h2 data-number="7.4" class="anchored" data-anchor-id="manipulating-files-and-directories"><span class="header-section-number">7.4</span> Manipulating files and directories</h2>
-<p>You’ll often need to manipulate files and directories. Here’s how.</p>
-<p>You can copy a file or directory from one place to another using the <code>cp</code> command. <code>cp</code> leaves behind the old file or directory and adds the new one at the specified location. You can use the <code>-r</code> flag to recursively copy everything in a directory.</p>
-<p>You can move a file with the <code>mv</code> command, which does not leave the old file behind.</p>
-<p>If you want to remove a file entirely, you can use the <code>rm</code> command. There is also a version to remove a directory, <code>rmdir</code>.</p>
-<div class="callout callout-style-default callout-warning callout-titled">
-<div class="callout-header d-flex align-content-center">
-<div class="callout-icon-container">
-<i class="callout-icon"></i>
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-<div class="callout-title-container flex-fill">
-Warning
-</div>
-</div>
-<div class="callout-body-container callout-body">
-<p>Be very careful with the <code>rm</code> command.</p>
-<p>Unlike on your desktop there’s no recycle bin! Things that are deleted are instantly deleted forever.</p>
-</div>
-</div>
-<p>If you want to make a directory, <code>mkdir</code> makes a directory. <code>mkdir</code> gets mad if it’s not creating the whole file path, so the <code>-p</code> flag can be handy to create only the parts of the path that don’t exist.</p>
-<p>Sometimes it’s useful to operate on every file inside a directory. You can get every file that matches a pattern with the wildcard, <code>*</code>. You can also do partial matching with the wildcard to get all the files that match part of a pattern.</p>
-<p>For example, let’s say I have a <code>/data</code> directory and I want to put a copy of only the <code>.csv</code> files inside into a new <code>data-copy</code> sub-directory. I could do the following:</p>
-<pre><code>&gt; mkdir -p /data/data-copy
-&gt; cp /data/*.csv /data/data-copy</code></pre>
-</section>
-<section id="moving-things-to-and-from-the-server" class="level2" data-number="7.5">
-<h2 data-number="7.5" class="anchored" data-anchor-id="moving-things-to-and-from-the-server"><span class="header-section-number">7.5</span> Moving things to and from the server</h2>
-<p>It’s very common to have a file on your server you want to move to your desktop or vice versa.</p>
-<p>If you’re moving multiple files, it’s easier to combine them into a single object and move that.</p>
-<p>The <code>tar</code> command turns a set of files or whole directory into a single archive file, usually with the file suffix <code>.tar.gz</code>. Creating an archive also does some compression. The amount depends on the content.</p>
-<p>In my opinion, <code>tar</code> is a rare failure of bash to provide standalone commands for anything you need to do. <code>tar</code> is used to both create and unpack (extract) archive files. Telling it which one requires the use of several flags. You’ll basically never use <code>tar</code> without a bunch of flags and the incantation is hard to remember. I google it every time I use it. The flags you’ll use most often are in the cheatsheet below.</p>
-<p>Once you’ve created an archive file, you can move it to or from a server with the <code>scp</code> command. <code>scp</code> – short for secure copy – is basically <code>cp</code>, but with an SSH connection in the middle.<a href="#fn2" class="footnote-ref" id="fnref2" role="doc-noteref"><sup>2</sup></a></p>
-<p>Since <code>scp</code> establishes an SSH connection, you need to make the request to somewhere that is accepting SSH connections. Since your server is probably accepting SSH connections and your laptop probably (hopefully) is not. That means that whether you’re copying something to or from a server, you’ll run <code>scp</code> from a regular terminal on your laptop, not one that’s already SSH-ed into your server.</p>
-<p>Regular <code>ssh</code> options work with <code>scp</code>, like <code>-i</code> and <code>-v</code>.</p>
-</section>
-<section id="writing-text-files" class="level2" data-number="7.6">
-<h2 data-number="7.6" class="anchored" data-anchor-id="writing-text-files"><span class="header-section-number">7.6</span> Writing text files</h2>
-<p>There will be many situations where writing into a text file will be handy. There are several ways to write into a text file without opening it to edit.</p>
-<p>You may have some preexisting text you want to add to a file. You can do this with the <code>&gt;</code> command, which takes the output of a command on the left and writes it as a file. If the file you specify already exists, it will be overwritten. If you want to append the new text, rather than overwrite, <code>&gt;&gt;</code> appends to the end of the file.</p>
-<p>A common reason you might want to do this is to add something to the end of your <code>.gitignore</code>. For example, if you want to add your <code>.Rprofile</code> file to your <code>.gitignore</code>, you could do that with <code>echo .Rprofile &gt;&gt; .gitignore</code>. Note that <code>echo</code> is a command that just repeats the input as a character string. Otherwise <code>.Rprofile</code> would be treated as a command.</p>
-<p>There are times when you want to make files or directories with nothing in them. The <code>touch</code> command makes a blank file at the specified file path. If you <code>touch</code> a preexisting file, it updates the time the file was last updated without actually making any changes.</p>
-<section id="text-editors---vim-and-nano" class="level3" data-number="7.6.1">
-<h3 data-number="7.6.1" class="anchored" data-anchor-id="text-editors---vim-and-nano"><span class="header-section-number">7.6.1</span> Text editors - vim and nano</h3>
-<p>There are two command line text editors you’ll probably encounter: <code>nano</code> and <code>vi</code>/<code>vim</code>.<a href="#fn3" class="footnote-ref" id="fnref3" role="doc-noteref"><sup>3</sup></a> While they’re both powerful text editing tools, they can also be intimidating if you’ve never used them before.</p>
-<p>You can open a file in either by typing <code>nano &lt;filename&gt;</code> or <code>vi &lt;filename&gt;</code>.</p>
-<p>At this point many newbie command line users find themselves completely stuck, unable to do anything – even just exit and try again. But don’t worry, there’s a way out of this labyrinth!</p>
-<p>In <code>nano</code> there will be some helpful-looking prompts at the bottom. You’ll see that once you’re ready to go, you can exit with <code>^x</code>. But you’ll find yourself stymied when you try to exit with the caret character, <code>^</code>, and an <code>x</code>.</p>
-<p>Never fear. On Windows, <code>^</code> is short for <code>Ctrl</code> and on Mac it’s for Command (<code>⌘</code>), so <code>Ctrl + x</code> or <code>⌘ + x</code> will exit.</p>
-<p>Where <code>nano</code> gives you helpful – if obscure – hints, a first experience in <code>vim</code> is the stuff of command line nightmares. Typed words don’t appear in your on the screen, but instead cause dizzying jumps around the page and words and lines of text disappear without a trace.</p>
-<p>This is all because you always enter <code>vim</code> in the (poorly named) <em>normal mode</em> where you use the letter keys to navigate, type, and interact with <code>vim</code> itself. Normal mode exists because <code>vim</code> was created before keyboards uniformly had arrow keys. These days, <code>vim</code> still operates this way because people are used to it and because it minimizes how much your hands have to move on the keyboard.</p>
-<p>While I’ve never felt taxed from using the arrow keys, <code>vim</code> keybindings are worth spending some time learning. <code>vim</code> includes some powerful shortcuts for moving within and between lines and selecting and editing text. Most IDEs you might use, including RStudio, JupyterLab, and VSCode have vim modes. Learning some of the basics can make you way faster editing code files, plus you’ll feel really cool.</p>
-<p>Here I’m only going to teach you how to make changes, save, and exit without issue.</p>
-<p>When you’re in normal mode, pressing the <code>i</code> key activates <em>insert mode</em>, which will feel normal for those of us used to arrow keys. You can type and words will appear and you can navigate with the arrow keys.</p>
-<p>Now that you’ve figured out how to exit normal mode, you may wish never to return. But it’s the only way to save files and exit <code>vim</code>. You can do so with the <code>escape</code> key.</p>
-<p>In order to do file operations, you type a colon, <code>:</code>, followed by the shortcut for what you want to do, and <code>enter</code>. The two most common commands you’ll use are save (write) with <code>w</code> and quit with <code>q</code>. You can combine these together, so you can save and quit in one command using <code>:wq</code>.</p>
-<p>Sometimes you may want to exit without saving. If you’ve made changes and try to exit with <code>:q</code>, you’ll find yourself in an endless loop of warnings that your changes won’t be saved. You can tell <code>vim</code> you mean it with the exclamation mark, <code>!</code>, and exit using <code>:q!</code>.</p>
-</section>
-</section>
-<section id="comprehension-questions" class="level2" data-number="7.7">
-<h2 data-number="7.7" class="anchored" data-anchor-id="comprehension-questions"><span class="header-section-number">7.7</span> Comprehension Questions</h2>
-<ol type="1">
-<li>What are the parts of a bash command?</li>
-<li>Where do commands run? How do you know where they’re going to run or specify a relative path?</li>
-<li>What are 4 commands to read text files?</li>
-<li>How can you copy, move, or delete a file? What about to or from a server?</li>
-<li>How do you know if you’ve opened <code>nano</code> or <code>vim</code>? How would you exit in either case?</li>
-</ol>
-</section>
-<section id="cheat-cli" class="level2" data-number="7.8">
-<h2 data-number="7.8" class="anchored" data-anchor-id="cheat-cli"><span class="header-section-number">7.8</span> Cheatsheet: Command Line</h2>
-<section id="general-command-line" class="level3" data-number="7.8.1">
-<h3 data-number="7.8.1" class="anchored" data-anchor-id="general-command-line"><span class="header-section-number">7.8.1</span> General Command Line</h3>
-<table class="table">
-<colgroup>
-<col style="width: 23%">
-<col style="width: 65%">
-</colgroup>
-<thead>
-<tr class="header">
-<th>Symbol</th>
-<th>What it is</th>
-</tr>
-</thead>
-<tbody>
-<tr class="odd">
-<td><code>man &lt;command&gt;</code></td>
-<td>Open manual for <code>command</code></td>
-</tr>
-<tr class="even">
-<td><code>q</code></td>
-<td>Quit the current screen</td>
-</tr>
-<tr class="odd">
-<td><code>\</code></td>
-<td>Continue bash command on new line</td>
-</tr>
-<tr class="even">
-<td><code>ctrl + c</code></td>
-<td>Quit current execution</td>
-</tr>
-</tbody>
-</table>
-</section>
-<section id="linux-navigation" class="level3" data-number="7.8.2">
-<h3 data-number="7.8.2" class="anchored" data-anchor-id="linux-navigation"><span class="header-section-number">7.8.2</span> Linux Navigation</h3>
-<table class="table">
-<colgroup>
-<col style="width: 23%">
-<col style="width: 33%">
-<col style="width: 38%">
-</colgroup>
-<thead>
-<tr class="header">
-<th>Command</th>
-<th>What it does/is</th>
-<th>Notes + Helpful options</th>
-</tr>
-</thead>
-<tbody>
-<tr class="odd">
-<td><code>/</code></td>
-<td>System root or file path separator</td>
-<td></td>
-</tr>
-<tr class="even">
-<td><code>.</code></td>
-<td>current working directory</td>
-<td></td>
-</tr>
-<tr class="odd">
-<td><code>..</code></td>
-<td>Parent of working directory</td>
-<td></td>
-</tr>
-<tr class="even">
-<td><code>~</code></td>
-<td>Home directory of the current user</td>
-<td></td>
-</tr>
-<tr class="odd">
-<td><code>ls &lt;dir&gt;</code></td>
-<td>List objects in a directory</td>
-<td><p><code>-l</code> - format as list</p>
-<p><code>-a</code> - all (include hidden files that start with <code>.</code>)</p></td>
-</tr>
-<tr class="even">
-<td><code>pwd</code></td>
-<td>Print working directory</td>
-<td></td>
-</tr>
-<tr class="odd">
-<td><code>cd &lt;dir&gt;</code></td>
-<td>Change directory</td>
-<td>Can use relative or absolute paths</td>
-</tr>
-</tbody>
-</table>
-</section>
-<section id="reading-text-files-1" class="level3" data-number="7.8.3">
-<h3 data-number="7.8.3" class="anchored" data-anchor-id="reading-text-files-1"><span class="header-section-number">7.8.3</span> Reading Text Files</h3>
-<table class="table">
-<colgroup>
-<col style="width: 26%">
-<col style="width: 33%">
-<col style="width: 33%">
-</colgroup>
-<thead>
-<tr class="header">
-<th>Command</th>
-<th>What it does</th>
-<th>Notes + Helpful options</th>
-</tr>
-</thead>
-<tbody>
-<tr class="odd">
-<td><code>cat &lt;file&gt;</code></td>
-<td>Print a file from the top.</td>
-<td></td>
-</tr>
-<tr class="even">
-<td><code>less &lt;file&gt;</code></td>
-<td>Print a file, but just a little.</td>
-<td><p>Can be very helpful to look at a few rows of csv.</p>
-<p>Lazily reads lines, so can be <em>much</em> faster than <code>cat</code> for big files.</p></td>
-</tr>
-<tr class="odd">
-<td><code>head &lt;file&gt;</code></td>
-<td>Look at the beginning of a file.</td>
-<td>Defaults to 10 lines, can specify a different number with <code>-n &lt;n&gt;</code>.</td>
-</tr>
-<tr class="even">
-<td><code>tail &lt;file&gt;</code></td>
-<td>Look at the end of a file.</td>
-<td><p>Useful for logs where the newest part is last.</p>
-<p>The <code>-f</code> flag is useful to follow for a live view.</p></td>
-</tr>
-<tr class="odd">
-<td><code>gr ep &lt;expression&gt;</code></td>
-<td>Search a file using regex.</td>
-<td><p>Writing regex can be a pain. I suggest testing expressions on regex101.com.</p>
-<p>Often useful in combination with the pipe.</p></td>
-</tr>
-<tr class="even">
-<td><code>|</code></td>
-<td>The pipe</td>
-<td></td>
-</tr>
-</tbody>
-</table>
-</section>
-<section id="manipulating-files" class="level3" data-number="7.8.4">
-<h3 data-number="7.8.4" class="anchored" data-anchor-id="manipulating-files"><span class="header-section-number">7.8.4</span> Manipulating Files</h3>
-<table class="table">
-<colgroup>
-<col style="width: 23%">
-<col style="width: 23%">
-<col style="width: 44%">
-</colgroup>
-<thead>
-<tr class="header">
-<th>Command</th>
-<th>What it does/is</th>
-<th>Notes + Helpful Options</th>
-</tr>
-</thead>
-<tbody>
-<tr class="odd">
-<td><code>rm &lt;path&gt;</code></td>
-<td>Remove</td>
-<td><p><code>-r</code> - recursively remove everything below a file path</p>
-<p><code>-f</code> - force - don’t ask for each file</p>
-<p><strong>Be very careful, it’s permanent</strong></p></td>
-</tr>
-<tr class="even">
-<td><code>c p &lt;from&gt; &lt;to&gt;</code></td>
-<td>Copy</td>
-<td></td>
-</tr>
-<tr class="odd">
-<td><code>m v &lt;from&gt; &lt;to&gt;</code></td>
-<td>Move</td>
-<td></td>
-</tr>
-<tr class="even">
-<td><code>*</code></td>
-<td>Wildcard</td>
-<td></td>
-</tr>
-<tr class="odd">
-<td><code>mkdir</code>/<code>rmdir</code></td>
-<td>Make/remove directory</td>
-<td><code>-p</code> - create any parts of path that don’t exist</td>
-</tr>
-</tbody>
-</table>
-</section>
-<section id="move-things-tofrom-server" class="level3" data-number="7.8.5">
-<h3 data-number="7.8.5" class="anchored" data-anchor-id="move-things-tofrom-server"><span class="header-section-number">7.8.5</span> Move things to/from server</h3>
-<table class="table">
-<colgroup>
-<col style="width: 23%">
-<col style="width: 23%">
-<col style="width: 37%">
-</colgroup>
-<thead>
-<tr class="header">
-<th>Command</th>
-<th>What it does</th>
-<th>Notes + Helpful options</th>
-</tr>
-</thead>
-<tbody>
-<tr class="odd">
-<td><code>tar</code></td>
-<td>Create/extract archive file</td>
-<td><p>Almost always used with flags.</p>
-<p>Create is usually</p>
-<p><code>tar -czf &lt; archive name&gt; &lt;file(s)&gt;</code></p>
-<p>Extract is usually</p>
-<p><code>tar -xfv &lt;archive name&gt;</code></p></td>
-</tr>
-<tr class="even">
-<td><code>scp</code></td>
-<td>Secure copy via <code>ssh</code></td>
-<td><p>Run on laptop to server</p>
-<p>Can use most <code>ssh</code> flags (like <code>-i</code> and <code>-v</code>)</p></td>
-</tr>
-</tbody>
-</table>
-</section>
-<section id="write-files-from-the-command-line" class="level3" data-number="7.8.6">
-<h3 data-number="7.8.6" class="anchored" data-anchor-id="write-files-from-the-command-line"><span class="header-section-number">7.8.6</span> Write files from the command line</h3>
-<table class="table">
-<colgroup>
-<col style="width: 23%">
-<col style="width: 23%">
-<col style="width: 36%">
-</colgroup>
-<thead>
-<tr class="header">
-<th>Command</th>
-<th>What it does</th>
-<th>Notes</th>
-</tr>
-</thead>
-<tbody>
-<tr class="odd">
-<td><code>touch</code></td>
-<td>Creates file if doesn’t already exist.</td>
-<td>Updates last updated to current time if it does exist.</td>
-</tr>
-<tr class="even">
-<td><code>&gt;</code></td>
-<td>Overwrite file contents</td>
-<td>Creates a new file if it doesn’t exist</td>
-</tr>
-<tr class="odd">
-<td><code>&gt;&gt;</code></td>
-<td>Concatenate to end of file</td>
-<td>Creates a new file if it doesn’t exist</td>
-</tr>
-</tbody>
-</table>
-</section>
-<section id="command-line-text-editors-vim-nano" class="level3" data-number="7.8.7">
-<h3 data-number="7.8.7" class="anchored" data-anchor-id="command-line-text-editors-vim-nano"><span class="header-section-number">7.8.7</span> Command Line Text Editors (Vim + Nano)</h3>
-<table class="table">
-<colgroup>
-<col style="width: 23%">
-<col style="width: 33%">
-<col style="width: 26%">
-</colgroup>
-<thead>
-<tr class="header">
-<th>Command</th>
-<th>What it does</th>
-<th>Notes + Helpful options</th>
-</tr>
-</thead>
-<tbody>
-<tr class="odd">
-<td><code>^</code></td>
-<td>Prefix for file command in <code>nano</code> editor.</td>
-<td>Its the <code>⌘</code> or <code>Ctrl</code> key, not the caret symbol.</td>
-</tr>
-<tr class="even">
-<td><code>i</code></td>
-<td>Enter insert mode (able to type) in <code>vim</code></td>
-<td></td>
-</tr>
-<tr class="odd">
-<td><code>escape</code></td>
-<td>Enter normal mode (navigation) in <code>vim</code>.</td>
-<td></td>
-</tr>
-<tr class="even">
-<td><code>:w</code></td>
-<td>Write the current file in <code>vim</code> (from normal mode)</td>
-<td>Can be combined to save and quit in one, <code>:wq</code></td>
-</tr>
-<tr class="odd">
-<td><code>:q</code></td>
-<td>Quit <code>vim</code> (from normal mode)</td>
-<td><code>:q!</code> quit without saving</td>
-</tr>
-</tbody>
-</table>
-
-
-</section>
-</section>
-<section id="footnotes" class="footnotes footnotes-end-of-document" role="doc-endnotes">
-<hr>
-<ol>
-<li id="fn1"><p>The title of this callout box is also the tagline for the <code>{magrittr}</code> package.<a href="#fnref1" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
-<li id="fn2"><p>It’s worth noting that <code>scp</code> is now considered “insecure and outdated”. The ways it is insecure are rather obscure and not terribly relevant for most people. But if you’re moving a lot of data, you may want something faster. If so, I’d recommend more modern options like <code>sftp</code> and <code>rsync</code>. I probably wouldn’t bother if you’re only occasionally <code>scp</code>-ing small files to or from your server.<a href="#fnref2" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
-<li id="fn3"><p><code>vi</code> is the original fullscreen text editor for Linux. <code>vim</code> is its successor (<code>vim</code> stands for <code>vi</code> improved). I’m not going to worry about the distinction.<a href="#fnref3" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
-</ol>
-</section>
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diff --git a/chapters/sec2/2-3-ssh.html b/chapters/sec2/2-2-cmd-line.html
similarity index 50%
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rename to chapters/sec2/2-2-cmd-line.html
index 9dfadd151..4c622ddb5 100644
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@@ -7,7 +7,7 @@
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-      <nav class="quarto-page-breadcrumbs" aria-label="breadcrumb"><ol class="breadcrumb"><li class="breadcrumb-item"><a href="../../chapters/sec2/2-0-sec-intro.html">IT/Admin Tools</a></li><li class="breadcrumb-item"><a href="../../chapters/sec2/2-3-ssh.html"><span class="chapter-number">8</span>&nbsp; <span class="chapter-title">Secure server connections with SSH</span></a></li></ol></nav>
+      <nav class="quarto-page-breadcrumbs" aria-label="breadcrumb"><ol class="breadcrumb"><li class="breadcrumb-item"><a href="../../chapters/sec2/2-0-sec-intro.html">IT/Admin for Data Science</a></li><li class="breadcrumb-item"><a href="../../chapters/sec2/2-2-cmd-line.html"><span class="chapter-number">8</span>&nbsp; <span class="chapter-title">Customizing the command line</span></a></li></ol></nav>
       <a class="flex-grow-1" role="button" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar,#quarto-sidebar-glass" aria-controls="quarto-sidebar" aria-expanded="false" aria-label="Toggle sidebar navigation" onclick="if (window.quartoToggleHeadroom) { window.quartoToggleHeadroom(); }">      
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@@ -213,13 +213,19 @@
   <a href="../../chapters/sec1/1-5-deployments.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">5</span>&nbsp; <span class="chapter-title">Deployments and code promotion</span></span></a>
   </div>
+</li>
+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/sec1/1-6-docker.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">6</span>&nbsp; <span class="chapter-title">Demystifying Docker</span></span></a>
+  </div>
 </li>
       </ul>
   </li>
         <li class="sidebar-item sidebar-item-section">
       <div class="sidebar-item-container"> 
             <a href="../../chapters/sec2/2-0-sec-intro.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text">IT/Admin Tools</span></a>
+ <span class="menu-text">IT/Admin for Data Science</span></a>
           <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-2" aria-expanded="true" aria-label="Toggle section">
             <i class="bi bi-chevron-right ms-2"></i>
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@@ -227,121 +233,98 @@
       <ul id="quarto-sidebar-section-2" class="collapse list-unstyled sidebar-section depth1 show">  
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-  <a href="../../chapters/sec2/2-1-cmd-line.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">6</span>&nbsp; <span class="chapter-title">Opening the Command Line</span></span></a>
-  </div>
-</li>
-          <li class="sidebar-item">
-  <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec2/2-2-cmd-line-use.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">7</span>&nbsp; <span class="chapter-title">Using the Command Line</span></span></a>
+  <a href="../../chapters/sec2/2-1-cloud.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">7</span>&nbsp; <span class="chapter-title">The Cloud</span></span></a>
   </div>
 </li>
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-  <a href="../../chapters/sec2/2-3-ssh.html" class="sidebar-item-text sidebar-link active">
- <span class="menu-text"><span class="chapter-number">8</span>&nbsp; <span class="chapter-title">Secure server connections with SSH</span></span></a>
+  <a href="../../chapters/sec2/2-2-cmd-line.html" class="sidebar-item-text sidebar-link active">
+ <span class="menu-text"><span class="chapter-number">8</span>&nbsp; <span class="chapter-title">Customizing the command line</span></span></a>
   </div>
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-  <a href="../../chapters/sec2/2-4-docker.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">9</span>&nbsp; <span class="chapter-title">Demystifying Docker</span></span></a>
+  <a href="../../chapters/sec2/2-3-linux.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">9</span>&nbsp; <span class="chapter-title">Intro to Linux Administration</span></span></a>
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-      </ul>
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- <span class="menu-text">IT/Admin for Data Science</span></a>
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- <span class="menu-text"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Getting Started with the Cloud</span></span></a>
+  <a href="../../chapters/sec2/2-4-app-admin.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Application administration</span></span></a>
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-  <a href="../../chapters/sec3/3-2-linux-admin.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Basic Linux SysAdmin</span></span></a>
+  <a href="../../chapters/sec2/2-5-scale.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Server Resources and Scaling</span></span></a>
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 </li>
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-  <a href="../../chapters/sec3/3-3-networking.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-6-networking.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">12</span>&nbsp; <span class="chapter-title">Intro to Computer Networks</span></span></a>
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 </li>
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-  <a href="../../chapters/sec3/3-4-dns.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-7-dns.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">13</span>&nbsp; <span class="chapter-title">DNS allows for human-readable addresses</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-5-ssl.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-8-ssl.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">14</span>&nbsp; <span class="chapter-title">You should use SSL/HTTPS</span></span></a>
   </div>
-</li>
-          <li class="sidebar-item">
-  <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-6-servers.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Choosing the right server for you</span></span></a>
-  </div>
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       <div class="sidebar-item-container"> 
-            <a href="../../chapters/sec4/4-0-sec-intro.html" class="sidebar-item-text sidebar-link">
+            <a href="../../chapters/sec3/3-0-sec-intro.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text">Making it Enterprise-Grade</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true" aria-label="Toggle section">
+          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-3" aria-expanded="true" aria-label="Toggle section">
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-      <ul id="quarto-sidebar-section-4" class="collapse list-unstyled sidebar-section depth1 show">  
+      <ul id="quarto-sidebar-section-3" class="collapse list-unstyled sidebar-section depth1 show">  
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-  <a href="../../chapters/sec4/4-1-os-ds-in-ent.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></a>
+  <a href="../../chapters/sec3/3-1-os-ds-in-ent.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></a>
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-  <a href="../../chapters/sec4/4-2-ent-networks.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></a>
+  <a href="../../chapters/sec3/3-2-ent-networks.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></a>
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-  <a href="../../chapters/sec4/4-3-auth.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></a>
+  <a href="../../chapters/sec3/3-3-auth.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></a>
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-  <a href="../../chapters/sec4/4-4-ent-servers.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">19</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></a>
+  <a href="../../chapters/sec3/3-4-ent-servers.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></a>
   </div>
 </li>
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         <li class="sidebar-item sidebar-item-section">
       <div class="sidebar-item-container"> 
-            <a class="sidebar-item-text sidebar-link text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-5" aria-expanded="true">
+            <a class="sidebar-item-text sidebar-link text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true">
  <span class="menu-text">Appendices</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-5" aria-expanded="true" aria-label="Toggle section">
+          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true" aria-label="Toggle section">
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-      <ul id="quarto-sidebar-section-5" class="collapse list-unstyled sidebar-section depth1 show">  
+      <ul id="quarto-sidebar-section-4" class="collapse list-unstyled sidebar-section depth1 show">  
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
   <a href="../../chapters/append/auth.html" class="sidebar-item-text sidebar-link">
@@ -353,6 +336,12 @@
   <a href="../../chapters/append/lab-map.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">B</span>&nbsp; <span class="chapter-title">Lab Map</span></span></a>
   </div>
+</li>
+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/append/cheatsheets.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">C</span>&nbsp; <span class="chapter-title">Cheatsheets</span></span></a>
+  </div>
 </li>
       </ul>
   </li>
@@ -366,23 +355,37 @@
     <h2 id="toc-title">Table of contents</h2>
    
   <ul>
-  <li><a href="#practical-ssh-usage" id="toc-practical-ssh-usage" class="nav-link active" data-scroll-target="#practical-ssh-usage"><span class="header-section-number">8.1</span> Practical SSH usage</a>
+  <li><a href="#getting-the-command-line-you-want" id="toc-getting-the-command-line-you-want" class="nav-link active" data-scroll-target="#getting-the-command-line-you-want"><span class="header-section-number">8.1</span> Getting the command line you want</a></li>
+  <li><a href="#the-terminal" id="toc-the-terminal" class="nav-link" data-scroll-target="#the-terminal"><span class="header-section-number">8.2</span> The terminal</a></li>
+  <li><a href="#the-shell" id="toc-the-shell" class="nav-link" data-scroll-target="#the-shell"><span class="header-section-number">8.3</span> The shell</a></li>
+  <li><a href="#configuration-management" id="toc-configuration-management" class="nav-link" data-scroll-target="#configuration-management"><span class="header-section-number">8.4</span> Configuration management</a></li>
+  <li><a href="#text-editors" id="toc-text-editors" class="nav-link" data-scroll-target="#text-editors"><span class="header-section-number">8.5</span> Text Editors</a></li>
+  <li><a href="#secure-server-connections-with-ssh" id="toc-secure-server-connections-with-ssh" class="nav-link" data-scroll-target="#secure-server-connections-with-ssh"><span class="header-section-number">8.6</span> Secure server connections with SSH</a>
   <ul class="collapse">
-  <li><a href="#step-1-create-keypair" id="toc-step-1-create-keypair" class="nav-link" data-scroll-target="#step-1-create-keypair"><span class="header-section-number">8.1.1</span> Step 1: Create Keypair</a></li>
-  <li><a href="#step-2-register-the-public-keys" id="toc-step-2-register-the-public-keys" class="nav-link" data-scroll-target="#step-2-register-the-public-keys"><span class="header-section-number">8.1.2</span> Step 2: Register the public keys</a></li>
-  <li><a href="#step-3-use-ssh" id="toc-step-3-use-ssh" class="nav-link" data-scroll-target="#step-3-use-ssh"><span class="header-section-number">8.1.3</span> Step 3: Use SSH</a></li>
+  <li><a href="#understanding-ssh-keys" id="toc-understanding-ssh-keys" class="nav-link" data-scroll-target="#understanding-ssh-keys"><span class="header-section-number">8.6.1</span> Understanding SSH keys</a></li>
+  </ul></li>
+  <li><a href="#practical-ssh-usage" id="toc-practical-ssh-usage" class="nav-link" data-scroll-target="#practical-ssh-usage"><span class="header-section-number">8.7</span> Practical SSH usage</a>
+  <ul class="collapse">
+  <li><a href="#step-1-create-keypair" id="toc-step-1-create-keypair" class="nav-link" data-scroll-target="#step-1-create-keypair"><span class="header-section-number">8.7.1</span> Step 1: Create Keypair</a></li>
+  <li><a href="#step-2-register-the-public-keys" id="toc-step-2-register-the-public-keys" class="nav-link" data-scroll-target="#step-2-register-the-public-keys"><span class="header-section-number">8.7.2</span> Step 2: Register the public keys</a></li>
+  <li><a href="#step-3-use-ssh" id="toc-step-3-use-ssh" class="nav-link" data-scroll-target="#step-3-use-ssh"><span class="header-section-number">8.7.3</span> Step 3: Use SSH</a></li>
+  </ul></li>
+  <li><a href="#comprehension-questions" id="toc-comprehension-questions" class="nav-link" data-scroll-target="#comprehension-questions"><span class="header-section-number">8.8</span> Comprehension Questions</a></li>
+  <li><a href="#lab-login-to-the-server" id="toc-lab-login-to-the-server" class="nav-link" data-scroll-target="#lab-login-to-the-server"><span class="header-section-number">8.9</span> Lab: Login to the server</a>
+  <ul class="collapse">
+  <li><a href="#step-1-grab-the-server-address" id="toc-step-1-grab-the-server-address" class="nav-link" data-scroll-target="#step-1-grab-the-server-address"><span class="header-section-number">8.9.1</span> Step 1: Grab the server address</a></li>
+  <li><a href="#step-2-log-on-with-the-.pem-key" id="toc-step-2-log-on-with-the-.pem-key" class="nav-link" data-scroll-target="#step-2-log-on-with-the-.pem-key"><span class="header-section-number">8.9.2</span> Step 2: Log on with the <code>.pem</code> key</a></li>
+  <li><a href="#step-3-create-your-own-ssh-key" id="toc-step-3-create-your-own-ssh-key" class="nav-link" data-scroll-target="#step-3-create-your-own-ssh-key"><span class="header-section-number">8.9.3</span> Step 3: Create your own SSH key</a></li>
   </ul></li>
-  <li><a href="#comprehension-questions" id="toc-comprehension-questions" class="nav-link" data-scroll-target="#comprehension-questions"><span class="header-section-number">8.2</span> Comprehension Questions</a></li>
-  <li><a href="#cheat-ssh" id="toc-cheat-ssh" class="nav-link" data-scroll-target="#cheat-ssh"><span class="header-section-number">8.3</span> Cheatsheet: <code>ssh</code></a></li>
   </ul>
-<div class="toc-actions"><div><i class="bi bi-github"></i></div><div class="action-links"><p><a href="https://github.com/akgold/do4ds/edit/main/chapters/sec2/2-3-ssh.qmd" class="toc-action">Edit this page</a></p></div></div></nav>
+<div class="toc-actions"><div><i class="bi bi-github"></i></div><div class="action-links"><p><a href="https://github.com/akgold/do4ds/edit/main/chapters/sec2/2-2-cmd-line.qmd" class="toc-action">Edit this page</a></p></div></div></nav>
     </div>
 <!-- main -->
 <main class="content" id="quarto-document-content">
 
 <header id="title-block-header" class="quarto-title-block default">
 <div class="quarto-title">
-<h1 class="title"><span id="sec-ssh" class="quarto-section-identifier"><span class="chapter-number">8</span>&nbsp; <span class="chapter-title">Secure server connections with SSH</span></span></h1>
+<h1 class="title"><span id="sec-cmd-line" class="quarto-section-identifier"><span class="chapter-number">8</span>&nbsp; <span class="chapter-title">Customizing the command line</span></span></h1>
 </div>
 
 
@@ -397,18 +400,122 @@ <h1 class="title"><span id="sec-ssh" class="quarto-section-identifier"><span cla
 
 </header>
 
-<p>One common IT/Admin task is remotely managing a server from the command line on your machine. SSH – short for Secure (Socket) Shell – is the program that allows direct interactions with a server’s command line from the command line of your computer.<a href="#fn1" class="footnote-ref" id="fnref1" role="doc-noteref"><sup>1</sup></a></p>
-<p>Using SSH requires invoking the <code>ssh</code> command line interface with a username and the address of the <em>remote host</em> <u>(</u>server). For example, to connect to the user <code>alex</code> on the remote host <code>server.example.com</code>, it would look like:</p>
+<p>When you want to do something on your personal computer or phone, you just tap or click to make it happen. But servers generally have no <em>graphical user interface (GUI)</em> to be tapped or clicked. On a server, interaction is via the <em>command line</em> – an all-text interface where you type to indicate what you want to do.</p>
+<p>Even if you’re not administering a server, it’s worth learning your way around the command line as a number of tasks are quicker and easier from the command line. Most people who learn the command line end up using it a lot on their personal computers.</p>
+<div class="callout callout-style-default callout-note callout-titled">
+<div class="callout-header d-flex align-content-center">
+<div class="callout-icon-container">
+<i class="callout-icon"></i>
+</div>
+<div class="callout-title-container flex-fill">
+Note
+</div>
+</div>
+<div class="callout-body-container callout-body">
+<p>Server admin tasks are done via a graphical tool in some organizations, but this is a red flag.</p>
+<p>It means that the organization is either trying to find relatively low-skill (cheap) admins who haven’t bothered to learn to use the command line or are using an intermediary tool to limit what IT/Admins can do. Either way, it’s going to be harder to get things done.</p>
+</div>
+</div>
+<p>In this chapter, you’re going to learn to set up and customize the command line on your machine and to access a server via <em>secure socket shell (SSH)</em> – the administrative side door on a server.</p>
+<section id="getting-the-command-line-you-want" class="level2" data-number="8.1">
+<h2 data-number="8.1" class="anchored" data-anchor-id="getting-the-command-line-you-want"><span class="header-section-number">8.1</span> Getting the command line you want</h2>
+<p>As you get started on the command line, you’ll soon realize that some customization is in order. Maybe the colors aren’t quite right, or you want shortcuts for commands you type a lot, or you want more information in the default display.</p>
+<p>Some people might argue that customizing your command line isn’t the best use of your time and energy. Those people are no fun. Having a command line that behaves exactly as you like will speed up your work and make you feel like a hacker.</p>
+<p>But as you get started, you’ll soon find yourself neck deep in Stack Overflow posts on how to customize your <code>.bashrc</code>. Or wait, is it the <code>.zshrc</code>? Or…</p>
+<p>The reason customizing your command line is somewhat confusing is that the command line you interact with is actually two or three programs that sit on top of each other. You can mix-and-match options for each of them and configure them in a variety of ways.</p>
+<div class="callout callout-style-default callout-note callout-titled">
+<div class="callout-header d-flex align-content-center">
+<div class="callout-icon-container">
+<i class="callout-icon"></i>
+</div>
+<div class="callout-title-container flex-fill">
+Notes on operating systems
+</div>
+</div>
+<div class="callout-body-container callout-body">
+<p>I’ve been using the command line in MacOS for many years, so I have strong opinions to share in this chapter.</p>
+<p>I haven’t used a Windows machine in many years. I’ve collected some recommendations, but I can’t personally vouch for them the same way.</p>
+<p>I don’t include Linux recommendations because people who use Linux on their desktop have already gone deep down the customization rabbit hole and don’t need my help wasting their time.</p>
+</div>
+</div>
+</section>
+<section id="the-terminal" class="level2" data-number="8.2">
+<h2 data-number="8.2" class="anchored" data-anchor-id="the-terminal"><span class="header-section-number">8.2</span> The terminal</h2>
+<p>The terminal is the GUI where you’ll type in commands. The terminal program you use will dictate the colors and themes available for the window, how tabs and panes work, and the keyboard shortcuts you’ll use to manage them.</p>
+<p>Some programs you might use, like RStudio or VSCode have terminals built into them. If you do basically all your terminal work from one of these environments, you may not need another. But it can be nice to have a standalone terminal program you like.</p>
+<div class="tabset-margin-container"></div><div class="panel-tabset">
+<ul class="nav nav-tabs" role="tablist"><li class="nav-item" role="presentation"><a class="nav-link active" id="tabset-1-1-tab" data-bs-toggle="tab" data-bs-target="#tabset-1-1" role="tab" aria-controls="tabset-1-1" aria-selected="true" aria-current="page">MacOS</a></li><li class="nav-item" role="presentation"><a class="nav-link" id="tabset-1-2-tab" data-bs-toggle="tab" data-bs-target="#tabset-1-2" role="tab" aria-controls="tabset-1-2" aria-selected="false">Windows</a></li></ul>
+<div class="tab-content">
+<div id="tabset-1-1" class="tab-pane active" role="tabpanel" aria-labelledby="tabset-1-1-tab">
+<p>I’d recommend against using the built-in terminal app (called <em>Terminal</em>). It’s fine, but there are better options.</p>
+<p>My personal favorite is the free <a href="https://iterm2.com/"><em>iTerm2</em></a>, which adds a bunch of niceties like better theming and multiple tabs.</p>
+</div>
+<div id="tabset-1-2" class="tab-pane" role="tabpanel" aria-labelledby="tabset-1-2-tab">
+<p>The built-in terminal is the favorite of many users. There are a variety of alternatives you can try, but feel free to stick with the default.</p>
+</div>
+</div>
+</div>
+</section>
+<section id="the-shell" class="level2" data-number="8.3">
+<h2 data-number="8.3" class="anchored" data-anchor-id="the-shell"><span class="header-section-number">8.3</span> The shell</h2>
+<p>The shell is the program that takes the commands you’re typing and runs them. It’s what matches the words you type to actual commands or programs on your system. Depending on which shell you choose, you’ll get different options for plugins and themes.</p>
+<p>The shell runs anywhere you’ve got a running operating system. So your computer has one shell and your server would have a different one. Even a Docker Container has a shell available. That means that if you do a lot of work on a server, you may need to configure your shell twice – once locally and once on the server.</p>
+<div class="tabset-margin-container"></div><div class="panel-tabset">
+<ul class="nav nav-tabs" role="tablist"><li class="nav-item" role="presentation"><a class="nav-link active" id="tabset-2-1-tab" data-bs-toggle="tab" data-bs-target="#tabset-2-1" role="tab" aria-controls="tabset-2-1" aria-selected="true">MacOS</a></li><li class="nav-item" role="presentation"><a class="nav-link" id="tabset-2-2-tab" data-bs-toggle="tab" data-bs-target="#tabset-2-2" role="tab" aria-controls="tabset-2-2" aria-selected="false">Windows</a></li></ul>
+<div class="tab-content">
+<div id="tabset-2-1" class="tab-pane active" role="tabpanel" aria-labelledby="tabset-2-1-tab">
+<p>The default shell for MacOS (and Linux) is called <em>bash</em>. I’d advise you to switch it out for <em>zsh</em>, which is the most popular <em>bash alternative</em>.<a href="#fn1" class="footnote-ref" id="fnref1" role="doc-noteref"><sup>1</sup></a> Bash alternatives are programs that extend bash with various bells and whistles.</p>
+<p>Relative to bash, zsh has a few advantages out of the box, like better auto-completion. It also has a huge ecosystem of themes to enhance visual appeal and functionality, and plugins that let your command line do everything from displaying your git status to controlling your Spotify playlist.</p>
+<p>I’d recommend looking up instructions for how to install zsh using <em>Homebrew</em>.</p>
+</div>
+<div id="tabset-2-2" class="tab-pane" role="tabpanel" aria-labelledby="tabset-2-2-tab">
+<p>Windows comes with two shells built in, the <em>Command Shell</em> (<code>cmd</code>) and the <em>PowerShell</em>.</p>
+<p>The Command Shell is older and has been superseded by PowerShell. If you’re just getting started, you should just work with PowerShell. If you’ve been using Command Shell on a Windows machine for a long time, most Command Shell commands work in PowerShell, so it may be worth switching over.</p>
+</div>
+</div>
+</div>
+</section>
+<section id="configuration-management" class="level2" data-number="8.4">
+<h2 data-number="8.4" class="anchored" data-anchor-id="configuration-management"><span class="header-section-number">8.4</span> Configuration management</h2>
+<p>Now that you’ve got your shell and terminal installed, you’ll want to customize. It is possible to directly customize both zsh and PowerShell. But the best way to configure them is to use a configuration manager for your themes and plugins.</p>
+<div class="tabset-margin-container"></div><div class="panel-tabset">
+<ul class="nav nav-tabs" role="tablist"><li class="nav-item" role="presentation"><a class="nav-link active" id="tabset-3-1-tab" data-bs-toggle="tab" data-bs-target="#tabset-3-1" role="tab" aria-controls="tabset-3-1" aria-selected="true">MacOS</a></li><li class="nav-item" role="presentation"><a class="nav-link" id="tabset-3-2-tab" data-bs-toggle="tab" data-bs-target="#tabset-3-2" role="tab" aria-controls="tabset-3-2" aria-selected="false">Windows</a></li></ul>
+<div class="tab-content">
+<div id="tabset-3-1" class="tab-pane active" role="tabpanel" aria-labelledby="tabset-3-1-tab">
+<p><em>Prezto</em> is my favorite configuration and plugin manager for zsh. <em>OhMyZsh</em> is also popular and very good. Feel free to choose either, but you can only use one.</p>
+<p>Once you’ve installed Prezto, you’ve got (at least) three different places you could configure your command line – the iTerm2 preferences, <code>.zshrc</code>, and <code>.zpreztorc</code>. I’d recommend leaving <code>.zshrc</code> alone, customizing the look of the window and the tab behavior in the iTerm2 preferences, and customizing the text theme and plugins via Prezto in the <code>.zpreztorc</code> file.</p>
+<p>I tend to be a pretty light on customization, but I’d recommend looking into git plugins and some of the advanced auto-completion and command history search functionality.</p>
+</div>
+<div id="tabset-3-2" class="tab-pane" role="tabpanel" aria-labelledby="tabset-3-2-tab">
+<p>Many people like customizing PowerShell with <a href="https://ohmyposh.dev/"><em>Oh My Posh</em></a>.</p>
+</div>
+</div>
+</div>
+</section>
+<section id="text-editors" class="level2" data-number="8.5">
+<h2 data-number="8.5" class="anchored" data-anchor-id="text-editors"><span class="header-section-number">8.5</span> Text Editors</h2>
+<p>If you’re working on your command line a lot, you’ll probably be working inside <em>text editors</em> a fair bit. There are many, many options for text editors and people have strong preferences.</p>
+<p>Mac OS’s default text editor is called TextEdit and it’s bad. Don’t use it. Windows users get Notepad, which is somewhat better than TextEdit, but still not the best option out there.</p>
+<p>If you like, you can just edit text files inside your IDE of choice like VS Code or RStudio. Others may prefer a standalone text editor. The most popular these days are probably <em>Sublime</em> or <em>Notepad++</em> (Windows Only).</p>
+<p>Unlike with the terminal, there’s no deep configuration here. Install one from the web, configure it as you like, and make sure it’s the default for opening <code>.txt</code> and other files you might want to edit in your system preferences.</p>
+</section>
+<section id="secure-server-connections-with-ssh" class="level2" data-number="8.6">
+<h2 data-number="8.6" class="anchored" data-anchor-id="secure-server-connections-with-ssh"><span class="header-section-number">8.6</span> Secure server connections with SSH</h2>
+<p>One common IT/Admin task is remotely accessing a server from the command line on your machine. <em>SSH</em> – short for <em>Secure (Socket) Shell</em> – is a tool for making a secure connection to another computer over an unsecured network. It’s most often used to interact with a server’s command line from the command line of your computer.</p>
+<p>Using SSH requires invoking the <code>ssh</code> command line interface from your computer (<em>local host</em>) with a username and the address of the <em>remote host</em> <u>(</u>server). For example, connecting to the server at <code>server.example.com</code> as the user <code>alex</code></p>
 <div class="code-with-filename">
 <div class="code-with-filename-file">
 <pre><strong>Terminal</strong></pre>
 </div>
 <div class="sourceCode" id="cb1"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb1-1"><a href="#cb1-1"></a><span class="op">&gt;</span> ssh <span class="ex">alex@server.example.com</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </div>
-<p>When this command runs, the local machine would request an SSH session from <code>server.example.com</code> and offer a <em>private ssh key</em> to verify that who’s asking. The remote host would use a <em>public ssh key</em> that’s already been registered with it to verify the private key and open an encrypted connection between the two machines.</p>
+<p>Once you run this command, your terminal will open a session to the terminal of the server.</p>
+<section id="understanding-ssh-keys" class="level3" data-number="8.6.1">
+<h3 data-number="8.6.1" class="anchored" data-anchor-id="understanding-ssh-keys"><span class="header-section-number">8.6.1</span> Understanding SSH keys</h3>
+<p>Before any of this can work, you’ll have to configure your <em>SSH keys</em>, which come in a set called <em>keypair</em>. Each keypair consists of a <em>public</em> key and a <em>private</em> key. You’ll register your public key anywhere you’re trying to SSH to, like a server or git host, but your private key must be treated as a precious secret.</p>
+<p>When you use the <code>ssh</code> command, your local machine sends a request to open an SSH session to the remote and includes the private key with the request. The remote host verifies the private key with the public key and opens an encrypted connection.</p>
 <p><img src="images/ssh.png" class="img-fluid" alt="A diagram of SSH initialization. The local host sends the private key, the remote checks against the public key, and then opens the session." width="450"></p>
-<p>Once the SSH session was established, any command line commands would run against the remote host, rather than against the local machine.</p>
-<p>SSH requires creating and using matching <em>ssh keypairs</em>. The public part of the keypair can be shared far and wide, while the private keys must be treated as danagerous secrets. That seems weird.</p>
+<p>This seems weird – how can you verify your secret identity with something that you can just spread around publicly? The answer is <em>public key cryptography</em>, which makes it easy to check whether a proffered private key is valid, but nearly impossible to fabricate a private key from a public key.</p>
 <div class="callout callout-style-default callout-note callout-titled">
 <div class="callout-header d-flex align-content-center">
 <div class="callout-icon-container">
@@ -419,43 +526,54 @@ <h1 class="title"><span id="sec-ssh" class="quarto-section-identifier"><span cla
 </div>
 </div>
 <div class="callout-body-container callout-body">
-<p>Honestly, I’m not a huge fan of the terms public key and private key. I think the terms <em>SSH key</em> for the private key and <em>SSH lock</em> for the public key makes the intent much clearer. But no one asked me.</p>
+<p>I wish public and private keys were named differently. Calling the private key the <em>key</em> and the public key the <em>lock</em> makes the intent much clearer. But no one asked me.</p>
 </div>
 </div>
-<p>Until you have some understanding of how SSH works, you can set up SSH by following online tutorials, but it always feels a little like a guessing game.</p>
-<p>SSH works because public keys and private keys are really different. Given both a public and a private key, it’s easy to check whether they fit. But if you only have a public key, it’s nearly impossible to fabricate the private key that goes with it.</p>
-<p>This is possible through the magic of <em>public key cryptography</em>, which uses mathematical operations that are easy in one direction but really hard to reverse.</p>
-<p>As a simple example, think of the number <span class="math inline">\(91\)</span> and its prime factors. Do you know what the prime factors of <span class="math inline">\(91\)</span> are offhand? I do not.</p>
-<p>If I give you the numbers <span class="math inline">\(7\)</span> and <span class="math inline">\(13\)</span>, it’s easy and fast to verify that <span class="math inline">\(7 * 13 = 91\)</span>. But if I’d left you hanging, it probably would’ve taken you a minute or two to figure out.</p>
+<p>The key to public key cryptography is mathematical operations that are easy in one direction but really hard to reverse. As a simple example, think of the number <span class="math inline">\(91\)</span> and its prime factors. Do you know what the prime factors of <span class="math inline">\(91\)</span> are offhand? I do not.</p>
+<p>It’ll probably take you a few minutes to try a bunch, even if you use a calculator. But if I give you the numbers <span class="math inline">\(7\)</span> and <span class="math inline">\(13\)</span>, it’s easy to verify that <span class="math inline">\(7 * 13 = 91\)</span>.</p>
 <p>In this example, the number <span class="math inline">\(91\)</span> would be the public key and the prime numbers <span class="math inline">\(7\)</span> and <span class="math inline">\(13\)</span> together would be the private key. This wouldn’t actually make for very good public key cryptography because it doesn’t take more than a few moments to figure out that <span class="math inline">\(7\)</span> and <span class="math inline">\(13\)</span> are prime factors of <span class="math inline">\(91\)</span>.</p>
-<p>In real public key cryptography, the idea is fundamentally similar, but the mathematical operations are substantially more complex and the numbers much, much bigger.<a href="#fn2" class="footnote-ref" id="fnref2" role="doc-noteref"><sup>2</sup></a> So much so that it’s basically impossible to break public ssh keys. Someone could try, but brute force guessing would take more time than we have left before the heat death of the universe.</p>
-<p>That means that it’s safe to share your public key anywhere you might need to access using SSH like a remote server or git host, like GitHub.</p>
-<p>But that doesn’t make SSH foolproof. While it’s basically impossible to fabricate a private key, it’s totally possible to steal one.</p>
-<p>Your private key <strong>must</strong> be kept secret. The best practice is to never move it from the computer where it was created and to never share them.</p>
+<p>In real public key cryptography, the idea is similar, but the mathematical operations are more complex and the numbers much, much bigger. So much so that it’s basically impossible to break public SSH keys through guessing.</p>
+<p>But that doesn’t make SSH foolproof. While it’s basically impossible to fabricate a private key, it’s totally possible to steal one. Your private key <strong>must</strong> be kept secret. The best practice is to never move it from the computer where it was created and to never share them.</p>
 <p>In summary, do what you want with your public keys, but don’t share your private keys. Don’t share your private keys. Seriously, do not share your private keys.</p>
-<section id="practical-ssh-usage" class="level2" data-number="8.1">
-<h2 data-number="8.1" class="anchored" data-anchor-id="practical-ssh-usage"><span class="header-section-number">8.1</span> Practical SSH usage</h2>
+</section>
+</section>
+<section id="practical-ssh-usage" class="level2" data-number="8.7">
+<h2 data-number="8.7" class="anchored" data-anchor-id="practical-ssh-usage"><span class="header-section-number">8.7</span> Practical SSH usage</h2>
 <p>Now that you’ve got an understanding of how SSH works, the steps should be easy to remember.</p>
 <ol type="1">
 <li>Create an SSH keypair on any machine you’ll be SSH-ing from (local host).</li>
 <li>Put the public key anywhere you’ll be SSH-ing to (remote host).</li>
 <li>Use the <code>ssh</code> command to connect.</li>
 </ol>
-<section id="step-1-create-keypair" class="level3" data-number="8.1.1">
-<h3 data-number="8.1.1" class="anchored" data-anchor-id="step-1-create-keypair"><span class="header-section-number">8.1.1</span> Step 1: Create Keypair</h3>
-<p>You’ll create a keypair on any server you’re SSH-ing <strong>from</strong>. Remember, you should never move your private key. If you think the answer to a problem you’re having is to move your private key, think again. You should create a new private key wherever you want to move it to.</p>
-<p>To create an SSH keypair, you should just follow a tutorial online. There are many.</p>
-<p>Creating the keypair will result in two parts. The one that ends in <code>.pub</code> is – you guessed it – the public key.</p>
-<p>In most cases, you’ll only create one private key on each machine. If you follow standard instructions for creating a key, it will use the default name, probably <code>id_ed25519</code>.<a href="#fn3" class="footnote-ref" id="fnref3" role="doc-noteref"><sup>3</sup></a> If you’re only creating one key, I’d recommend sticking with the default name because the <code>ssh</code> command will atuomatically use your keys if they have the default name.</p>
-<p>You may not be able to use the default names if your organization mandates a unique keypair for every service you’re reaching out to. There isn’t a cryptographic reason for this. It’s mostly to make it easier to swap out the keypair later if you need to.</p>
+<p>If you’re working on a server, you’ll probably create at least two keypairs. One on your personal computer to SSH to the server, and one on the server to access outside services that use SSH, like GitHub.</p>
+<section id="step-1-create-keypair" class="level3" data-number="8.7.1">
+<h3 data-number="8.7.1" class="anchored" data-anchor-id="step-1-create-keypair"><span class="header-section-number">8.7.1</span> Step 1: Create Keypair</h3>
+<p>You’ll create a keypair on any server you’re SSH-ing <strong>from</strong>.</p>
+<p>To create an SSH keypair, you should just follow a tutorial online. The keypair will have two parts. The one that ends in <code>.pub</code> is – you guessed it – the public key.</p>
+<p>In most cases, you’ll only create one private key on each machine. If you follow standard instructions for creating a key, it will use the default name, probably <code>id_ed25519</code>.<a href="#fn2" class="footnote-ref" id="fnref2" role="doc-noteref"><sup>2</sup></a> Sticking with the default name is great because the <code>ssh</code> command will automatically use them. If you don’t use the default name, you’ll have to specify.</p>
+<div class="callout callout-style-default callout-note callout-titled">
+<div class="callout-header d-flex align-content-center">
+<div class="callout-icon-container">
+<i class="callout-icon"></i>
+</div>
+<div class="callout-title-container flex-fill">
+Note
+</div>
+</div>
+<div class="callout-body-container callout-body">
+<p>Remember, you should never move your private key. If you think the answer to a problem you’re having is to move your private key, think again.</p>
+<p>Instead of moving your private key, create a new private key on the machine where you need to use SSH and register a second public key on the remote.</p>
+</div>
+</div>
+<p>Some organizations require that you have a unique key for each service you’re using to make it easier to swap keys in the event of a breach. If so, you won’t be able to use the default key names.</p>
 </section>
-<section id="step-2-register-the-public-keys" class="level3" data-number="8.1.2">
-<h3 data-number="8.1.2" class="anchored" data-anchor-id="step-2-register-the-public-keys"><span class="header-section-number">8.1.2</span> Step 2: Register the public keys</h3>
-<p>To register a public key on a server you control, you’ll add the public key to the end of the user’s <code>.ssh/authorized_keys</code> file in their home directory. You’ll have to make sure the permissions on the <code>authorized_keys</code> file are correct. More on that in <a href="../sec3/3-2-linux-admin.html">Chapter&nbsp;<span>11</span></a>.</p>
-<p>If you’re registering with a service, like GitHub.com, find a guide to registering SSH keys and it will show you how to do so.</p>
+<section id="step-2-register-the-public-keys" class="level3" data-number="8.7.2">
+<h3 data-number="8.7.2" class="anchored" data-anchor-id="step-2-register-the-public-keys"><span class="header-section-number">8.7.2</span> Step 2: Register the public keys</h3>
+<p>To register a public key to SSH into a server, you’ll add the public key to the end of the user’s <code>.ssh/authorized_keys</code> file in their home directory. You’ll have to make sure the permissions on the <code>authorized_keys</code> file are correct. More on that in <a href="2-3-linux.html">Chapter&nbsp;<span>9</span></a>.</p>
+<p>If you’re registering with a service, like GitHub.com, there’s probably a text box in the GUI to add an SSH key. Google for instructions on how to do it.</p>
 </section>
-<section id="step-3-use-ssh" class="level3" data-number="8.1.3">
-<h3 data-number="8.1.3" class="anchored" data-anchor-id="step-3-use-ssh"><span class="header-section-number">8.1.3</span> Step 3: Use SSH</h3>
+<section id="step-3-use-ssh" class="level3" data-number="8.7.3">
+<h3 data-number="8.7.3" class="anchored" data-anchor-id="step-3-use-ssh"><span class="header-section-number">8.7.3</span> Step 3: Use SSH</h3>
 <p>To use SSH, you type <code>ssh &lt;user&gt;@&lt;host&gt;</code>. There are also other commands that can use SSH under the hood, like <code>git</code> or <code>scp</code>.</p>
 <div class="callout callout-style-default callout-note callout-titled">
 <div class="callout-header d-flex align-content-center">
@@ -467,60 +585,90 @@ <h3 data-number="8.1.3" class="anchored" data-anchor-id="step-3-use-ssh"><span c
 </div>
 </div>
 <div class="callout-body-container callout-body">
-<p>For a long time, Windows didn’t support SSH out of the box, so SSH-ing from Windows required a separate utility called <em>PuTTY</em>. More recent versions of Windows support using SSH directly in PowerShell or in Windows Subsystem for Linux (WSL). If SSH isn’t enabled on your machine, google for instructions.</p>
+<p>For a long time, Windows didn’t support SSH out of the box, so SSH-ing from Windows required a separate utility called <em>PuTTY</em>. More recent versions of Windows support using SSH directly in PowerShell or in Windows Subsystem for Linux (WSL). If SSH isn’t enabled on your machine, Google for instructions.</p>
 </div>
 </div>
 <p>If you have multiple SSH keys or didn’t use the default flag, you can specify a particular key with the <code>-i</code> flag.</p>
-<p>If you’re using SSH a lot, I’d recommend setting up an SSH config file. An SSH config file allows you to create aliases that are shortcuts to SSH commands including users, hosts, and other details. So if you had a long SSH command like <code>ssh -i my-ssh-key alex@server.example.com</code>, you could shorten it to <code>ssh alex-server</code> or whatever you want.</p>
-<p>Many people also like using <em>tmux</em> with SSH. tmux is a terminal multiplexer, which allows you to manipulate terminal sessions from the command line. SSH sessions block the terminal session they’re using and will break when your computer goes to sleep. tmux allows you to create sessions and make them durable through sleeps and other operations. To be honest, I’m including tmux because lots of people love it, but I’ve tried using it and found the learning curve too steep for it to come into regular usage. Your mileage may vary.</p>
-<p>Lastly, if you ever run into trouble using SSH, it has one of my favorite debugging modes. Just add a <code>-v</code> to your command for verbose mode. If that’s not enough information, add another <code>v</code> for more verbosity, and if <strong>that’s</strong> not enough, just add another <code>v</code> for super verbose mode.</p>
+<p>If you’re using SSH a lot, I’d recommend setting up an <em>SSH config file</em>. An SSH config file allows you to create aliases that are shortcuts to SSH commands including users, hosts, and other details. So if you had a long SSH command like <code>ssh -i my-ssh-key alex@server.example.com</code>, you could shorten it to <code>ssh alex-server</code> or whatever you want.</p>
+<p>One annoyance about SSH is that they block the terminal they’re using and will break when your computer goes to sleep. Many people also like using the <em>tmux</em> command line utility with SSH to help solve these issues.</p>
+<p>tmux is a <em>terminal multiplexer</em>, which allows you to manipulate terminal sessions from the command line, including putting sessions into the background and making sessions durable through sleeps and other operations. To be honest, I’m mentioning tmux because lots of people love it, but I’ve found the learning curve too steep for it to come into regular usage for me. Your mileage may vary.</p>
+<p>If you ever run into trouble using SSH, it has one of my favorite debugging modes. Just add a <code>-v</code> to your command for verbose mode. If that’s not enough information, add another <code>v</code> for more verbosity, and if <strong>that’s</strong> not enough, just add another <code>v</code> for super verbose mode.</p>
 </section>
 </section>
-<section id="comprehension-questions" class="level2" data-number="8.2">
-<h2 data-number="8.2" class="anchored" data-anchor-id="comprehension-questions"><span class="header-section-number">8.2</span> Comprehension Questions</h2>
+<section id="comprehension-questions" class="level2" data-number="8.8">
+<h2 data-number="8.8" class="anchored" data-anchor-id="comprehension-questions"><span class="header-section-number">8.8</span> Comprehension Questions</h2>
 <ol type="1">
+<li>Draw a mental map that includes the following: terminal, shell, theme manager, operating system, my laptop</li>
 <li>Under what circumstances should you move or share your SSH private key?</li>
 <li>What is it about SSH public keys that makes them safe to share?</li>
 </ol>
 </section>
-<section id="cheat-ssh" class="level2" data-number="8.3">
-<h2 data-number="8.3" class="anchored" data-anchor-id="cheat-ssh"><span class="header-section-number">8.3</span> Cheatsheet: <code>ssh</code></h2>
-<div class="sourceCode" id="cb2"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb2-1"><a href="#cb2-1"></a><span class="fu">ssh</span> <span class="op">&lt;</span>user<span class="op">&gt;</span>@<span class="op">&lt;</span>host<span class="op">&gt;</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-<table class="table">
-<colgroup>
-<col style="width: 21%">
-<col style="width: 32%">
-<col style="width: 45%">
-</colgroup>
-<thead>
-<tr class="header">
-<th>Flag</th>
-<th>What it does</th>
-<th>Notes</th>
-</tr>
-</thead>
-<tbody>
-<tr class="odd">
-<td><code>-v</code></td>
-<td>Verbose, good for debugging.</td>
-<td>Add more <code>v</code>s as you please, <code>-vv</code> or <code>-vvv</code>.</td>
-</tr>
-<tr class="even">
-<td><code>-i</code></td>
-<td>Choose identity file (private key)</td>
-<td>Not necessary with default key names.</td>
-</tr>
-</tbody>
-</table>
+<section id="lab-login-to-the-server" class="level2" data-number="8.9">
+<h2 data-number="8.9" class="anchored" data-anchor-id="lab-login-to-the-server"><span class="header-section-number">8.9</span> Lab: Login to the server</h2>
+<p>In the last chapter we got your server up and running. In this lab, we’ll use the provided <code>.pem</code> key to log in for the first time.</p>
+<section id="step-1-grab-the-server-address" class="level3" data-number="8.9.1">
+<h3 data-number="8.9.1" class="anchored" data-anchor-id="step-1-grab-the-server-address"><span class="header-section-number">8.9.1</span> Step 1: Grab the server address</h3>
+<p>From the EC2 page, you can click on the instance ID in blue to see all the details of about your server.</p>
+<p>Copy the Public IPv4 DNS address, which starts with <span class="math inline">\(\text{ec2-}\)</span> and ends with <span class="math inline">\(\text{amazonaws.com}\)</span>. That little icon on the left of the address copies it. You’ll need it throughout the labs. If you lose it, come back here to get it.</p>
+<div class="callout callout-style-default callout-tip callout-titled">
+<div class="callout-header d-flex align-content-center">
+<div class="callout-icon-container">
+<i class="callout-icon"></i>
+</div>
+<div class="callout-title-container flex-fill">
+Set a Server Address Variable
+</div>
+</div>
+<div class="callout-body-container callout-body">
+<p>In the rest of the labs in this book, I’m going to write the commands using the bash variable <code>SERVER_ADDRESS</code>. That means that if you create that variable, you’ll be able to just copy the commands out of the book.</p>
+<p>For example, as I write this, my server has the address <span class="math inline">\(\text{ec2-54-159-134-39.compute-1.amazonaws.com}\)</span>. So would set my server address variable on my command line with <code>SERVER_ADDRESS=ec2-54-159-134-39.compute-1.amazonaws.com</code>.</p>
+<p>If you’re used to R or Python, where it’s best practice to put spaces around <code>=</code>, notice that assigning variables in bash <strong>requires</strong> no spaces around <code>=</code>.</p>
+</div>
+</div>
+</section>
+<section id="step-2-log-on-with-the-.pem-key" class="level3" data-number="8.9.2">
+<h3 data-number="8.9.2" class="anchored" data-anchor-id="step-2-log-on-with-the-.pem-key"><span class="header-section-number">8.9.2</span> Step 2: Log on with the <code>.pem</code> key</h3>
+<p>The <code>.pem</code> key you downloaded when you set up the server is the private key for a pre-registered keypair that will let you SSH into your server as the admin user (named <code>ubuntu</code> on a Ubuntu system).</p>
+<p>The <code>.pem</code> key is just an SSH key, so you can SSH to your server with</p>
+<div class="code-with-filename">
+<div class="code-with-filename-file">
+<pre><strong>Terminal</strong></pre>
+</div>
+<div class="sourceCode" id="cb2"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb2-1"><a href="#cb2-1"></a><span class="fu">ssh</span> <span class="at">-i</span> do4ds-lab-key.pem <span class="dt">\</span></span>
+<span id="cb2-2"><a href="#cb2-2"></a>  ubuntu@SERVER_ADDRESS</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+</div>
+<p>When you first try this, you’re probably going to get an alert that looks something like this:</p>
+<div class="sourceCode" id="cb3"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb3-1"><a href="#cb3-1"></a></span>
+<span id="cb3-2"><a href="#cb3-2"></a><span class="ex">\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@</span></span>
+<span id="cb3-3"><a href="#cb3-3"></a></span>
+<span id="cb3-4"><a href="#cb3-4"></a><span class="ex">\@</span> WARNING: UNPROTECTED PRIVATE KEY FILE! <span class="dt">\@</span></span>
+<span id="cb3-5"><a href="#cb3-5"></a></span>
+<span id="cb3-6"><a href="#cb3-6"></a><span class="ex">\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@</span></span>
+<span id="cb3-7"><a href="#cb3-7"></a></span>
+<span id="cb3-8"><a href="#cb3-8"></a><span class="ex">Permissions</span> 0644 for <span class="st">'do4ds-lab-key.pem'</span> are too open.</span>
+<span id="cb3-9"><a href="#cb3-9"></a></span>
+<span id="cb3-10"><a href="#cb3-10"></a><span class="ex">It</span> is required that your private key files are NOT accessible by others.</span>
+<span id="cb3-11"><a href="#cb3-11"></a></span>
+<span id="cb3-12"><a href="#cb3-12"></a><span class="ex">This</span> private key will be ignored.</span>
+<span id="cb3-13"><a href="#cb3-13"></a></span>
+<span id="cb3-14"><a href="#cb3-14"></a><span class="ex">Load</span> key <span class="st">"do4ds-lab-key.pem"</span>: bad permissions</span>
+<span id="cb3-15"><a href="#cb3-15"></a></span>
+<span id="cb3-16"><a href="#cb3-16"></a><span class="ex">ubuntu@ec2-54-159-134-39.compute-1.amazonaws.com:</span> Permission denied <span class="er">(</span><span class="ex">publickey</span><span class="kw">)</span><span class="bu">.</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+<p>Because the keypair is so powerful, AWS requires that you restrict the access pretty severely. Before you can use it to open the server, you’ll need to change the permissions. We’ll get into permissions in <a href="2-3-linux.html">Chapter&nbsp;<span>9</span></a>. Until then, you can just change the permissions by navigating to the right directory with the <code>cd</code> command and running <code>chmod 600 do4ds-lab-key.pem</code>.</p>
+<p>Once you’ve done that, you should be able to login to your machine as the root user. When you want to exit an SSH session and get back to your machine, you can just type <code>exit</code>.</p>
+</section>
+<section id="step-3-create-your-own-ssh-key" class="level3" data-number="8.9.3">
+<h3 data-number="8.9.3" class="anchored" data-anchor-id="step-3-create-your-own-ssh-key"><span class="header-section-number">8.9.3</span> Step 3: Create your own SSH key</h3>
+<p>You really shouldn’t use the AWS-provided <code>.pem</code> key to login to your server after the first time. It’s too powerful. Create a normal SSH key using the instructions earlier in this chapter. In the next lab, we’ll get that SSH key configured for your user on the server.</p>
 
 
+</section>
 </section>
 <section id="footnotes" class="footnotes footnotes-end-of-document" role="doc-endnotes">
 <hr>
 <ol>
-<li id="fn1"><p>SSH actually can be used between any two machines, provided at least one is accepting SSH connections. For data scientists, SSH is almost always use to connect from a local machine to a server.<a href="#fnref1" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
-<li id="fn2"><p>And prime numbers generally loom large in the operation.<a href="#fnref2" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
-<li id="fn3"><p>The pattern is <code>id_&lt;encryption type&gt;</code>. <code>ed25519</code> is the standard SSH key encryption type as of this writing.<a href="#fnref3" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
+<li id="fn1"><p>zsh is pronounced by just speaking the letters aloud, <em>zee-ess-aitch</em>. Some people might disagree and say it’s <em>zeesh</em>, but they’re not writing this book, are they?<a href="#fnref1" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
+<li id="fn2"><p>The pattern is <code>id_&lt;encryption type&gt;</code>. <code>ed25519</code> is the standard SSH key encryption type as of this writing.<a href="#fnref2" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
 </ol>
 </section>
 
@@ -760,13 +908,13 @@ <h2 data-number="8.3" class="anchored" data-anchor-id="cheat-ssh"><span class="h
 </script>
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+      <a href="../../chapters/sec2/2-1-cloud.html" class="pagination-link">
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+      <a href="../../chapters/sec2/2-3-linux.html" class="pagination-link">
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+      <ul id="quarto-sidebar-section-2" class="collapse list-unstyled sidebar-section depth1 show">  
+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/sec2/2-1-cloud.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">7</span>&nbsp; <span class="chapter-title">The Cloud</span></span></a>
+  </div>
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+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/sec2/2-2-cmd-line.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">8</span>&nbsp; <span class="chapter-title">Customizing the command line</span></span></a>
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+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/sec2/2-3-linux.html" class="sidebar-item-text sidebar-link active">
+ <span class="menu-text"><span class="chapter-number">9</span>&nbsp; <span class="chapter-title">Intro to Linux Administration</span></span></a>
+  </div>
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+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/sec2/2-4-app-admin.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Application administration</span></span></a>
+  </div>
+</li>
+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/sec2/2-5-scale.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Server Resources and Scaling</span></span></a>
+  </div>
+</li>
+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/sec2/2-6-networking.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">12</span>&nbsp; <span class="chapter-title">Intro to Computer Networks</span></span></a>
+  </div>
+</li>
+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/sec2/2-7-dns.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">13</span>&nbsp; <span class="chapter-title">DNS allows for human-readable addresses</span></span></a>
+  </div>
+</li>
+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/sec2/2-8-ssl.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">14</span>&nbsp; <span class="chapter-title">You should use SSL/HTTPS</span></span></a>
+  </div>
+</li>
+      </ul>
+  </li>
+        <li class="sidebar-item sidebar-item-section">
+      <div class="sidebar-item-container"> 
+            <a href="../../chapters/sec3/3-0-sec-intro.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text">Making it Enterprise-Grade</span></a>
+          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-3" aria-expanded="true" aria-label="Toggle section">
+            <i class="bi bi-chevron-right ms-2"></i>
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+  <a href="../../chapters/sec3/3-1-os-ds-in-ent.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></a>
+  </div>
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+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/sec3/3-2-ent-networks.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></a>
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+</li>
+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/sec3/3-3-auth.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></a>
+  </div>
+</li>
+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/sec3/3-4-ent-servers.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></a>
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+</li>
+      </ul>
+  </li>
+        <li class="sidebar-item sidebar-item-section">
+      <div class="sidebar-item-container"> 
+            <a class="sidebar-item-text sidebar-link text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true">
+ <span class="menu-text">Appendices</span></a>
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+ <span class="menu-text"><span class="chapter-number">A</span>&nbsp; <span class="chapter-title">Auth Technologies</span></span></a>
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+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/append/lab-map.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">B</span>&nbsp; <span class="chapter-title">Lab Map</span></span></a>
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+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/append/cheatsheets.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">C</span>&nbsp; <span class="chapter-title">Cheatsheets</span></span></a>
+  </div>
+</li>
+      </ul>
+  </li>
+    </ul>
+    </div>
+</nav>
+<div id="quarto-sidebar-glass" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar,#quarto-sidebar-glass"></div>
+<!-- margin-sidebar -->
+    <div id="quarto-margin-sidebar" class="sidebar margin-sidebar">
+        <nav id="TOC" role="doc-toc" class="toc-active">
+    <h2 id="toc-title">Table of contents</h2>
+   
+  <ul>
+  <li><a href="#a-brief-history-of-linux" id="toc-a-brief-history-of-linux" class="nav-link active" data-scroll-target="#a-brief-history-of-linux"><span class="header-section-number">9.1</span> A brief history of Linux</a></li>
+  <li><a href="#bash-basics" id="toc-bash-basics" class="nav-link" data-scroll-target="#bash-basics"><span class="header-section-number">9.2</span> Bash basics</a></li>
+  <li><a href="#commands-run-on-behalf-of-users" id="toc-commands-run-on-behalf-of-users" class="nav-link" data-scroll-target="#commands-run-on-behalf-of-users"><span class="header-section-number">9.3</span> Commands run on behalf of users</a></li>
+  <li><a href="#permissions-dictate-what-users-can-do" id="toc-permissions-dictate-what-users-can-do" class="nav-link" data-scroll-target="#permissions-dictate-what-users-can-do"><span class="header-section-number">9.4</span> Permissions dictate what users can do</a></li>
+  <li><a href="#the-linux-filesystem-is-a-tree" id="toc-the-linux-filesystem-is-a-tree" class="nav-link" data-scroll-target="#the-linux-filesystem-is-a-tree"><span class="header-section-number">9.5</span> The Linux Filesystem is a tree</a>
+  <ul class="collapse">
+  <li><a href="#working-with-file-paths" id="toc-working-with-file-paths" class="nav-link" data-scroll-target="#working-with-file-paths"><span class="header-section-number">9.5.1</span> Working with file paths</a></li>
+  </ul></li>
+  <li><a href="#moving-files-and-directories" id="toc-moving-files-and-directories" class="nav-link" data-scroll-target="#moving-files-and-directories"><span class="header-section-number">9.6</span> Moving files and directories</a>
+  <ul class="collapse">
+  <li><a href="#moving-things-to-and-from-the-server" id="toc-moving-things-to-and-from-the-server" class="nav-link" data-scroll-target="#moving-things-to-and-from-the-server"><span class="header-section-number">9.6.1</span> Moving things to and from the server</a></li>
+  </ul></li>
+  <li><a href="#pipes-and-redirection" id="toc-pipes-and-redirection" class="nav-link" data-scroll-target="#pipes-and-redirection"><span class="header-section-number">9.7</span> Pipes and redirection</a></li>
+  <li><a href="#comprehension-questions" id="toc-comprehension-questions" class="nav-link" data-scroll-target="#comprehension-questions"><span class="header-section-number">9.8</span> Comprehension Questions</a></li>
+  <li><a href="#lab-set-up-a-user" id="toc-lab-set-up-a-user" class="nav-link" data-scroll-target="#lab-set-up-a-user"><span class="header-section-number">9.9</span> Lab: Set up a user</a>
+  <ul class="collapse">
+  <li><a href="#step-1-create-a-non-root-user" id="toc-step-1-create-a-non-root-user" class="nav-link" data-scroll-target="#step-1-create-a-non-root-user"><span class="header-section-number">9.9.1</span> Step 1: Create a non-root user</a></li>
+  <li><a href="#step-2-add-an-ssh-key-for-your-new-user" id="toc-step-2-add-an-ssh-key-for-your-new-user" class="nav-link" data-scroll-target="#step-2-add-an-ssh-key-for-your-new-user"><span class="header-section-number">9.9.2</span> Step 2: Add an SSH key for your new user</a></li>
+  </ul></li>
+  </ul>
+<div class="toc-actions"><div><i class="bi bi-github"></i></div><div class="action-links"><p><a href="https://github.com/akgold/do4ds/edit/main/chapters/sec2/2-3-linux.qmd" class="toc-action">Edit this page</a></p></div></div></nav>
+    </div>
+<!-- main -->
+<main class="content" id="quarto-document-content">
+
+<header id="title-block-header" class="quarto-title-block default">
+<div class="quarto-title">
+<h1 class="title"><span id="sec-linux" class="quarto-section-identifier"><span class="chapter-number">9</span>&nbsp; <span class="chapter-title">Intro to Linux Administration</span></span></h1>
+</div>
+
+
+
+<div class="quarto-title-meta">
+
+    
+  
+    
+  </div>
+  
+
+</header>
+
+<p>You’re used to interacting with a computer and a phone running MacOS or Windows or iOS or Android. But most servers don’t run any of those.</p>
+<p>Outside of personal computers and phones, <em>Linux</em> is the world’s predominant <em>operating system (OS)</em>. Almost all of the world’s embedded computers – in ATMs, cars and planes, TVs, smart thermostats, and most other gadgets and gizmos – Linux. Android actually is Linux, as is ChromeOS. Basically all of the world’s supercomputers run Linux.</p>
+<p>Most importantly for our purposes, a majority of the world’s servers also run on Linux.<a href="#fn1" class="footnote-ref" id="fnref1" role="doc-noteref"><sup>1</sup></a></p>
+<p>So in order to administer a server, you’re going to have to learn a little about Linux. In this chapter, you’ll learn about the history of Linux and about how to navigate and manipulate a server running Linux.</p>
+<section id="a-brief-history-of-linux" class="level2" data-number="9.1">
+<h2 data-number="9.1" class="anchored" data-anchor-id="a-brief-history-of-linux"><span class="header-section-number">9.1</span> A brief history of Linux</h2>
+<p>A computer’s OS defines how applications can interact with the underlying hardware. OSes dictate how files are stored and accessed, how applications are installed, how network connections work, and more.</p>
+<p>Your laptop probably runs MacOS or Windows. Neither of them is Linux. But Linux is dominant basically everywhere else. Because it’s an open source OS and in order to accommodate that huge variety of use cases and contexts, Linux comes in a wide variety of “flavors” that differ by technical attributes and licensing model. These flavors are called <em>distros</em>, short for distributions.</p>
+<p>Before the early 1970s, the market for computer hardware and software looked nothing like it does now. Computers of that era had extremely tight linkages between hardware and software. For example, there was no Microsoft Word you could use on a Dell machine or an HP machine or an Apple machine.</p>
+<p>Instead, every hardware company was also a software company. If Example Corp’s computer did text editing, it was because Example Corp had written (or commissioned) text editing software specifically for their machine. If Example Corp’s machine could run a game, Example Corp had written that game just for their computer.</p>
+<p>Then, in the early 1970s, researchers funded by AT&amp;T’s Bell Labs released <em>Unix</em> – the first operating system. Now, there was a piece of middleware that sat between the computer hardware and the end-user software.</p>
+<p>After the advent of the OS, the computer market started looking a lot more familiar to 2020s eyes. Hardware manufacturers could build machines that ran Unix and software companies could write applications that ran on Unix.</p>
+<p>The one issue (for everyone but Bell Labs) was that they were paying Bell Labs a lot of money for licenses to Unix. So in the 1980s, programmers started writing Unix-like OSes. These so-called <em>Unix clones</em> behaved just like Unix, but didn’t include any actual Unix code.<a href="#fn2" class="footnote-ref" id="fnref2" role="doc-noteref"><sup>2</sup></a></p>
+<p>In 1991, Linus Torvalds – then a 21 year-old Finnish grad student – released an open source Unix clone called Linux via a amusingly nonchalant newsgroup posting, saying, “I’m doing a (free) operating system (just a hobby, won’t be big and professional like gnu)…Any suggestions are welcome, but I won’t promise I’ll implement them&nbsp;:-).”<a href="#fn3" class="footnote-ref" id="fnref3" role="doc-noteref"><sup>3</sup></a></p>
+<p>Obviously, the Linux project outgrew that modest newgroup post. At this point there are over 600 Linux distros, reflecting both the natural fragmentation of popular open source projects, as well as disparate requirements for an OS for your car’s infotainment system versus a smartphone versus the controller for your smart thermostat.</p>
+<p>Luckily, you don’t have to know hundreds of distros. For server use, most organizations standardize on one of a handful. The most common open source distros are Ubuntu or CentOS. Red Hat Enterprise Linux (RHEL) is the most common paid distro.<a href="#fn4" class="footnote-ref" id="fnref4" role="doc-noteref"><sup>4</sup></a> Many organizations on AWS are using Amazon Linux, which is independently maintained by Amazon but was originally a RHEL derivative.<a href="#fn5" class="footnote-ref" id="fnref5" role="doc-noteref"><sup>5</sup></a></p>
+<p>Most individuals who have a choice in the matter prefer Ubuntu. It’s definitely my personal preference. It’s a little simpler and easier to configure than the others.</p>
+<div class="callout callout-style-default callout-note callout-titled">
+<div class="callout-header d-flex align-content-center">
+<div class="callout-icon-container">
+<i class="callout-icon"></i>
+</div>
+<div class="callout-title-container flex-fill">
+A note on Ubuntu Versioning
+</div>
+</div>
+<div class="callout-body-container callout-body">
+<p>Ubuntu versions are numbered by the year and month they were released. Most people use the Long Term Support (LTS) releases, which are released in April of even years.</p>
+<p>Ubuntu versions have fun alliterative names, so you’ll hear people refer to releases by name or version. As of this writing, most Ubuntu machines are running Bionic (20.04, Bionic Beaver) or Jammy (22.04, Jammy Jellyfish).</p>
+</div>
+</div>
+</section>
+<section id="bash-basics" class="level2" data-number="9.2">
+<h2 data-number="9.2" class="anchored" data-anchor-id="bash-basics"><span class="header-section-number">9.2</span> Bash basics</h2>
+<p>Linux is administered from the command line using bash or a bash alternative like zsh. The philosophy behind bash and its derivatives says that you should be able to accomplish anything you want with small programs invoked via a <em>command</em>. Each command should do just one thing, and complicated things should be accomplished by <em>composing</em> commands – taking the output from one as the input to the next.</p>
+<p>Invoking a command is done by typing the command on the command line and hitting <code>enter</code>. If you ever find yourself stuck in a situation you can’t seem to exit, <code>ctrl + c</code> will quit in most cases.</p>
+<p>Helpfully, most bash commands are an abbreviation of the word for what the command does. Unhelpfully, the letters often seem somewhat random.</p>
+<p>For example, the command to <em>list</em> the contents of a directory is <code>ls</code>, which sorta makes sense. Over time, you’ll get very comfortable with the commands you use frequently.</p>
+<p>Bash commands can be modified to behave the way you need them to.</p>
+<p><em>Command arguments</em> provide details to the command. They come after the command with a space in between. For example, if I want to run <code>ls</code> on the directory <code>/home/alex</code>, I can run <code>ls /home/alex</code> on the command line.</p>
+<p>Some commands have default arguments. For example the default argument for the <code>ls</code> command is the current directory. So if I’m in <code>/home/alex</code>, I’d get the same thing from either <code>ls</code> or <code>ls /home/alex</code>.</p>
+<p><em>Options</em> or <em>flags</em> modify how the command operates and come between the command and arguments. Flags are denoted by having one or more dashes before them. For example, <code>ls</code> allows the <code>-l</code> flag, which displays the output as a list. So, <code>ls -l /home/alex</code> would get the files in <code>/home/alex</code> as a list.</p>
+<p>Some flags themselves have <em>flag arguments</em>. For example, the <code>-D</code> flag allows specifying a format for how the datetime is displayed from <code>ls -l</code>. So running <code>ls -l -D %Y-%m-%dT%H:%M:%S /home/alex</code> lists all the files in <code>/home/alex</code> with the date-time of the last update formatted in <em>ISO-8601</em> format, which is always the correct format for dates.</p>
+<p>Bash commands are always formatted as <code>&lt;command&gt; &lt;flags + flag args&gt; &lt;command args&gt;</code>.</p>
+<p>It’s nice that this structure is standard. It’s not nice that the main argument is all the way at the end, because it makes long bash commands hard to read. To make commands more readable, you can break the command over multiple lines and include one flag or argument per line. You can tell bash you want it to continue a command after a line break by ending the line with a space and a <code>\</code>.</p>
+<p>For example, here’s that long <code>ls</code> command more nicely formatted:</p>
+<div class="code-with-filename">
+<div class="code-with-filename-file">
+<pre><strong>Terminal</strong></pre>
+</div>
+<div class="sourceCode" id="cb1"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb1-1"><a href="#cb1-1"></a><span class="op">&gt;</span> ls <span class="ex">-l</span> <span class="dt">\</span></span>
+<span id="cb1-2"><a href="#cb1-2"></a>  <span class="at">-D</span> %Y-%m-%dT%H:%M:%S <span class="dt">\</span></span>
+<span id="cb1-3"><a href="#cb1-3"></a>  /home/alex</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+</div>
+<p>All of the flags and arguments for commands can be found in the program’s <em>man page</em> (short for manual). You can access the man page for any command with <code>man &lt;command&gt;</code>. You can scroll the man page with arrow keys and exit with <code>q</code>.</p>
+<p>Bash is a real – if ugly – programming language, so you can assign variables with <code>&lt;var-name&gt;=&lt;value&gt;</code> (no spaces allowed) and access them <code>$&lt;var-name&gt;</code>. The bash version of <code>print</code> is <code>echo</code>.</p>
+<p>For example,</p>
+<div class="code-with-filename">
+<div class="code-with-filename-file">
+<pre><strong>Terminal</strong></pre>
+</div>
+<div class="sourceCode" id="cb2"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb2-1"><a href="#cb2-1"></a><span class="op">&gt;</span> MSG=<span class="st">"Hello World!"</span></span>
+<span id="cb2-2"><a href="#cb2-2"></a><span class="op">&gt;</span> echo <span class="va">$MSG</span></span>
+<span id="cb2-3"><a href="#cb2-3"></a><span class="ex">Hello</span> World!</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+</div>
+<p>For the most part, you’ll write commands directly on the command line. It’s also possible to write and run bash scripts that include conditionals, loops, and functions. Bash scripts usually end in <code>.sh</code> and are most often run with the <code>sh</code> command like <code>sh my-script.sh</code>.</p>
+<p>The advantage of writing bash scripts is that they can run basically anywhere. The disadvantage of writing bash scripts is that bash is a truly ugly programming language that is hard to debug.</p>
+</section>
+<section id="commands-run-on-behalf-of-users" class="level2" data-number="9.3">
+<h2 data-number="9.3" class="anchored" data-anchor-id="commands-run-on-behalf-of-users"><span class="header-section-number">9.3</span> Commands run on behalf of users</h2>
+<p>Whenever a program is running in Linux, it is running as a particular user who can be identified by their <em>username</em>.</p>
+<p>On any Unix-like system, the <code>whoami</code> command returns the username of the active user. So when I run <code>whoami</code> on my MacBook, I get:</p>
+<div class="code-with-filename">
+<div class="code-with-filename-file">
+<pre><strong>Terminal</strong></pre>
+</div>
+<div class="sourceCode" id="cb3"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb3-1"><a href="#cb3-1"></a><span class="op">&gt;</span> whoami                                                       </span>
+<span id="cb3-2"><a href="#cb3-2"></a><span class="ex">alexkgold</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+</div>
+<p>Usernames have to be unique on the system – but they’re not the true identifier for a user. A user is uniquely identified by their <em>user id (<code>uid</code>)</em>, which maps to all the other user attributes like username, password, home directory, groups, and more. The <code>uid</code> for a user is assigned at the time the user is created and usually don’t need to be changed or specified manually.<a href="#fn6" class="footnote-ref" id="fnref6" role="doc-noteref"><sup>6</sup></a></p>
+<p>Each human who accesses a Linux server should have their own account. In addition, many applications create <em>service account</em> users for themselves and run as those users. For example, installing RStudio Server will create a user with username <code>rstudio-server</code>. Then, when RStudio Server goes to do something – start an <code>R</code> session for example – it will do so as <code>rstudio-server</code>.</p>
+<p>User <code>uid</code>s start at 10,000 with those below 10,000 reserved for system processes. There’s also one special user – called the admin, root, sudo, or super user who gets the special <code>uid</code> 0.</p>
+<p>Users belong to <em>groups</em>, which are collections of one or more users. Each user has exactly one <em>primary</em> <em>group</em> and can be a member of secondary groups.<a href="#fn7" class="footnote-ref" id="fnref7" role="doc-noteref"><sup>7</sup></a> By default, each user’s primary group is the same as their username.</p>
+<p>Like a user has a <code>uid</code>, a group has a <code>gid</code>. User <code>gid</code>s start at 100.</p>
+<p>You can see a user’s username, <code>uid</code>, groups, and <code>gid</code> with the <code>id</code> command. On my MacBook, I’m a member of a number of different groups, with the primary group <code>staff</code>.</p>
+<div class="code-with-filename">
+<div class="code-with-filename-file">
+<pre><strong>Terminal</strong></pre>
+</div>
+<div class="sourceCode" id="cb4"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb4-1"><a href="#cb4-1"></a><span class="op">&gt;</span> id                                                                </span>
+<span id="cb4-2"><a href="#cb4-2"></a><span class="va">uid</span><span class="op">=</span>501<span class="kw">(</span><span class="ex">alexkgold</span><span class="kw">)</span> <span class="va">gid</span><span class="op">=</span>20<span class="kw">(</span><span class="ex">staff</span><span class="kw">)</span> <span class="va">groups</span><span class="op">=</span>20<span class="kw">(</span><span class="ex">staff</span><span class="kw">)</span><span class="ex">,12</span><span class="er">(</span><span class="ex">everyone</span><span class="kw">)</span><span class="ex">,61</span><span class="er">(</span><span class="ex">localaccounts</span><span class="kw">)</span><span class="ex">,79</span><span class="er">(</span><span class="ex">_appserverusr</span><span class="kw">)</span><span class="ex">,80</span><span class="er">(</span><span class="ex">admin</span><span class="kw">)</span><span class="ex">,81</span><span class="er">(</span><span class="ex">_appserveradm</span><span class="kw">)</span><span class="ex">,98</span><span class="er">(</span><span class="ex">_lpadmin</span><span class="kw">)</span><span class="ex">,701</span><span class="er">(</span><span class="ex">com.apple.sharepoint.group.1</span><span class="kw">)</span><span class="ex">,33</span><span class="er">(</span><span class="ex">_appstore</span><span class="kw">)</span><span class="ex">,100</span><span class="er">(</span><span class="ex">_lpoperator</span><span class="kw">)</span><span class="ex">,204</span><span class="er">(</span><span class="ex">_developer</span><span class="kw">)</span><span class="ex">,250</span><span class="er">(</span><span class="ex">_analyticsusers</span><span class="kw">)</span><span class="ex">,395</span><span class="er">(</span><span class="ex">com.apple.access_ftp</span><span class="kw">)</span><span class="ex">,398</span><span class="er">(</span><span class="ex">com.apple.access_screensharing</span><span class="kw">)</span><span class="ex">,400</span><span class="er">(</span><span class="ex">com.apple.access_remote_ae</span><span class="kw">)</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+</div>
+<p>If you ever need to add users to a server, the easiest way is with the <code>useradd</code> command. Once you have a user, you may need to change the password, which you can do at any time with the <code>passwd</code> command. Both <code>useradd</code> and <code>passwd</code> start interactive prompts, so you don’t need to do much more than run those commands.</p>
+<p>If you ever need to alter a user – the most common task being to add a user to a group, you would use the <code>usermod</code> command with the <code>-aG</code> flag.</p>
+</section>
+<section id="permissions-dictate-what-users-can-do" class="level2" data-number="9.4">
+<h2 data-number="9.4" class="anchored" data-anchor-id="permissions-dictate-what-users-can-do"><span class="header-section-number">9.4</span> Permissions dictate what users can do</h2>
+<p>In Linux, everything you can interact with is just a file. Every log – file. Every picture – file. Every application – file. Every configuration – file.</p>
+<p>So determining whether a user can take an action is really a question of whether they have the right permissions on a particular file.</p>
+<p>Basic Linux permissions (called <em>POSIX permissions</em>) consist of a 3x3 matrix of read, write, and execute for the owner, the owning group, and everyone else. Read means the user can see the contents of a file, write means the user can save a changed version of a file, and execute means they can run the file as a program.</p>
+<div class="callout callout-style-default callout-note callout-titled">
+<div class="callout-header d-flex align-content-center">
+<div class="callout-icon-container">
+<i class="callout-icon"></i>
+</div>
+<div class="callout-title-container flex-fill">
+Note
+</div>
+</div>
+<div class="callout-body-container callout-body">
+<p>There are more complex ways to manage Linux permissions. For example, you might hear about Access Control Lists (ACLs). They’re beyond the scope of this book.</p>
+<p>There is more information on different ways organizations manage users and what they’re allowed to do in <a href="../sec3/3-3-auth.html">Chapter&nbsp;<span>17</span></a>, which is all about auth.</p>
+</div>
+</div>
+<p>For example, here’s a set of permissions that you might have for a program if you wanted anyone to be able to run it, group members to inspect it, and only the owner to change it.</p>
+<p><img src="./images/perms-ex.png" class="img-fluid" alt="A 3x3 grid read, write, execute, on one side and owner, owning group, and everyone else at the top. Green checks in all of the execute, write for the owner, and read for owner and owning group. Red xs everywhere else." width="400"></p>
+<p>Directories also have permissions – read allows the user see what’s in the directory, write allows the user to alter what’s in the directory, and execute allows the user to enter the directory.</p>
+<p>File permissions and directory permissions don’t have to match. For example, a user could have read permissions on a directory, so they could see the names of the files, but not actually have read permissions on any of the files, so they can’t look at the contents.</p>
+<p>When you’re working on the command line, you don’t get a little grid of permissions. Instead they’re expressed in one of two ways. The first is the string representation, which is a 10-character string that looks something like <code>-rw-r–r--</code>.</p>
+<p>The first character indicates the type of file: most often <code>-</code> for normal (file) or <code>d</code> for a directory.</p>
+<p>The next nine characters are indicators for the three permissions for the user, the group, and everyone else. There will be an <code>r</code> for read, a <code>w</code> for write, and an <code>x</code> for execute or <code>-</code> to indicate that they don’t have the permission.</p>
+<p>So the permissions in the graphic would be <code>-rwxr-x--x</code> for a file and <code>drwxr-x--x</code> for a directory.</p>
+<p>The best way to get these permissions is to run the <code>ls -l</code> command.</p>
+<div class="code-with-filename">
+<div class="code-with-filename-file">
+<pre><strong>Terminal</strong></pre>
+</div>
+<div class="sourceCode" id="cb5"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb5-1"><a href="#cb5-1"></a><span class="op">&gt;</span> ls <span class="ex">-l</span>                                                           </span>
+<span id="cb5-2"><a href="#cb5-2"></a><span class="ex">-rw-r--r--</span>  1 alexkgold  staff     28 Oct 30 11:05 config.py</span>
+<span id="cb5-3"><a href="#cb5-3"></a><span class="ex">-rw-r--r--</span>  1 alexkgold  staff   2330 May  8  2017 credentials.json</span>
+<span id="cb5-4"><a href="#cb5-4"></a><span class="ex">-rw-r--r--</span>  1 alexkgold  staff   1083 May  8  2017 main.py</span>
+<span id="cb5-5"><a href="#cb5-5"></a><span class="ex">drwxr-xr-x</span> 33 alexkgold  staff   1056 May 24 13:08 tests</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+</div>
+<p>Each line starts with the string representation of the permissions followed by the owner and group so you can easily understand who should be able to access that file or directory.</p>
+<p>All of the files in this directory are owned by <code>alexkgold</code>. Only the owner (<code>alexkgold</code>) has write permission, but everyone has read permission. In addition, there’s a <code>tests</code> directory, with read and execute for everyone and write only for <code>alexkgold</code>.</p>
+<p>In the course of administering a server, you will probably need to change a file’s permissions. You can do so using the <code>chmod</code> command.</p>
+<p>For <code>chmod</code>, permissions are indicated as a three digit number, like <code>600</code>, where the first digit is the permission for the user, the second for the group, and the third for everyone else. To get the right number, you sum the permissions as follows: 4 for read, 2 for write, and 1 for execute. You can check for yourself that any set of permissions is uniquely identified by a number between 1 and 7.<a href="#fn8" class="footnote-ref" id="fnref8" role="doc-noteref"><sup>8</sup></a></p>
+<p>So to implement the permissions from the graphic, you’d want the permission set <code>751</code> to give the user full permissions (4 + 2 + 1), read and execute (4 + 1) to the group, and execute only (1) to everyone else.</p>
+<div class="callout callout-style-default callout-note callout-titled">
+<div class="callout-header d-flex align-content-center">
+<div class="callout-icon-container">
+<i class="callout-icon"></i>
+</div>
+<div class="callout-title-container flex-fill">
+Note
+</div>
+</div>
+<div class="callout-body-container callout-body">
+<p>If you spend any time administering a Linux server, you almost certainly will at some point find yourself running into a problem and applying <code>chmod 777</code> out of frustration to rule out a permissions issue.</p>
+<p>I can’t tell you not to do this – we’ve all been there. But if it’s something important, be sure you change it back once you’re finished figuring out what’s going on.</p>
+</div>
+</div>
+<p>In some cases you might actually want to change the owner or group of a file. You can change users and groups with either names or ids. You can do so using the <code>chown</code> command. Changing users just uses the username and changing groups get prefixed with a colon.</p>
+<p>In some cases, you might not be the correct user to take a particular action. If you want to change the user you are, you can use the <code>su</code> (switch user) command. You’ll be prompted for a password to make sure you’re allowed.</p>
+<p>The admin or root user has full permissions on every file and there are some actions that only the root user can do. When you need to do root-only things, you usually don’t want to <code>su</code> to be the root user. It’s too powerful. Plus if you have user-level configuration, it all gets left behind.</p>
+<p>Instead, individual users can be granted the power to temporarily assume root privileges without changing to be the root user. This is accomplished by making them members of the admin group. If a user is a member of the admin group, they can prefix commands with <code>sudo</code> to run those commands with root privileges.</p>
+<p>The name of the admin group varies by distro. In Ubuntu, the group is called <code>sudo</code>.</p>
+</section>
+<section id="the-linux-filesystem-is-a-tree" class="level2" data-number="9.5">
+<h2 data-number="9.5" class="anchored" data-anchor-id="the-linux-filesystem-is-a-tree"><span class="header-section-number">9.5</span> The Linux Filesystem is a tree</h2>
+<p>Regardless of which Linux distro you’re running, understanding where to find things on your system is crucial.</p>
+<p>All of the information available to a computer is indexed by its <em>filesystem</em>, which is made up of <em>directories</em> or <em>folders</em>, which are containers for other directories and for files.</p>
+<p>On your laptop, you’re probably used to browsing the filesystem with your mouse. On your phone, the filesystem is completely obscured by apps, but it’s there.</p>
+<p>On a Linux server, the only way to traverse the filesystem is with written commands. Having a good mental model for what the filesystem looks like is, therefore, really important.</p>
+<p>On Linux, the entire filesystem is a tree (or perhaps an upside-down tree). Every directory is contained in by a <em>parent directory</em>, and may contain one or more <em>children</em> or <em>sub-directories</em>. The <em>root directory, <code>/</code></em> is the base of the tree and is its own parent. A <code>/</code> in between two directories means that it’s a sub-directory.</p>
+<p><img src="images/directories.png" class="img-fluid" alt="A tree of directories. / is the root, /home is a sub directory, /home/alex is a sub-sub-directory, and /etc is another sub-directory." width="600"></p>
+<p>Every directory is a sub-directory of <code>/</code> or a sub-directory of a sub-directory of <code>/</code> or…you get the picture. So the <code>/home/alex</code> <em>file path</em> defines a particular location, which is the <code>alex</code> sub-directory of <code>/home</code>, which is a sub-directory of the root directory, <code>/</code>.</p>
+<div class="callout callout-style-default callout-tip callout-titled">
+<div class="callout-header d-flex align-content-center">
+<div class="callout-icon-container">
+<i class="callout-icon"></i>
+</div>
+<div class="callout-title-container flex-fill">
+Tip
+</div>
+</div>
+<div class="callout-body-container callout-body">
+<p>It’s never necessary, but sometimes the tree-like layout for a directory is helpful. The <code>tree</code> utility can show you one. It doesn’t always come pre-installed, so you might have to install it.</p>
+</div>
+</div>
+<p>Because the entire Linux filesystem is based at <code>/</code>, it doesn’t matter what physical or virtual disks you have attached to your system. They will fall somewhere under the main filesystem (often inside <code>/mnt</code>).</p>
+<p>This will be familiar to MacOS users, because MacOS is based on an operating system called BSD that, like Linux, is a Unix clone.</p>
+<p>If you’re familiar with Windows, the Linux filesystem may seem a little strange.</p>
+<p>In Linux, each computer has exactly one filesystem, which is based at the root, <code>/</code>. Network shares or other types of volumes can be mounted somewhere on the filesystem, often below <code>/mnt</code>, but the fact that they’re on separate drives is obscured from the user.</p>
+<p>In Windows, each physical or logical disk has its own filesystem with its own root. You’re probably familiar with <code>C:</code> as your main filesystem. Your machine may also have a <code>D:</code> drive. If you’ve got network share drives, they’re likely at <code>M:</code> or <code>N:</code> or <code>P:</code>.</p>
+<p>One other difference is that Windows uses <code>\</code> to separate file path elements rather than <code>/</code>. This used to be a big deal, but newer versions of Windows accept file paths using <code>/</code>.</p>
+<section id="working-with-file-paths" class="level3" data-number="9.5.1">
+<h3 data-number="9.5.1" class="anchored" data-anchor-id="working-with-file-paths"><span class="header-section-number">9.5.1</span> Working with file paths</h3>
+<p>Whenever a command runs, it runs at a particular path in the filesystem, called the <em>working directory</em>. You can get the absolute path to your working directory with the <code>pwd</code> command, which is an abbreviation for <em>print working directory</em>.</p>
+<p>When you want a command to run the same irrespective of where it’s run from, it’s best to use an <em>absolute path</em>, which is a path specified relative to the root. They operate the same irrespective of the current working directory. Absolute file paths are easy to recognize because they always start with <code>/</code>.</p>
+<p>Sometimes it’s convenient to use a <em>relative</em> file path, which starts at the working directory, denoted by <code>.</code>. So, for example, if I want to access the <code>data</code> subdirectory of the working directory, that would be available at <code>./data</code>.</p>
+<p>The working directory’s parent is at <code>..</code>. So, you could see everything in the parent directory of your current working directory with <code>ls ..</code> or its parent with <code>ls ../..</code>.</p>
+<p>All accounts that represent actual humans should have a <em>home directory</em>, which usually livelive inside <code>/home</code>.</p>
+<p>The home directory and all its contents are owned by the user to whom it belongs. The home directory is the user’s space to store the things they need, including user-specific configuration. When navigating the file system, the user can find their home directory is at <code>~</code>.</p>
+<p>Along with being able to inspect directories with <code>ls</code>, it’s useful to be able to change your working directory with the <code>cd</code> command, short for <em>change directory</em>. You can use either absolute or relative file paths with <code>cd</code>. So if you were in <code>/home/alex</code> and wanted to navigate to <code>/home</code>, either <code>cd ..</code> or <code>cd /home</code> would work.</p>
+<p>Some files or directories are <em>hidden</em> so they don’t appear in a normal <code>ls</code>. You know a file or directory is hidden because its name starts with <code>.</code>. Hidden files are usually configuration files that you aren’t manipulating in normal usage. These aren’t secret or protected in any way, they’re just skipped by <code>ls</code> for convenience. If you want to display all files in a directory, including hidden ones, you can use the <code>-a</code> flag (for all) with <code>ls</code>.</p>
+<p>You’ve already seen a couple of hidden files in this book – your GitHub Action was configured in the <code>.github</code> directory and your Prezto configuration was done in the <code>.zpreztorc</code> file. You might also be familiar with <code>.gitignore</code>, <code>.Rprofile</code>, and <code>.Renviron</code>.</p>
+</section>
+</section>
+<section id="moving-files-and-directories" class="level2" data-number="9.6">
+<h2 data-number="9.6" class="anchored" data-anchor-id="moving-files-and-directories"><span class="header-section-number">9.6</span> Moving files and directories</h2>
+<p>You will frequently need to change where files are on your system, including copying, deleting, moving, and more.</p>
+<p>You can copy a file or directory from one place to another using the <code>cp</code> command. <code>cp</code> leaves behind the old file or directory and adds the new one at the specified location. You can use the <code>-r</code> flag to recursively copy everything in a directory.</p>
+<p>You can move a file with the <code>mv</code> command, which does not leave the old file behind. If you want to remove a file entirely, you can use the <code>rm</code> command. The <code>-r</code> (recursive) flag can be used with <code>rm</code> to remove everything within a directory and the <code>-f</code> (force) flag can skip <code>rm</code> double checking you really want to do this.</p>
+<div class="callout callout-style-default callout-warning callout-titled">
+<div class="callout-header d-flex align-content-center">
+<div class="callout-icon-container">
+<i class="callout-icon"></i>
+</div>
+<div class="callout-title-container flex-fill">
+Warning
+</div>
+</div>
+<div class="callout-body-container callout-body">
+<p>Be very careful with the <code>rm</code> command, especially with <code>-rf</code>.</p>
+<p>There’s no recycle bin. Things that are deleted are instantly deleted forever.</p>
+</div>
+</div>
+<p>If you want to make a directory, <code>mkdir</code> makes a file path. It can be used with relative or absolute file paths, and can include multiple layers of paths to create. For example, if you’re in <code>/home/alex</code>, you could <code>mkdir project1/data</code> to make a <code>project1</code> directory and <code>data</code> sub-directory.</p>
+<p>The <code>mkdir</code> command throws an error if you try to create a path that includes some directories that already exist – for example if <code>project1</code> already existed in the example above. The <code>-p</code> flag can be handy to create only the parts of the path that don’t exist.</p>
+<p>Sometimes it’s useful to operate on every file inside a directory. You can get every file that matches a pattern with the wildcard, <code>*</code>. You can also do partial matching with the wildcard to get all the files that match part of a pattern.</p>
+<p>For example, let’s say I have a <code>/data</code> directory and I want to put a copy of only the <code>.csv</code> files inside into a new <code>data-copy</code> sub-directory. I could do the following:</p>
+<div class="code-with-filename">
+<div class="code-with-filename-file">
+<pre><strong>Terminal</strong></pre>
+</div>
+<div class="sourceCode" id="cb6"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb6-1"><a href="#cb6-1"></a><span class="op">&gt;</span> mkdir <span class="ex">-p</span> /data/data-copy</span>
+<span id="cb6-2"><a href="#cb6-2"></a><span class="op">&gt;</span> cp <span class="ex">/data/*.csv</span> /data/data-copy</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+</div>
+<section id="moving-things-to-and-from-the-server" class="level3" data-number="9.6.1">
+<h3 data-number="9.6.1" class="anchored" data-anchor-id="moving-things-to-and-from-the-server"><span class="header-section-number">9.6.1</span> Moving things to and from the server</h3>
+<p>It’s very common to have a file on your server you want to move to your desktop or vice versa. There are a few different ways to move files and directories.</p>
+<p>If you’re moving multiple files, it’s easier to combine them into a single object and move that. The <code>tar</code> command turns a set of files or whole directory into a single archive file, usually with the file suffix <code>.tar.gz</code>. Creating an archive also does some compression. The amount depends on the content.</p>
+<p>In my opinion, <code>tar</code> is a rare failure of bash to provide standalone commands for anything you need to do. <code>tar</code> is used to both create and unpack (extract) archive files. Telling it which one requires the use of several flags. You’ll basically never use <code>tar</code> without a bunch of flags and the incantation is hard to remember. I google it every time I use it. The flags you’ll use most often are in the <a href="@sec-append-cheat">cheatsheet in the appendix</a>.</p>
+<p>You can move files to or from a server with the <code>scp</code> command. <code>scp</code> – short for secure copy – is basically <code>cp</code>, but with an SSH connection in the middle.<a href="#fn9" class="footnote-ref" id="fnref9" role="doc-noteref"><sup>9</sup></a></p>
+<p>Since <code>scp</code> establishes an SSH connection, you need to make the request to somewhere that is accepting SSH connections. That means that whether you’re copying something to or from a server, you’ll run <code>scp</code> from a regular terminal on your laptop, not one that’s already SSH-ed into your server.</p>
+<p>Regular <code>ssh</code> options work with <code>scp</code>, like <code>-i</code> and <code>-v</code>.</p>
+</section>
+</section>
+<section id="pipes-and-redirection" class="level2" data-number="9.7">
+<h2 data-number="9.7" class="anchored" data-anchor-id="pipes-and-redirection"><span class="header-section-number">9.7</span> Pipes and redirection</h2>
+<p>You can always copy and paste command outputs or write them to a file, but it can also be helpful to just chain a few commands together. Linux provides a few handy <em>operators</em> you can use to make this easy.</p>
+<p>The simplest operator is the <em>pipe</em> <code>|</code>, which just takes the output of one command and makes it the input for the next command.</p>
+<p>For example, you might want to see how many files are in a directory. The <code>wc -l</code> (word count, lines) command counts lines, so you could do <code>ls | wc -l</code> since each file returned by <code>ls</code> is counted as a line.</p>
+<div class="callout callout-style-default callout-note callout-titled">
+<div class="callout-header d-flex align-content-center">
+<div class="callout-icon-container">
+<i class="callout-icon"></i>
+</div>
+<div class="callout-title-container flex-fill">
+Ceci n’est pas une pipe?
+</div>
+</div>
+<div class="callout-body-container callout-body">
+<p>The pipe should feel extremely familiar to R users.</p>
+<p>The pipe from the <code>{magrittr}</code> package, <code>%&gt;%</code>, was introduced in 2013, and is a popular part of the <code>{tidyverse}</code>.<a href="#fn10" class="footnote-ref" id="fnref10" role="doc-noteref"><sup>10</sup></a> The <code>{magrittr}</code> pipe was inspired by both the Unix (Linux) pipe and the pipe operator in the <code>F#</code> programming language.</p>
+<p>Due to its popularity, the pipe <code>|&gt;</code> was formally added to the base R language in R 4.1 in 2021.</p>
+</div>
+</div>
+<p>There are a few operators that write the output of the left hand side into a file.</p>
+<p>The <code>&gt;</code> command takes the output of a command on the left and writes it as a new file. If the file you specify already exists, it will be overwritten.</p>
+<p>If you want to append the new text, rather than overwrite, <code>&gt;&gt;</code> appends to the end of the file. I generally default to <code>&gt;&gt;</code>, because it’ll create a new file if one doesn’t exist, and I usually don’t mean to overwrite what’s there.</p>
+<p>A common reason you might want to do this is to add something to the end of your <code>.gitignore</code>. For example, if you want to add your <code>.env</code> file to your <code>.gitignore</code>, you could do that with <code>echo .env &gt;&gt; .gitignore</code>.<a href="#fn11" class="footnote-ref" id="fnref11" role="doc-noteref"><sup>11</sup></a> Another great usage is to add a new public key to your <code>.ssh/authorized_keys</code> file.</p>
+<p>There are times when you want to make files or directories with nothing in them. The <code>touch</code> command makes a blank file at the specified file path. If you <code>touch</code> a preexisting file, it updates the time the file was last updated without actually making any changes. This can be useful because some applications look at the timestamp on files to see if action is needed.</p>
+</section>
+<section id="comprehension-questions" class="level2" data-number="9.8">
+<h2 data-number="9.8" class="anchored" data-anchor-id="comprehension-questions"><span class="header-section-number">9.8</span> Comprehension Questions</h2>
+<ol type="1">
+<li>What are the parts of a bash command?</li>
+<li>Where do commands run? How do you know where they’re going to run or specify a relative path?</li>
+<li>How can you copy, move, or delete a file? What about to or from a server?</li>
+<li>Create a mind map of the following terms: Operating System, Windows, MacOS, Unix, Linux, Distro, Ubuntu</li>
+<li>What are the 3x3 options for Linux file permissions? How are they indicated in an <code>ls -l</code> command?</li>
+</ol>
+</section>
+<section id="lab-set-up-a-user" class="level2" data-number="9.9">
+<h2 data-number="9.9" class="anchored" data-anchor-id="lab-set-up-a-user"><span class="header-section-number">9.9</span> Lab: Set up a user</h2>
+<p>When you use your server’s <code>.pem</code> key, you login as the root user, but that’s too much power to acquire on a regular basis. Additionally, since your server is probably for multiple people, you’re going to want to create users for them.</p>
+<p>In this lab, you’ll create a regular user for yourself and add an SSH key for them so you can directly log in from your personal computer.</p>
+<section id="step-1-create-a-non-root-user" class="level3" data-number="9.9.1">
+<h3 data-number="9.9.1" class="anchored" data-anchor-id="step-1-create-a-non-root-user"><span class="header-section-number">9.9.1</span> Step 1: Create a non-root user</h3>
+<p>Let’s create a user using the <code>adduser</code> command. This will walk us through a set of prompts to create a new user with a home directory and a password. Feel free to add any information you want – or to leave it blank – when prompted.</p>
+<p>I’m going to use the username <code>test-user</code>. If you want to be able to copy/paste commands, I’d advise doing the same. If you were creating users based on real humans, I’d advise using their names.</p>
+<div class="code-with-filename">
+<div class="code-with-filename-file">
+<pre><strong>Terminal</strong></pre>
+</div>
+<div class="sourceCode" id="cb7"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb7-1"><a href="#cb7-1"></a><span class="op">&gt;</span> adduser <span class="ex">test-user</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+</div>
+<p>We want this new user to be able to adopt root privileges so let’s add them to the <code>sudo</code> group with</p>
+<div class="code-with-filename">
+<div class="code-with-filename-file">
+<pre><strong>Terminal</strong></pre>
+</div>
+<div class="sourceCode" id="cb8"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb8-1"><a href="#cb8-1"></a><span class="op">&gt;</span> usermod <span class="ex">-aG</span> sudo test-user</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+</div>
+</section>
+<section id="step-2-add-an-ssh-key-for-your-new-user" class="level3" data-number="9.9.2">
+<h3 data-number="9.9.2" class="anchored" data-anchor-id="step-2-add-an-ssh-key-for-your-new-user"><span class="header-section-number">9.9.2</span> Step 2: Add an SSH key for your new user</h3>
+<p>Let’s register an SSH key for the new user by adding the key from the last lab to the server user’s <code>authorized_users</code> file.</p>
+<p>First, you need to get your public key to the server using scp.</p>
+<p>For me, the command looks like this</p>
+<div class="code-with-filename">
+<div class="code-with-filename-file">
+<pre><strong>Terminal</strong></pre>
+</div>
+<div class="sourceCode" id="cb9"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb9-1"><a href="#cb9-1"></a><span class="op">&gt;</span> scp <span class="ex">-i</span> ~/Documents/do4ds-lab/do4ds-lab-key.pem <span class="dt">\ </span></span>
+<span id="cb9-2"><a href="#cb9-2"></a>  <span class="ex">~/.ssh/id_ed25519.pub</span> <span class="dt">\</span></span>
+<span id="cb9-3"><a href="#cb9-3"></a>  ubuntu@<span class="va">$SERVER_ADDRESS</span>:/home/ubuntu</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+</div>
+<p>Note that I’m copying the public key, but SSH access is still using the server’s <code>.pem</code> key because I don’t have another key registered yet.</p>
+<p>Now the public key is on the server, but it’s in the <code>ubuntu</code> user’s home directory. You’ll need to do the following:</p>
+<ol type="1">
+<li><p>Create <code>.ssh/authorized_keys</code> in <code>test-user</code>’s home directory.</p></li>
+<li><p>Copy the contents of the public key you uploaded into the <code>authorized_keys</code> file (recall <code>&gt;&gt;</code>).</p></li>
+<li><p>Make sure the <code>.ssh</code> directory and <code>authorized_keys</code> files are owned by <code>test-user</code> with <code>700</code> permissions on <code>.ssh</code> and <code>600</code> on <code>authorized_keys</code>.</p></li>
+</ol>
+<p>You could do this all as the admin user, but I’d recommend switching to being <code>test-user</code> at some point with the <code>su</code> command.</p>
+<div class="callout callout-style-default callout-tip callout-titled">
+<div class="callout-header d-flex align-content-center">
+<div class="callout-icon-container">
+<i class="callout-icon"></i>
+</div>
+<div class="callout-title-container flex-fill">
+Tip
+</div>
+</div>
+<div class="callout-body-container callout-body">
+<p>If you run into trouble assuming <code>sudo</code> with your new user, try exiting SSH and coming back. Sometimes these changes aren’t picked up until you restart the shell.</p>
+</div>
+</div>
+<p>Once you’ve done all this, you should be able to log in from your personal computer with <code>ssh test-user@$SERVER_ADDRESS</code>.</p>
+<p>Now that we’re all set up, you should store the <code>.pem</code> key somewhere safe and never use it to log in again.</p>
+
+
+</section>
+</section>
+<section id="footnotes" class="footnotes footnotes-end-of-document" role="doc-endnotes">
+<hr>
+<ol>
+<li id="fn1"><p>The remainder are mostly Windows servers. There are a few other OSes you might encounter, like Oracle Solaris. There is a product called <em>Mac Server</em>, but it’s just a program for managing Mac desktops and iOS devices, not a server OS.</p>
+<p>There are also versions on Linux that run on desktop computers. Despite the best efforts of many hopeful nerds, desktop Linux is pretty much only used by professional computer people.<a href="#fnref1" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
+<li id="fn2"><p>Or at least they weren’t supposed to. There’s an interesting history of lawsuits, especially around whether the BSD OS illegally included Unix code.<a href="#fnref2" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
+<li id="fn3"><p>More in the <a href="https://en.wikipedia.org/wiki/History_of_Linux">History of Linux Wikipedia article</a>.</p>
+<p>Pedants will scream that the original release of Linux was just the operating system <em>kernel</em>, not a full operating system like Unix. Duly noted, now go away.<a href="#fnref3" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
+<li id="fn4"><p>RHEL and CentOS are related operating systems, but that relationship has changed a lot in the last few years. The details are somewhat complicated, but most people expect less adoption of CentOS in enterprise settings going forward.<a href="#fnref4" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
+<li id="fn5"><p>As I’m writing this, Amazon Linux 2 is popular, but Amazon Linux 2023 (AL2023) was recently released. I’d expect AL2023 or it’s successor to be dominant by the time you read this.<a href="#fnref5" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
+<li id="fn6"><p>The one exception to this is when you’ve got the same user accessing resources across multiple machines. Then the <code>uid</code>s have to match. If you’re worrying about this kind of thing, it’s probably time to bring in a professional IT/Admin.<a href="#fnref6" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
+<li id="fn7"><p>Depending on your version of Linux, there may be a limit of 16 groups per user.<a href="#fnref7" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
+<li id="fn8"><p>Clever eyes may realize that this is just the base-10 representation of a three-digit binary number.<a href="#fnref8" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
+<li id="fn9"><p>It’s worth noting that <code>scp</code> is now considered “insecure and outdated”. The ways it is insecure are rather obscure and not terribly relevant for most people. But if you’re moving a lot of data, you may want something faster. If so, I’d recommend more modern options like <code>sftp</code> and <code>rsync</code>. I probably wouldn’t bother if you’re only occasionally <code>scp</code>-ing small files to or from your server.<a href="#fnref9" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
+<li id="fn10"><p>The title of this callout box is also the tagline for the <code>{magrittr}</code> package.<a href="#fnref10" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
+<li id="fn11"><p>Note that <code>echo</code> is needed so that the <code>.env</code> gets repeated as a character string. Otherwise <code>.env</code> would be treated as a command.<a href="#fnref11" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
+</ol>
+</section>
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+ <span class="menu-text"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Application administration</span></span></a>
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+ <span class="menu-text"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Server Resources and Scaling</span></span></a>
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+ <span class="menu-text"><span class="chapter-number">12</span>&nbsp; <span class="chapter-title">Intro to Computer Networks</span></span></a>
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+ <span class="menu-text"><span class="chapter-number">13</span>&nbsp; <span class="chapter-title">DNS allows for human-readable addresses</span></span></a>
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+            <a href="../../chapters/sec3/3-0-sec-intro.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text">Making it Enterprise-Grade</span></a>
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+ <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></a>
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+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/sec3/3-2-ent-networks.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></a>
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+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/sec3/3-3-auth.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></a>
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+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/sec3/3-4-ent-servers.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></a>
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+ <span class="menu-text"><span class="chapter-number">A</span>&nbsp; <span class="chapter-title">Auth Technologies</span></span></a>
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+        <nav id="TOC" role="doc-toc" class="toc-active">
+    <h2 id="toc-title">Table of contents</h2>
+   
+  <ul>
+  <li><a href="#linux-app-install-config" id="toc-linux-app-install-config" class="nav-link active" data-scroll-target="#linux-app-install-config"><span class="header-section-number">10.1</span> Linux app install + config</a>
+  <ul class="collapse">
+  <li><a href="#application-configuration" id="toc-application-configuration" class="nav-link" data-scroll-target="#application-configuration"><span class="header-section-number">10.1.1</span> Application configuration</a></li>
+  <li><a href="#where-to-find-application-files" id="toc-where-to-find-application-files" class="nav-link" data-scroll-target="#where-to-find-application-files"><span class="header-section-number">10.1.2</span> Where to find application files</a></li>
+  <li><a href="#command-line-configuration-with-vim-and-nano" id="toc-command-line-configuration-with-vim-and-nano" class="nav-link" data-scroll-target="#command-line-configuration-with-vim-and-nano"><span class="header-section-number">10.1.3</span> Command line configuration with vim and nano</a></li>
+  </ul></li>
+  <li><a href="#reading-logs" id="toc-reading-logs" class="nav-link" data-scroll-target="#reading-logs"><span class="header-section-number">10.2</span> Reading logs</a></li>
+  <li><a href="#running-the-right-commands" id="toc-running-the-right-commands" class="nav-link" data-scroll-target="#running-the-right-commands"><span class="header-section-number">10.3</span> Running the right commands</a></li>
+  <li><a href="#running-applications-as-services" id="toc-running-applications-as-services" class="nav-link" data-scroll-target="#running-applications-as-services"><span class="header-section-number">10.4</span> Running applications as services</a>
+  <ul class="collapse">
+  <li><a href="#running-docker-containers-as-a-service" id="toc-running-docker-containers-as-a-service" class="nav-link" data-scroll-target="#running-docker-containers-as-a-service"><span class="header-section-number">10.4.1</span> Running Docker containers as a service</a></li>
+  </ul></li>
+  <li><a href="#managing-r-and-python" id="toc-managing-r-and-python" class="nav-link" data-scroll-target="#managing-r-and-python"><span class="header-section-number">10.5</span> Managing R and Python</a>
+  <ul class="collapse">
+  <li><a href="#python-specific-considerations" id="toc-python-specific-considerations" class="nav-link" data-scroll-target="#python-specific-considerations"><span class="header-section-number">10.5.1</span> Python-specific considerations</a></li>
+  <li><a href="#r-specific-considerations" id="toc-r-specific-considerations" class="nav-link" data-scroll-target="#r-specific-considerations"><span class="header-section-number">10.5.2</span> R-specific considerations</a></li>
+  </ul></li>
+  <li><a href="#managing-system-libraries" id="toc-managing-system-libraries" class="nav-link" data-scroll-target="#managing-system-libraries"><span class="header-section-number">10.6</span> Managing System Libraries</a></li>
+  <li><a href="#comprehension-questions" id="toc-comprehension-questions" class="nav-link" data-scroll-target="#comprehension-questions"><span class="header-section-number">10.7</span> Comprehension Questions</a></li>
+  <li><a href="#lab-installing-applications" id="toc-lab-installing-applications" class="nav-link" data-scroll-target="#lab-installing-applications"><span class="header-section-number">10.8</span> Lab: Installing Applications</a>
+  <ul class="collapse">
+  <li><a href="#step-1-install-python" id="toc-step-1-install-python" class="nav-link" data-scroll-target="#step-1-install-python"><span class="header-section-number">10.8.1</span> Step 1: Install Python</a></li>
+  <li><a href="#step-2-install-r" id="toc-step-2-install-r" class="nav-link" data-scroll-target="#step-2-install-r"><span class="header-section-number">10.8.2</span> Step 2: Install R</a></li>
+  <li><a href="#step-3-install-jupyerhub-jupyterlab" id="toc-step-3-install-jupyerhub-jupyterlab" class="nav-link" data-scroll-target="#step-3-install-jupyerhub-jupyterlab"><span class="header-section-number">10.8.3</span> Step 3: Install JupyerHub + JupyterLab</a></li>
+  <li><a href="#step-4-daemonize-jupyterhub" id="toc-step-4-daemonize-jupyterhub" class="nav-link" data-scroll-target="#step-4-daemonize-jupyterhub"><span class="header-section-number">10.8.4</span> Step 4: Daemonize JupyterHub</a></li>
+  <li><a href="#step-5-install-rstudio-server" id="toc-step-5-install-rstudio-server" class="nav-link" data-scroll-target="#step-5-install-rstudio-server"><span class="header-section-number">10.8.5</span> Step 5: Install RStudio Server</a></li>
+  <li><a href="#step-6-run-the-penguin-api-from-docker" id="toc-step-6-run-the-penguin-api-from-docker" class="nav-link" data-scroll-target="#step-6-run-the-penguin-api-from-docker"><span class="header-section-number">10.8.6</span> Step 6: Run the penguin API from Docker</a></li>
+  <li><a href="#step-7-put-up-the-shiny-app" id="toc-step-7-put-up-the-shiny-app" class="nav-link" data-scroll-target="#step-7-put-up-the-shiny-app"><span class="header-section-number">10.8.7</span> Step 7: Put up the Shiny app</a></li>
+  <li><a href="#lab-extensions" id="toc-lab-extensions" class="nav-link" data-scroll-target="#lab-extensions"><span class="header-section-number">10.8.8</span> Lab Extensions</a></li>
+  </ul></li>
+  </ul>
+<div class="toc-actions"><div><i class="bi bi-github"></i></div><div class="action-links"><p><a href="https://github.com/akgold/do4ds/edit/main/chapters/sec2/2-4-app-admin.qmd" class="toc-action">Edit this page</a></p></div></div></nav>
+    </div>
+<!-- main -->
+<main class="content" id="quarto-document-content">
+
+<header id="title-block-header" class="quarto-title-block default">
+<div class="quarto-title">
+<h1 class="title"><span id="sec-app-admin" class="quarto-section-identifier"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Application administration</span></span></h1>
+</div>
+
+
+
+<div class="quarto-title-meta">
+
+    
+  
+    
+  </div>
+  
+
+</header>
+
+<p>The last few chapters have been all about how to run a Linux server. But you don’t really care about running a Linux server – you care about doing data science. In order to do that, you’ll need to run applications.</p>
+<p>In this chapter, you’ll learn a little about how to install and administer applications on a Linux server, as well as specific pointers for data science tools like R, Python, and the system packages they use.</p>
+<section id="linux-app-install-config" class="level2" data-number="10.1">
+<h2 data-number="10.1" class="anchored" data-anchor-id="linux-app-install-config"><span class="header-section-number">10.1</span> Linux app install + config</h2>
+<p>You can install applications to Linux from a distro-specific repository, much like the app store for your phone or you can just download the application from the internet and install it locally.</p>
+<p>For Ubuntu, the <code>apt</code> command is used for interacting with repositories of <code>.deb</code> files. For CentOS and RedHat, the <code>yum</code> command is used for installing <code>.rpm</code> files.</p>
+<div class="callout callout-style-default callout-note callout-titled">
+<div class="callout-header d-flex align-content-center">
+<div class="callout-icon-container">
+<i class="callout-icon"></i>
+</div>
+<div class="callout-title-container flex-fill">
+Note
+</div>
+</div>
+<div class="callout-body-container callout-body">
+<p>The examples below are all for Ubuntu, since that’s what we use in the lab for this book. Conceptually, using <code>yum</code> is very similar, though the exact commands differ somewhat.</p>
+</div>
+</div>
+<p>In addition to actually installing packages, <code>apt</code> is also the utility for ensuring the lists of available packages you have are up to date with <code>update</code> and that all packages on your system are at their latest version with <code>upgrade</code>. When you find Ubuntu commands online, it’s common to see them prefixed with <code>apt-get update &amp;&amp; apt-get upgrade -y</code>. The <code>-y</code> flag bypasses a manual confirmation step.</p>
+<p>Packages are installed with <code>apt-get install &lt;package&gt;</code>. Depending on which user you are, you may need to prefix the command with <code>sudo</code>.</p>
+<p>Sometimes, you may want to install packages that aren’t in the repository for your distro. Doing that will generally involve downloading a file directly from a URL – usually with <code>wget</code> and then installing it from the file you’ve downloaded.</p>
+<section id="application-configuration" class="level3" data-number="10.1.1">
+<h3 data-number="10.1.1" class="anchored" data-anchor-id="application-configuration"><span class="header-section-number">10.1.1</span> Application configuration</h3>
+<p>Once you’ve installed an application, it will generally require some configuration like the default background color, the set of users allowed in, or the frequency something updates.</p>
+<p>On your personal computer, you’d probably find the setting in a series of dropdown menus at the top of the screen. On a server, no such menu exists.</p>
+<p>For applications running on your server, application behavior is usually configured through one or more <em>config files</em>. For applications hosted inside a Docker container, behavior is often configured with environment variables, sometimes in addition to config files.</p>
+</section>
+<section id="where-to-find-application-files" class="level3" data-number="10.1.2">
+<h3 data-number="10.1.2" class="anchored" data-anchor-id="where-to-find-application-files"><span class="header-section-number">10.1.2</span> Where to find application files</h3>
+<p>Linux applications often use several files located in different locations on the filesystem. Here are some of the ones you’ll use most frequently:</p>
+<ul>
+<li><p><code>/bin</code>, <code>/opt</code>, <code>/usr/local</code>, <code>/usr/bin</code> - installation locations for software.</p></li>
+<li><p><code>/etc</code> - configuration files for applications.</p></li>
+<li><p><code>/var</code> - variable data, most commonly log files in <code>/var/log</code> or <code>/var/lib</code>.</p></li>
+</ul>
+<p>This means that on a Linux server, the files for a particular application probably don’t all live in the same directory. Instead, you might run the application from the executable in <code>/opt</code>, configure it with files in <code>/etc</code>, and troubleshoot from logs in <code>/var</code>.</p>
+</section>
+<section id="command-line-configuration-with-vim-and-nano" class="level3" data-number="10.1.3">
+<h3 data-number="10.1.3" class="anchored" data-anchor-id="command-line-configuration-with-vim-and-nano"><span class="header-section-number">10.1.3</span> Command line configuration with vim and nano</h3>
+<p>Obviously, if you’re administering applications on a server, you’ll need to spend a fair bit of time editing text files. But how? Unlike on your personal computer, where you click a text file to open and edit it, you’ll need to work with a <em>command line text editor</em> when you’re working on a server.</p>
+<p>There are two command line text editors you’ll probably encounter: <code>nano</code> and <code>vi</code>/<code>vim</code>.<a href="#fn1" class="footnote-ref" id="fnref1" role="doc-noteref"><sup>1</sup></a> While they’re both powerful text editing tools, they can also be intimidating if you’ve never used them before.</p>
+<p>You can open a file in either by typing <code>nano &lt;filename&gt;</code> or <code>vi &lt;filename&gt;</code>.</p>
+<p>At this point many newbie command line users find themselves completely stuck, unable to do anything – even just exit and try again. But don’t worry, there’s a way out of this labyrinth.</p>
+<p>If you opened nano, there will be some helpful-looking prompts at the bottom. You’ll see that once you’re ready to go, you can exit with <code>^x</code>. But the <code>^</code> isn’t actually the caret character. On Windows, <code>^</code> is short for <code>Ctrl</code> and on Mac it’s for Command (<code>⌘</code>), so <code>Ctrl + x</code> or <code>⌘ + x</code> will exit.</p>
+<p>Where nano gives you helpful – if obscure – hints, a first experience in vim is the stuff of command line nightmares. You’ll type words and they won’t appear onscreen. Instead, you’ll experience dizzying jumps around the page and words and lines of text will disappear without a trace.</p>
+<p>This is because vim uses the letter keys not just to type, but also to navigate the page and interact with vim itself. You see, vim was created before keyboards uniformly had arrow keys.</p>
+<p>While they can be intimidating at first, vim keybindings are worth spending some time learning. Vim includes some powerful shortcuts for moving within and between lines and selecting and editing text. Most IDEs you might use, including RStudio, JupyterLab, and VSCode have vim modes.</p>
+<p>When you enter <code>vim</code>, you’re in the (poorly named) <em>normal mode</em>, which is for navigation only. Pressing the <code>i</code> key activates <em>insert mode</em>, which will feel normal for those of us used to arrow keys. Once in insert mode, you can type and words will appear and you can navigate with the arrow keys.</p>
+<p>You can return to normal mode with the <code>escape</code> key.</p>
+<p>Once you’ve escaped, you may wish never to return to normal mode, but it’s the only way to save files and exit <code>vim</code>. In order to do file operations, you type a colon, <code>:</code>, followed by the shortcut for what you want to do, and <code>enter</code>. The two most common commands you’ll use are save (write) with <code>w</code> and quit with <code>q</code>. You can combine these together, so you can save and quit in one command using <code>:wq</code>.</p>
+<p>Sometimes you may want to exit without saving or you might’ve opened and changed a file you don’t actually have permission to edit. If you’ve made changes and try to exit with <code>:q</code>, you’ll find yourself in an endless loop of warnings that your changes won’t be saved. You can tell <code>vim</code> you mean it with the exclamation mark, <code>!</code>, and exit using <code>:q!</code>.</p>
+</section>
+</section>
+<section id="reading-logs" class="level2" data-number="10.2">
+<h2 data-number="10.2" class="anchored" data-anchor-id="reading-logs"><span class="header-section-number">10.2</span> Reading logs</h2>
+<p>Once your applications are up and running, you may run into issues. Or even if you don’t, you may want to take a look at how things are running.</p>
+<p>Most applications write their logs into somewhere inside the <code>/var</code> directory. Some things will get logged to the main log at <code>/var/log/syslog</code>. Other things may get logged to <code>/var/log/&lt;application name&gt;</code> or <code>/var/lib/&lt;application name&gt;</code>.</p>
+<p>It’s important to get comfortable with the commands to read text files in order to be able to examine logs (and other files). The commands I use most commonly are:</p>
+<ul>
+<li><p><code>cat</code> is the basic command to print a file, starting at the beginning.</p></li>
+<li><p><code>less</code> prints a file, starting at the beginning, but only a few lines at a time.</p></li>
+<li><p><code>head</code> prints only the first few lines and exits. It is especially useful to peer at the beginning of a large file, like a <code>csv</code> file – so you can quickly preview the column heads and the first few values.</p></li>
+<li><p><code>tail</code> prints a file going up from the end. This is especially useful for log files, as the newest logs are appended to the end of a file. This is such a common practice that “tailing a log file” is a common phrase.</p>
+<ul>
+<li>Sometimes, you’ll want to use the <code>-f</code> flag (for <em>follow</em>) to tail a file with a live view as it updates.</li>
+</ul></li>
+</ul>
+<p>Sometimes you want to search around inside a text file. You’re probably familiar with the power and hassle of <em>regular expressions (regex)</em> to search for specific character sequences in text strings. The Linux command <code>grep</code> is the main regex command.</p>
+<p>In addition to searching in text files, <code>grep</code> is often useful in combination with other commands. For example, it’s often useful to put the output of <code>ls</code> into <code>grep</code> to search for a particular file in a big directory using the pipe.</p>
+</section>
+<section id="running-the-right-commands" class="level2" data-number="10.3">
+<h2 data-number="10.3" class="anchored" data-anchor-id="running-the-right-commands"><span class="header-section-number">10.3</span> Running the right commands</h2>
+<p>Let’s say you want to open Python on your command line. One option would be to type the complete path to a Python install every time. For example, I’ve got a version of Python in <code>/usr/bin</code>, so <code>/usr/bin/python3</code> works.</p>
+<p>But in most cases, it’s nice to just type <code>python3</code> and have the right version open up.</p>
+<div class="code-with-filename">
+<div class="code-with-filename-file">
+<pre><strong>Terminal</strong></pre>
+</div>
+<div class="sourceCode" id="cb1"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb1-1"><a href="#cb1-1"></a><span class="op">&gt;</span> python3</span>
+<span id="cb1-2"><a href="#cb1-2"></a><span class="ex">Python</span> 3.9.6 <span class="er">(</span><span class="ex">default,</span> May  7 2023, 23:32:45<span class="kw">)</span> </span>
+<span id="cb1-3"><a href="#cb1-3"></a><span class="ex">[Clang</span> 14.0.3 <span class="er">(</span><span class="ex">clang-1403.0.22.14.1</span><span class="kw">)</span><span class="ex">]</span> on darwin</span>
+<span id="cb1-4"><a href="#cb1-4"></a><span class="ex">Type</span> <span class="st">"help"</span>, <span class="st">"copyright"</span>, <span class="st">"credits"</span> or <span class="st">"license"</span> for more information.</span>
+<span id="cb1-5"><a href="#cb1-5"></a><span class="op">&gt;&gt;&gt;</span> </span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+</div>
+<p>In some cases, this isn’t optional. Certain applications will rely on others being available, like RStudio Server needing to find R. Or Jupyter Notebook finding your Python kernels.</p>
+<p>So how does Linux know where to find those applications and files?</p>
+<p>If you ever want to check which actual executable is being used by a command, you can use the <code>which</code> command. For example, on my system this is the result of <code>which python3</code>.</p>
+<div class="code-with-filename">
+<div class="code-with-filename-file">
+<pre><strong>Terminal</strong></pre>
+</div>
+<div class="sourceCode" id="cb2"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb2-1"><a href="#cb2-1"></a><span class="op">&gt;</span> which <span class="ex">python3</span>                                                    </span>
+<span id="cb2-2"><a href="#cb2-2"></a><span class="ex">/usr/bin/python3</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+</div>
+<p>The operating system knows how to find the actual runnable programs on your system via the <em>path</em>. The path is a set of directories that the system knows to search when it tries to run a program. The path is stored in an environment variable, conveniently named <code>PATH</code>.</p>
+<p>You can check your path at any time with <code>echo $PATH</code>. On my MacBook, this is what the path looks like.</p>
+<div class="code-with-filename">
+<div class="code-with-filename-file">
+<pre><strong>Terminal</strong></pre>
+</div>
+<div class="sourceCode" id="cb3"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb3-1"><a href="#cb3-1"></a><span class="op">&gt;</span> echo <span class="va">$PATH</span>                                                      </span>
+<span id="cb3-2"><a href="#cb3-2"></a><span class="ex">/opt/homebrew/bin:/opt/homebrew/sbin:/usr/local/bin:/System/Cryptexes/App/usr/bin:/usr/bin:/bin:/usr/sbin:/sbin</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+</div>
+<p>When you install a new piece of software you’ll need to add it two the path. Say I was to install a new version of Python in <code>/opt/python</code>. That’s not on my <code>PATH</code>, so my system wouldn’t be able to find it.</p>
+<p>I can get it on the path in one of two ways – the first option would be to add <code>/opt/python</code> to my <code>PATH</code> every time a terminal session starts usually via a file in <code>/etc</code> or the <code>.zshrc</code>.</p>
+<p>The other option is to create a <em>symlink</em> to the new application in a directory already on the <code>PATH</code>. A symlink does what it sounds like – creates a way to link to a file from a different directory without moving it. Symlinks are created with the <code>ln</code> command.</p>
+</section>
+<section id="running-applications-as-services" class="level2" data-number="10.4">
+<h2 data-number="10.4" class="anchored" data-anchor-id="running-applications-as-services"><span class="header-section-number">10.4</span> Running applications as services</h2>
+<p>On your personal computer, you probably have programs that start every time your computer does. Maybe this happens for Slack, Microsoft Teams, or Spotify. Such applications that execute on startup and run in the background waiting for some sort of input are called a <em>daemon</em> or a <em>service</em>.</p>
+<p>On a server, most of the applications are configured to run as a service so they’re ready for users who may not have the permissions to start them. For example, on a data science workbench, you’d want JupyterHub and/or RStudio Server to run as a service.</p>
+<p>In Linux, the tool to turn a regular application into a daemon is called <code>systemd</code>. Some applications automatically configure themselves with <code>systemd</code> when they’re installed. If your application doesn’t, or you want to alter the startup behavior, most applications have their <code>systemd</code> configuration in <code>/etc/systemd/system/&lt;service name&gt;.service</code>.</p>
+<p>Daemonized services are controlled using the <code>systemctl</code> command line tool.</p>
+<div class="callout callout-style-default callout-note callout-titled">
+<div class="callout-header d-flex align-content-center">
+<div class="callout-icon-container">
+<i class="callout-icon"></i>
+</div>
+<div class="callout-title-container flex-fill">
+Note
+</div>
+</div>
+<div class="callout-body-container callout-body">
+<p>Basically all modern Linux distros have coalesced around using <code>systemd</code> and <code>systemctl</code>. Older systems may not have it installed by default and you may have to install it or use a different tool.</p>
+</div>
+</div>
+<p>The <code>systemctl</code> command has a set of sub-commands that are useful for working with applications. Providing those commands looks like <code>systemctl &lt;subcommand&gt; &lt;application&gt;</code>. Often <code>systemctl</code> has to be run as <code>sudo</code>, since you’re working with an application for all users of the system.</p>
+<p>The most useful <code>systemctl</code> commands include <code>status</code> for checking whether a program is running or not, <code>start</code>, <code>stop</code>, and <code>restart</code> for a <code>stop</code> followed by a <code>start</code>. Many applications also support a <code>reload</code> command, which reloads configuration settings without having to actually restart the process. Exactly which settings require a <code>restart</code> vs a <code>reload</code> varies from one application to another.</p>
+<p>If you’ve changed a service’s <code>systemd</code> configuration, you can load changes with <code>daemon-reload</code>. You also can turn a service on or off for the next time the server starts with <code>enable</code> and <code>disable</code>.</p>
+<section id="running-docker-containers-as-a-service" class="level3" data-number="10.4.1">
+<h3 data-number="10.4.1" class="anchored" data-anchor-id="running-docker-containers-as-a-service"><span class="header-section-number">10.4.1</span> Running Docker containers as a service</h3>
+<p>One of the benefits of running Docker Containers is that they run basically anywhere, so it’s a popular way to quickly run an application on a server. To run them as a service, you’ll need to make sure Docker itself is daemonized and then ensure the container you care about comes up whenever Docker does by setting a <em>restart policy</em> for the container.</p>
+<p>However, many Docker services involve coordinating more than one container. If that’s the case, you’ll want to use a system that’s custom-built for managing multiple containers. The most popular are <em>Docker Compose</em> or <em>Kubernetes</em>.</p>
+<p>Docker Compose is a relatively lightweight system where you write a YAML file to describe the containers you need and the relationship between them. You can then use a single command to launch the entire set of Docker containers.</p>
+<p>Docker Compose is fantastic for prototyping systems of Docker containers and for running small-scale Docker-ized deployments on a single server. There are many great resources on Docker Compose online to learn more.</p>
+<p>Kubernetes is designed for a similar purpose, but instead of running a handful of containers on one server, Kubernetes is a heavy-duty production system designed to schedule hundreds or thousands of Docker-based workloads across a cluster of many individual servers.</p>
+<p>In general, I’d recommend sticking with Docker Compose for the work you’re doing. If you’re finding yourself needing the full might of Kubernetes to do what you want, you probably should be working closely with a professional IT/Admin</p>
+</section>
+</section>
+<section id="managing-r-and-python" class="level2" data-number="10.5">
+<h2 data-number="10.5" class="anchored" data-anchor-id="managing-r-and-python"><span class="header-section-number">10.5</span> Managing R and Python</h2>
+<p>As the admin of a data science server, Python and R are some of the most critical software you’ll manage.</p>
+<p>In general, the easiest path to making many users happy is having a bunch of versions of R and Python installed side-by-side. That way you can allow users to upgrade their version of R or Python as it works for their project, not according to your upgrade schedule.</p>
+<p>I’ve seen this work best by installing R and Python into the <code>/opt/python</code> and <code>/opt/R</code> directory. Users can grab them from there to create project-specific virtual environments. You’ll need to make sure permissions are correct on <code>/opt/python</code> for this to work.</p>
+<p>Now, this isn’t what will happen if you just <code>sudo apt-get install python</code> or <code>sudo apt-get install R</code>, so you’ll have to be a little more clever. My favorite route (though I’m obviously biased) is to install Python and R from the pre-built binaries provided by Posit.</p>
+<section id="python-specific-considerations" class="level3" data-number="10.5.1">
+<h3 data-number="10.5.1" class="anchored" data-anchor-id="python-specific-considerations"><span class="header-section-number">10.5.1</span> Python-specific considerations</h3>
+<p>Python is one of the world’s most popular programming languages for general purpose computing. This actually makes configuring Python <strong>harder</strong>.</p>
+<p>Almost every system comes with a <em>system version</em> of Python. This is the version of Python that’s used by the operating system for various tasks. It’s almost always very old and you really don’t want to mess with it.</p>
+<p>So in order to configure Python on your system, you have to install data science specific versions of Python, get them on the path, and get the system version of Python off the path. This is the source of much frustration trying to get Python up and running, both on servers and your personal computer.</p>
+<p>On your personal computer, Conda is a great solution for this problem. Conda allows you to install a standalone version of Python in <em>user-space</em>. That means that even if your organization doesn’t let you have admin rights on your computer, you can install and manage versions of Python for development.</p>
+<p>For the same reason, Conda isn’t a great choice for administering a data science server. You’re not a user – you’re an admin. And giving everyone on the server access to Python versions is generally easier without Conda.</p>
+<p>This is why it’s a good idea to install data science Python versions into <code>/opt/python</code>. It’s easy to add that one directory to the path, and it’s completely distinct from where the system Python lives.</p>
+</section>
+<section id="r-specific-considerations" class="level3" data-number="10.5.2">
+<h3 data-number="10.5.2" class="anchored" data-anchor-id="r-specific-considerations"><span class="header-section-number">10.5.2</span> R-specific considerations</h3>
+<p>People pretty much only ever install R to do data science so it’s generally not a huge deal where you install R and get it on the path. If you want just one version of R, using <code>apt-get install</code> is fine.</p>
+<p>If you want multiple versions, you’ll need to manually install to <code>/opt/R</code> or use <code>rig</code>, which is an R-specific installation manager. Currently, <code>rig</code> only supports Windows, Mac, and Ubuntu.</p>
+</section>
+</section>
+<section id="managing-system-libraries" class="level2" data-number="10.6">
+<h2 data-number="10.6" class="anchored" data-anchor-id="managing-system-libraries"><span class="header-section-number">10.6</span> Managing System Libraries</h2>
+<p>As an admin, you’ll also have to decide what to do about <em>system packages</em>, which are Linux libraries you install from a Linux repository or the internet.</p>
+<p>Many packages in Python and R don’t do any work themselves. Instead, they’re just language-specific interfaces to system packages. For example, any R or Python library that uses a JDBC database connector will need to make use of Java on your system. And many geospatial libraries make use of system packages like GDAL.</p>
+<p>As the administrator, you’ll need to make sure you understand what system libraries are needed for the Python and R packages you’re using, and you’ll need to make sure they’re available and on the path.</p>
+<p>For many of these libraries, it’s not a huge pain. You’ll just install the required library using <code>apt</code> or the system package manager for your distro. In some cases (especially Java), more configuration may be required to make sure that the package you need shows up on the path.</p>
+</section>
+<section id="comprehension-questions" class="level2" data-number="10.7">
+<h2 data-number="10.7" class="anchored" data-anchor-id="comprehension-questions"><span class="header-section-number">10.7</span> Comprehension Questions</h2>
+<ol type="1">
+<li>What are two different ways to install Linux applications and what are commands to do so?</li>
+<li>What does it mean to daemonize a Linux application? What programs and commands are used to do so?</li>
+<li>How do you know if you’ve opened <code>nano</code> or <code>vim</code>? How would you exit them if you didn’t mean to?</li>
+<li>What are 4 commands to read text files?</li>
+<li>How would you create a file called <code>secrets.txt</code>, open it with vim, write something in, close and save it, and make it so that only you can read it?</li>
+</ol>
+</section>
+<section id="lab-installing-applications" class="level2" data-number="10.8">
+<h2 data-number="10.8" class="anchored" data-anchor-id="lab-installing-applications"><span class="header-section-number">10.8</span> Lab: Installing Applications</h2>
+<p>As we’ve started to administer our server, we’ve mostly been doing very generic server administration tasks. Now let’s set up the applications we need to run a data science workbench and get our API and Shiny app set up for using in our portfolio.</p>
+<section id="step-1-install-python" class="level3" data-number="10.8.1">
+<h3 data-number="10.8.1" class="anchored" data-anchor-id="step-1-install-python"><span class="header-section-number">10.8.1</span> Step 1: Install Python</h3>
+<p>Let’s start by installing a data science version of Python so we’re not using the system Python for data science purposes.</p>
+<p>If you want just one version of Python, you can <code>apt-get install</code> a specific version. As of this writing, Python 3.10 is a relatively new version of Python, so we’ll install that one with</p>
+<div class="code-with-filename">
+<div class="code-with-filename-file">
+<pre><strong>Terminal</strong></pre>
+</div>
+<div class="sourceCode" id="cb4"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb4-1"><a href="#cb4-1"></a><span class="fu">sudo</span> apt-get install python3.10-venv</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+</div>
+<p>Once you’ve installed Python, you can check that you’ve got the right version by running</p>
+<div class="code-with-filename">
+<div class="code-with-filename-file">
+<pre><strong>Terminal</strong></pre>
+</div>
+<div class="sourceCode" id="cb5"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb5-1"><a href="#cb5-1"></a><span class="ex">python3</span> <span class="at">--version</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+</div>
+<p>This method, using <code>apt-get</code>, is great when you just want one version of Python. But if you want multiple versions sitting side by side, you’ll need to do something else. I recommend installing using the instructions on the Posit website, which will involve downloading and installing from <code>.deb</code> files.</p>
+</section>
+<section id="step-2-install-r" class="level3" data-number="10.8.2">
+<h3 data-number="10.8.2" class="anchored" data-anchor-id="step-2-install-r"><span class="header-section-number">10.8.2</span> Step 2: Install R</h3>
+<p>Since we’re using Ubuntu, we can use <code>rig</code>. There are good instructions on downloading <code>rig</code> and using it to install R on the <a href="https://github.com/r-lib/rig"><code>rlib/rig</code> GitHub repo</a>. Use those instructions to install the current R release on your server.</p>
+<p>Once you’ve installed R on your server, you can check that it’s running by just typing <code>R</code> into the command line. If that works, you’re good to move on to the next step. If not, you’ll need to make sure R got onto the path.</p>
+</section>
+<section id="step-3-install-jupyerhub-jupyterlab" class="level3" data-number="10.8.3">
+<h3 data-number="10.8.3" class="anchored" data-anchor-id="step-3-install-jupyerhub-jupyterlab"><span class="header-section-number">10.8.3</span> Step 3: Install JupyerHub + JupyterLab</h3>
+<p>JupyterHub and JupyterLab are Python programs, so we’re going to run them from within a Python virtual environment. I’d recommend putting that virtual environment inside <code>/opt/jupyterhub</code>.</p>
+<p>Here are the commands to create and activate a <code>jupyterhub</code> virtual environment in <code>/opt/jupyterhub</code>:</p>
+<div class="code-with-filename">
+<div class="code-with-filename-file">
+<pre><strong>Terminal</strong></pre>
+</div>
+<div class="sourceCode" id="cb6"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb6-1"><a href="#cb6-1"></a><span class="fu">sudo</span> python3 <span class="at">-m</span> venv /opt/jupyterhub</span>
+<span id="cb6-2"><a href="#cb6-2"></a><span class="bu">source</span> /opt/jupyterhub/bin/activate</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+</div>
+<p>Now we’re going to actually get JupyterHub up and running inside the virtual environment we just created. JupyterHub produces <a href="https://jupyterhub.readthedocs.io/en/stable/quickstart.html">docs that you can use</a> to get up and running very quickly. If you have to stop for any reason, make sure to come back, assume sudo, and start the JupyterHub virtual environment we created.</p>
+<p>Note that because we’re working inside a virtual environment, you may have to use the <code>jupyterhub-singleuser</code> version of the binary.</p>
+</section>
+<section id="step-4-daemonize-jupyterhub" class="level3" data-number="10.8.4">
+<h3 data-number="10.8.4" class="anchored" data-anchor-id="step-4-daemonize-jupyterhub"><span class="header-section-number">10.8.4</span> Step 4: Daemonize JupyterHub</h3>
+<p>Because JupyterHub is a Python process, not a system process, it won’t automatically get daemonized, so we’ll have to do it manually.</p>
+<p>We don’t need it right now, but it’ll be easier to manage JupyterHub later on from a config file that’s in <code>/etc/jupyterhub</code>. In order to do so, activate the <code>jupyterhub</code> virtual environment, create a default JupyterHub config (Google for the command), and move it into <code>/etc/jupyterhub/jupyterhub_config.py</code>.</p>
+<p>Now let’s move on to daemonizing JupyterHub. To start, kill the existing JupyterHub process (consult the cheatsheet in <a href="../append/cheatsheets.html">Appendix&nbsp;<span>C</span></a> if you need help). Since JupyterHub wasn’t automatically daemonized, you’ll have to manually create the systemd file.</p>
+<p>Here’s the file I created in <code>/etc/systemd/system/jupyterhub.service</code>.</p>
+<div class="code-with-filename">
+<div class="code-with-filename-file">
+<pre><strong>/etc/systemd/system/jupyterhub.service</strong></pre>
+</div>
+<div class="sourceCode" id="cb7"><pre class="sourceCode numberSource yaml number-lines code-with-copy"><code class="sourceCode yaml"><span id="cb7-1"><a href="#cb7-1"></a><span class="kw">[</span><span class="at">Unit</span><span class="kw">]</span></span>
+<span id="cb7-2"><a href="#cb7-2"></a><span class="at">Description=Jupyterhub</span></span>
+<span id="cb7-3"><a href="#cb7-3"></a><span class="at">After=syslog.target network.target</span></span>
+<span id="cb7-4"><a href="#cb7-4"></a></span>
+<span id="cb7-5"><a href="#cb7-5"></a><span class="kw">[</span><span class="at">Service</span><span class="kw">]</span></span>
+<span id="cb7-6"><a href="#cb7-6"></a><span class="at">User=root</span></span>
+<span id="cb7-7"><a href="#cb7-7"></a><span class="at">Environment="PATH=/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/opt/jupyterhub/bin"</span></span>
+<span id="cb7-8"><a href="#cb7-8"></a><span class="at">ExecStart=/opt/jupyterhub/bin/jupyterhub -f /etc/jupyterhub/jupyterhub_config.py</span></span>
+<span id="cb7-9"><a href="#cb7-9"></a></span>
+<span id="cb7-10"><a href="#cb7-10"></a><span class="kw">[</span><span class="at">Install</span><span class="kw">]</span></span>
+<span id="cb7-11"><a href="#cb7-11"></a><span class="at">WantedBy=multi-user.target</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+</div>
+<p>There are two things here worth noticing. The first is the <code>Environment</code> line that adds <code>/opt/jupyterhub/bin</code> to the path – that’s where our virtual environment is.</p>
+<p>The second is <code>ExecStart</code> line, which provides is the startup command and specifies that JupyterHub should use the config we just created, specified by <code>-f /etc/jupyterhub/jupyterhub_config.py</code>.</p>
+<p>Now, you’ll need to use <code>systemctl</code> to reload the daemon, start JupyterHub, and enable it.</p>
+</section>
+<section id="step-5-install-rstudio-server" class="level3" data-number="10.8.5">
+<h3 data-number="10.8.5" class="anchored" data-anchor-id="step-5-install-rstudio-server"><span class="header-section-number">10.8.5</span> Step 5: Install RStudio Server</h3>
+<p>You can find the commands to install RStudio server on the <a href="https://posit.co/download/rstudio-server/">Posit website</a>. Make sure to pick the version that matches your operating system. Since you’ve already installed R, you can skip down to the “Install RStudio Server” step.</p>
+<p>Unlike JupyterHub, RStudio Server does daemonize itself right out of the box, so you can check and control the status with <code>systemctl</code> without any further work.</p>
+</section>
+<section id="step-6-run-the-penguin-api-from-docker" class="level3" data-number="10.8.6">
+<h3 data-number="10.8.6" class="anchored" data-anchor-id="step-6-run-the-penguin-api-from-docker"><span class="header-section-number">10.8.6</span> Step 6: Run the penguin API from Docker</h3>
+<p>First, you’ll have to make sure that Docker itself is available on the system. It can be installed from <code>apt</code> using <code>apt-get install docker.io</code>. You may need to adopt <code>sudo</code> privileges to do so.</p>
+<p>Once Docker is installed, getting the API running is almost trivially easy using the command we used back in <a href="../sec1/1-6-docker.html">Chapter&nbsp;<span>6</span></a> to run our container.</p>
+<div class="code-with-filename">
+<div class="code-with-filename-file">
+<pre><strong>Terminal</strong></pre>
+</div>
+<div class="sourceCode" id="cb8"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb8-1"><a href="#cb8-1"></a><span class="fu">sudo</span> docker run <span class="at">--rm</span> <span class="at">-d</span> <span class="dt">\</span></span>
+<span id="cb8-2"><a href="#cb8-2"></a>  <span class="at">-p</span> 8080:8080 <span class="dt">\</span></span>
+<span id="cb8-3"><a href="#cb8-3"></a>  <span class="at">--name</span> penguin-model <span class="dt">\</span></span>
+<span id="cb8-4"><a href="#cb8-4"></a>  alexkgold/penguin-model</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+</div>
+<p>The one change you might note is that I’ve changed the port on the server to be <code>8080</code>, since JupyterHub runs on <code>8000</code> by default.</p>
+<p>Once it’s up, you can check that it’s running with <code>docker ps</code>.</p>
+</section>
+<section id="step-7-put-up-the-shiny-app" class="level3" data-number="10.8.7">
+<h3 data-number="10.8.7" class="anchored" data-anchor-id="step-7-put-up-the-shiny-app"><span class="header-section-number">10.8.7</span> Step 7: Put up the Shiny app</h3>
+<p>We’re going to use Shiny Server to host our Shiny app on the server. Start by moving the app code to the server. I put mine in <code>/home/test-user/do4ds-lab/app</code> by cloning the Git repo.</p>
+<p>After that, you’ll need to:</p>
+<ol type="1">
+<li>Open R or Python and rebuild the package library with <code>{renv}</code> or <code>{venv}</code>.</li>
+<li>Install Shiny Server using the instructions from the <a href="https://docs.posit.co/shiny-server/#getting-started">Admin Guide</a>.
+<ul>
+<li>Note that you can skip steps to install R and/or Python, as well as the <code>{shiny}</code> package as we’ve already done that.</li>
+</ul></li>
+<li>Edit Shiny Server’s configuration file to run the right app.</li>
+<li>Start and enable Shiny Server with <code>systemctl</code>.</li>
+</ol>
+</section>
+<section id="lab-extensions" class="level3" data-number="10.8.8">
+<h3 data-number="10.8.8" class="anchored" data-anchor-id="lab-extensions"><span class="header-section-number">10.8.8</span> Lab Extensions</h3>
+<p>There are a few things you might want to consider before moving into the next chapter, where we’ll start working on giving this server a stable public URL.</p>
+<p>First, we haven’t daemonized the API. Feel free to try Docker Compose or setting a restart policy for the container.</p>
+<p>Second, neither the API nor the Shiny app will automatically update when we make changes to them. You might want to set up a GitHub Action to do so. For Shiny Server, you’ll need to push the updates to the server and then restart Shiny Server. For the API, you’d need to configure a GitHub action to rebuild the container and push it to a registry. You’d then need to tell Docker on the server to re-pull and restart the container.</p>
+<p>Finally, there’s no authentication in front of our API. Now, the API has pretty limited functionality, so that’s not a huge worry. But if you had an API with more functionality that might be a problem. Additionally, someone could try to flood your API with requests to make it unusable. The most common way to solve this is to buy a product that hosts the API for you or to put an authenticating proxy in front of the API (Google for instructions for NGINX if you want to try it).</p>
+
+
+</section>
+</section>
+<section id="footnotes" class="footnotes footnotes-end-of-document" role="doc-endnotes">
+<hr>
+<ol>
+<li id="fn1"><p><code>vi</code> is the original fullscreen text editor for Linux. <code>vim</code> is its successor (<code>vim</code> stands for <code>vi</code> improved). I’m not going to worry about the distinction.<a href="#fnref1" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
+</ol>
+</section>
+
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+        <nav id="TOC" role="doc-toc" class="toc-active">
+    <h2 id="toc-title">Table of contents</h2>
+   
+  <ul>
+  <li><a href="#the-briefest-intro-to-computational-theory" id="toc-the-briefest-intro-to-computational-theory" class="nav-link active" data-scroll-target="#the-briefest-intro-to-computational-theory"><span class="header-section-number">11.1</span> The briefest intro to computational theory</a></li>
+  <li><a href="#how-computers-compute" id="toc-how-computers-compute" class="nav-link" data-scroll-target="#how-computers-compute"><span class="header-section-number">11.2</span> How computers compute</a></li>
+  <li><a href="#recommendation-1-fewer-faster-cpu-cores" id="toc-recommendation-1-fewer-faster-cpu-cores" class="nav-link" data-scroll-target="#recommendation-1-fewer-faster-cpu-cores"><span class="header-section-number">11.3</span> Recommendation 1: Fewer, faster CPU cores</a></li>
+  <li><a href="#how-memory-works" id="toc-how-memory-works" class="nav-link" data-scroll-target="#how-memory-works"><span class="header-section-number">11.4</span> How memory works</a></li>
+  <li><a href="#recommendation-2-get-as-much-ram-as-feasible" id="toc-recommendation-2-get-as-much-ram-as-feasible" class="nav-link" data-scroll-target="#recommendation-2-get-as-much-ram-as-feasible"><span class="header-section-number">11.5</span> Recommendation 2: Get as much RAM as feasible</a></li>
+  <li><a href="#understanding-storage" id="toc-understanding-storage" class="nav-link" data-scroll-target="#understanding-storage"><span class="header-section-number">11.6</span> Understanding storage</a></li>
+  <li><a href="#recommendation-3-get-lots-of-storage-its-cheap" id="toc-recommendation-3-get-lots-of-storage-its-cheap" class="nav-link" data-scroll-target="#recommendation-3-get-lots-of-storage-its-cheap"><span class="header-section-number">11.7</span> Recommendation 3: Get lots of storage, it’s cheap</a></li>
+  <li><a href="#gpus-are-special-purpose-compute" id="toc-gpus-are-special-purpose-compute" class="nav-link" data-scroll-target="#gpus-are-special-purpose-compute"><span class="header-section-number">11.8</span> GPUs are special-purpose compute</a></li>
+  <li><a href="#recommendation-4-get-a-gpu-maybe" id="toc-recommendation-4-get-a-gpu-maybe" class="nav-link" data-scroll-target="#recommendation-4-get-a-gpu-maybe"><span class="header-section-number">11.9</span> Recommendation 4: Get a GPU, maybe</a></li>
+  <li><a href="#assessing-ram-cpu-usage" id="toc-assessing-ram-cpu-usage" class="nav-link" data-scroll-target="#assessing-ram-cpu-usage"><span class="header-section-number">11.10</span> Assessing RAM + CPU usage</a></li>
+  <li><a href="#examining-at-storage-usage" id="toc-examining-at-storage-usage" class="nav-link" data-scroll-target="#examining-at-storage-usage"><span class="header-section-number">11.11</span> Examining at storage usage</a></li>
+  <li><a href="#running-out-of-resources" id="toc-running-out-of-resources" class="nav-link" data-scroll-target="#running-out-of-resources"><span class="header-section-number">11.12</span> Running out of Resources</a>
+  <ul class="collapse">
+  <li><a href="#aws-instances-for-data-science" id="toc-aws-instances-for-data-science" class="nav-link" data-scroll-target="#aws-instances-for-data-science"><span class="header-section-number">11.12.1</span> AWS Instances for data science</a></li>
+  </ul></li>
+  <li><a href="#comprehension-questions" id="toc-comprehension-questions" class="nav-link" data-scroll-target="#comprehension-questions"><span class="header-section-number">11.13</span> Comprehension Questions</a></li>
+  <li><a href="#lab-changing-instance-size" id="toc-lab-changing-instance-size" class="nav-link" data-scroll-target="#lab-changing-instance-size"><span class="header-section-number">11.14</span> Lab: Changing Instance Size</a>
+  <ul class="collapse">
+  <li><a href="#step-1-confirm-current-server-size" id="toc-step-1-confirm-current-server-size" class="nav-link" data-scroll-target="#step-1-confirm-current-server-size"><span class="header-section-number">11.14.1</span> Step 1: Confirm current server size</a></li>
+  <li><a href="#step-2-change-the-instance-type-and-bring-it-back" id="toc-step-2-change-the-instance-type-and-bring-it-back" class="nav-link" data-scroll-target="#step-2-change-the-instance-type-and-bring-it-back"><span class="header-section-number">11.14.2</span> Step 2: Change the instance type and bring it back</a></li>
+  <li><a href="#step-3-confirm-new-server-size" id="toc-step-3-confirm-new-server-size" class="nav-link" data-scroll-target="#step-3-confirm-new-server-size"><span class="header-section-number">11.14.3</span> Step 3: Confirm new server size</a></li>
+  <li><a href="#step-4-upgrade-storage-maybe" id="toc-step-4-upgrade-storage-maybe" class="nav-link" data-scroll-target="#step-4-upgrade-storage-maybe"><span class="header-section-number">11.14.4</span> Step 4: Upgrade storage (maybe)</a></li>
+  </ul></li>
+  </ul>
+<div class="toc-actions"><div><i class="bi bi-github"></i></div><div class="action-links"><p><a href="https://github.com/akgold/do4ds/edit/main/chapters/sec2/2-5-scale.qmd" class="toc-action">Edit this page</a></p></div></div></nav>
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+<header id="title-block-header" class="quarto-title-block default">
+<div class="quarto-title">
+<h1 class="title"><span id="sec-scale" class="quarto-section-identifier"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Server Resources and Scaling</span></span></h1>
+</div>
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+<div class="quarto-title-meta">
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+
+<p>If your server is for more than just playing, you’re going to want to make sure you’ve got sufficient resources to do the work you need.</p>
+<p>This chapter is going to help you develop a mental model of what a server’s computational resources are, teach you about the command line tools to assess how much of your resources are being used, and provide recommendations on how to scale and size a server for data science.</p>
+<section id="the-briefest-intro-to-computational-theory" class="level2" data-number="11.1">
+<h2 data-number="11.1" class="anchored" data-anchor-id="the-briefest-intro-to-computational-theory"><span class="header-section-number">11.1</span> The briefest intro to computational theory</h2>
+<p>You’re probably aware that everything you’ve ever seen on a computer – from this book to your work in R or Python, your favorite internet cat videos, and Minecraft – it’s just 1s and 0s.</p>
+<p>But the 1s and 0s aren’t actually the interesting part. The interesting part is that these 1s and 0s don’t directly represent a cat or a book. Instead, the 1s and 0s are binary representations of integers (whole numbers) and <strong>the only</strong> thing the computer does is add these integers.<a href="#fn1" class="footnote-ref" id="fnref1" role="doc-noteref"><sup>1</sup></a></p>
+<p>Once they’ve been added, they’re reinterpreted back into something meaningful. But the bottom line is that every bit of input your computer gets is turned into an addition problem, processed, and the results are reverted back into something we interpret as meaningful.</p>
+<p>So, a computer is really just a factory that does addition problems. So as you’re thinking about how to size and scale a server, you’re really thinking about how to optimally design your factory.</p>
+<p>There are three essential resources a server has – compute, memory, and storage. In this chapter, I’m going to share some mental models I find helpful about how to think of each and some recommendations for getting a data science server.</p>
+</section>
+<section id="how-computers-compute" class="level2" data-number="11.2">
+<h2 data-number="11.2" class="anchored" data-anchor-id="how-computers-compute"><span class="header-section-number">11.2</span> How computers compute</h2>
+<p>The addition assembly line itself – where the work actually gets done – is referred to as <em>compute</em>. It’s where 2+2 gets turned into 4, and where 345619912 + 182347910 gets turned into 527967822.</p>
+<p>The main compute that all computers have is the central processing unit (CPU), which completes addition problems in a <em>core</em>.</p>
+<p>The first attribute that determines the speed of compute is the number of cores, which is like the number of conveyor belts in the factory.</p>
+<p>These days, most consumer-grade laptops have between 4 and 16 physical cores. Many have software capabilities that effectively double that number, so they can do between 4 and 32 simultaneous addition problems.</p>
+<p>The second speed-determining attribute is how quickly a single addition problem gets completed by a single core. This is called the <em>single core clock speed</em>. You can think of this as how fast the conveyor belt moves.</p>
+<p>Clock speeds are measured in operations per second or <em>hertz (hz)</em>. The cores in your laptop probably max out between two and five gigahertz (GHz), which means between 2 billion and 5 billion operations per second.</p>
+<p>For decades, many of the innovations in computing were coming from increases in single core clock speed, but those have fallen off a lot in the last few decades. The clock speeds of consumer-grade chips increased by approximately 10x during the 90s, by 2-3x in the 2000s, and somewhere between not at all and 1.5x in the 2010s.</p>
+<p>But computers have continued getting a lot faster even as the increase in clock speeds has slowed. The increase has mostly come from increases in the number of cores, better software usage of parallelization, and faster loading and unloading of the CPU (called the <em>bus</em>).</p>
+</section>
+<section id="recommendation-1-fewer-faster-cpu-cores" class="level2" data-number="11.3">
+<h2 data-number="11.3" class="anchored" data-anchor-id="recommendation-1-fewer-faster-cpu-cores"><span class="header-section-number">11.3</span> Recommendation 1: Fewer, faster CPU cores</h2>
+<p>R and Python are single-threaded. This means that unless you’re using special libraries for parallel processing, you’ll end up red-lining a single CPU core while the others just look on in silence.</p>
+<p>Therefore for most R and Python work, single core clock speed matters more than the number of cores, and fewer, faster cores are usually preferable to many slower</p>
+<p>You’re probably not used to thinking about this tradeoff from buying a laptop or phone. The reality is that modern CPUs are pretty darn good and you should just buy the one that fits your budget.</p>
+<p>If you’re standing up a server, you often do have an explicit choice between more slower cores and fewer faster ones, determined by the instance family.</p>
+<p>If you’re running a multi-user server, the number of cores you need can be hard to estimate. If you’re doing non-ML tasks like counts and dashboarding or relatively light-duty machine learning I might advise the following:</p>
+<p><span class="math display">\[
+\text{n cores} = \text{1 core per user} + 1
+\]</span></p>
+<p>The spare core is for the server to do its own operations apart from the data science usage. On the other hand, if you’re doing heavy-duty machine learning or parallelizing jobs across the CPU, you may need more cores than this rule of thumb.</p>
+</section>
+<section id="how-memory-works" class="level2" data-number="11.4">
+<h2 data-number="11.4" class="anchored" data-anchor-id="how-memory-works"><span class="header-section-number">11.4</span> How memory works</h2>
+<p>Your computer’s random access memory (RAM) is its short term storage. You can think of RAM like the stock that’s sitting out on the factory floor ready to go right on an assembly line and the completed work that’s ready to be shipped.</p>
+<p>RAM is very fast to for your computer to access, so you can read and write to it very quickly. The downside is that it’s temporary. When your computer turns off, the RAM gets wiped.<a href="#fn2" class="footnote-ref" id="fnref2" role="doc-noteref"><sup>2</sup></a></p>
+<div class="callout callout-style-default callout-note callout-titled">
+<div class="callout-header d-flex align-content-center">
+<div class="callout-icon-container">
+<i class="callout-icon"></i>
+</div>
+<div class="callout-title-container flex-fill">
+Note
+</div>
+</div>
+<div class="callout-body-container callout-body">
+<p>Memory and storage are measured in <em>bytes</em> with metric prefixes.</p>
+<p>Common sizes for memory these days are in <em>gigabytes</em> (billion bytes) and <em>terrabytes</em> (trillion bytes). Some enterprise data stores run on the scales of thousands of terrabytes (<em>pettabytes</em>) or even thousands of pettabytes (<em>yottabytes</em>).</p>
+</div>
+</div>
+<p>Modern consumer-grade laptops come with somewhere between 4 and 16 Gb of memory.</p>
+</section>
+<section id="recommendation-2-get-as-much-ram-as-feasible" class="level2" data-number="11.5">
+<h2 data-number="11.5" class="anchored" data-anchor-id="recommendation-2-get-as-much-ram-as-feasible"><span class="header-section-number">11.5</span> Recommendation 2: Get as much RAM as feasible</h2>
+<p>In most cases, R and Python have to load all of your data into memory. Thus, the size of the data you can use is limited to the size of your machine’s RAM.</p>
+<p>Most other limits of your machine will just result in things being slower than you’d really want, but trying to load too much data into memory will result in a session crash.</p>
+<div class="callout callout-style-default callout-note callout-titled">
+<div class="callout-header d-flex align-content-center">
+<div class="callout-icon-container">
+<i class="callout-icon"></i>
+</div>
+<div class="callout-title-container flex-fill">
+Note
+</div>
+</div>
+<div class="callout-body-container callout-body">
+<p>If you’re running into this limitation, go back and think about your project architecture as discussed in <a href="../sec1/1-2-proj-arch.html">Chapter&nbsp;<span>2</span></a>. Maybe you can load less data into memory.</p>
+</div>
+</div>
+<p>Because your computer needs memory for things other than R and Python and because you’ll often be doing transformations that temporarily increase the size of your data, you need more memory than your largest data set.</p>
+<p>In general, you’ll always want more RAM, but a pretty good rule of thumb is that you’ll be happy if:</p>
+<p><span class="math display">\[\text{Amount of RAM} \ge 3 * \text{max amount of data}\]</span></p>
+<p>If you’re thinking about running a multi-user server, you’ll need to take a step back to think about how many concurrent users you expect and how much data you expect each one to load.</p>
+</section>
+<section id="understanding-storage" class="level2" data-number="11.6">
+<h2 data-number="11.6" class="anchored" data-anchor-id="understanding-storage"><span class="header-section-number">11.6</span> Understanding storage</h2>
+<p><em>Storage</em>, or <em>hard disk/drive</em>, is your computer’s place to put things for the long-term. It’s where applications are installed, and where you save things you want to keep.</p>
+<p>Relative to the RAM that’s right next to the factory floor, your computer’s storage is like the warehouse in the next building over. It’s slower to get things from storage than RAM, but it’s also permanent once its stored there.</p>
+<p>Up until a few years ago, storage was much slower than RAM. Those drives, called <em>HDD</em> drives, had a bunch of spinning magnetic disks with magnetized read/write heads that move among the disks to save and read data.</p>
+<p>While they spin very fast – 5,400 and 7,200 RPM are common speeds – there were still physical moving parts, and reading and writing data was very slow by computational standards.</p>
+<p>In the last few years, <em>solid-state drives (SSDs)</em> have become more-or-less standard in laptops. SSDs, which are collections of flash memory chips with no moving parts are up to 15x faster than HDDs.</p>
+</section>
+<section id="recommendation-3-get-lots-of-storage-its-cheap" class="level2" data-number="11.7">
+<h2 data-number="11.7" class="anchored" data-anchor-id="recommendation-3-get-lots-of-storage-its-cheap"><span class="header-section-number">11.7</span> Recommendation 3: Get lots of storage, it’s cheap</h2>
+<p>As for configuring storage on your server – get a lot – but don’t think about it too hard, because it’s cheap and easy to upgrade. Storage is cheap enough these days that it is almost always more cost efficient to buy more storage rather than making a highly-paid professional spend their time trying to figure out how to move things around.</p>
+<div class="callout callout-style-default callout-note callout-titled">
+<div class="callout-header d-flex align-content-center">
+<div class="callout-icon-container">
+<i class="callout-icon"></i>
+</div>
+<div class="callout-title-container flex-fill">
+Note
+</div>
+</div>
+<div class="callout-body-container callout-body">
+<p>If the IT/Admins at your organization want you to spend a lot of time deleting things from storage that’s usually a red flag that they aren’t thinking much about how to make the overall organization work more smoothly.</p>
+</div>
+</div>
+<p>If you’re running a multi-user server, the amount of storage you need depends a lot on your data and your workflows.</p>
+<p>If you’re not running particularly large data, or most of your data won’t be saved into the server’s storage (generally a good thing), a reasonable rule of thumb is to choose</p>
+<p><span class="math display">\[
+\text{Amount of Storage} = \text{1Gb} * \text{n users}
+\]</span></p>
+<p>If you’re not saving large data files, the amount of space each person needs on the server is small. Code is very small and it’s rare to see R and Python packages take up more than a few dozen Mb per data scientist.</p>
+<div class="callout callout-style-default callout-note callout-titled">
+<div class="callout-header d-flex align-content-center">
+<div class="callout-icon-container">
+<i class="callout-icon"></i>
+</div>
+<div class="callout-title-container flex-fill">
+Note
+</div>
+</div>
+<div class="callout-body-container callout-body">
+<p>If you’re working with a professional IT admin, they may be concerned about the storage implications of having package copies for each person on their team if you’re following best practices for running environments as code from <a href="../sec1/1-1-env-as-code.html">Chapter&nbsp;<span>1</span></a>. I’ve heard this concern a lot from IT/Admins thinking ahead about running their server and almost never of a case where it’s actually been a problem.</p>
+</div>
+</div>
+<p>If, on the other hand, you will be saving a lot of data, you’ve got to take that into account. In some organizations, each data scientist will save dozens of flat files of a Gb or more for each of their projects.</p>
+<p>If you’re operating in the cloud, this really isn’t an important choice. As you’ll see in the lab, upgrading the amount of storage you have is a trivial operation, requiring at most a few minutes of downtime. Choose a size you guess will be adequate and add more if you need.</p>
+</section>
+<section id="gpus-are-special-purpose-compute" class="level2" data-number="11.8">
+<h2 data-number="11.8" class="anchored" data-anchor-id="gpus-are-special-purpose-compute"><span class="header-section-number">11.8</span> GPUs are special-purpose compute</h2>
+<p>All computers have a CPU. There are also specialized chips where the CPU can offload particular tasks, the most common of which is the graphical processing unit (GPU). GPUs are architected for tasks like editing photo or videos, rendering video game graphics, some kinds of machine learning, and (yes) Bitcoin mining.</p>
+<p>A GPU is an addition factory just like a CPU, but with the opposite architecture. CPUs have only a handful of cores, but those cores are fast. A GPU takes the opposite approach, with many (relatively) slow cores.</p>
+<p>Where a consumer-grade CPU has 4-16 cores, mid-range GPUs have 700-4,000 cores, with each one running at only about 1% to 10% the single core clock speed speed of a CPU core.</p>
+<p>The choice of whether you need a GPU to do your work will really depend on what you’re doing and your budget.</p>
+<p>For the tasks GPUs are good at, the overwhelming parallelism ends up being more important than the speed of any individual core, and GPU computation can be dramatically faster.</p>
+</section>
+<section id="recommendation-4-get-a-gpu-maybe" class="level2" data-number="11.9">
+<h2 data-number="11.9" class="anchored" data-anchor-id="recommendation-4-get-a-gpu-maybe"><span class="header-section-number">11.9</span> Recommendation 4: Get a GPU, maybe</h2>
+<p>The tasks that most benefit from GPU computing are training highly parallel machine learning models like deep learning or tree-based models. If you do have one of these use cases, GPU computing can massively speed up your computation – making models trainable in hours instead of days.</p>
+<p>If you are planning to use cloud resources for your computing, GPU-backed instances are quite pricey, and you’ll want to be careful about only putting those machines up when you’re using them.</p>
+<p>Because GPUs are expensive, I generally wouldn’t bother with GPU-backed computing unless you’ve already tried without and find that it takes too long to be feasible.</p>
+<p>It’s also worth noting that using a GPU won’t happen automatically. The tooling has gotten good enough that it’s usually pretty easy to set up, but your computer won’t train your XGBoost models on your GPU unless you tell it to do so.</p>
+</section>
+<section id="assessing-ram-cpu-usage" class="level2" data-number="11.10">
+<h2 data-number="11.10" class="anchored" data-anchor-id="assessing-ram-cpu-usage"><span class="header-section-number">11.10</span> Assessing RAM + CPU usage</h2>
+<p>Once you’ve chosen your server size and gotten up and running, you’ll want to be able to monitor RAM and CPU for problems.</p>
+<p>Any program that is running is called a <em>process</em>. For example, when you type <code>python</code> on the command line to open a REPL, that starts a single Python process. If you were to start a second terminal session and run <code>python</code> again, you’d have a second Python process.</p>
+<p>Complicated programs often involve multiple interlocking processes. For example, running the RStudio IDE involves (at minimum) one process for the IDE itself and one for the R session that it uses in the background. The relationships between these different processes is mostly hidden from you – the end user.</p>
+<p>As an admin, you may want to inspect the processes running on your system at any given time. The <code>top</code> command is a good first stop. <code>top</code> shows the top CPU-consuming processes in real time along with a number of other facts about them.</p>
+<p>Here’s the <code>top</code> output from my machine as I write this sentence.</p>
+<div class="code-with-filename">
+<div class="code-with-filename-file">
+<pre><strong>Terminal</strong></pre>
+</div>
+<div class="sourceCode" id="cb1"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb1-1"><a href="#cb1-1"></a><span class="ex">PID</span>    COMMAND      %CPU TIME     <span class="co">#TH    #WQ  #PORT MEM    PURG   CMPRS PGRP</span></span>
+<span id="cb1-2"><a href="#cb1-2"></a><span class="ex">0</span>      kernel_task  16.1 03:56:53 530/10 0    0     2272K  0B     0B    0</span>
+<span id="cb1-3"><a href="#cb1-3"></a><span class="ex">16329</span>  WindowServer 16.0 01:53:20 23     6    3717  941M-  16M+   124M  16329</span>
+<span id="cb1-4"><a href="#cb1-4"></a><span class="ex">24484</span>  iTerm2       11.3 00:38.20 5      2    266-  71M-   128K   18M-  24484</span>
+<span id="cb1-5"><a href="#cb1-5"></a><span class="ex">29519</span>  top          9.7  00:04.30 1/1    0    36    9729K  0B     0B    29519</span>
+<span id="cb1-6"><a href="#cb1-6"></a><span class="ex">16795</span>  Magnet       3.1  00:39.16 3      1    206   82M    0B     39M   16795</span>
+<span id="cb1-7"><a href="#cb1-7"></a><span class="ex">16934</span>  Arc          1.8  18:18.49 45     6    938   310M   144K   61M   16934</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+</div>
+<p>In most instances, the first three columns are the most useful. The first column is the unique process id (<code>pid</code>) for that process. You’ve got the name of the process (<code>COMMAND</code>) and how much CPU its using. You’ve also got the amount of memory used a few columns over. Right now, nothing is using very much CPU.</p>
+<p>The <code>top</code> command takes over your whole terminal. You can exit with <code>Ctrl + c</code>.</p>
+<div class="callout callout-style-default callout-note callout-titled">
+<div class="callout-header d-flex align-content-center">
+<div class="callout-icon-container">
+<i class="callout-icon"></i>
+</div>
+<div class="callout-title-container flex-fill">
+So much CPU?
+</div>
+</div>
+<div class="callout-body-container callout-body">
+<p>For <code>top</code> (and most other commands), CPU is expressed as a percent of <em>single core</em> availability. So, on a modern machine with multiple cores, it’s very common to see CPU totals well over 100%. Seeing a single process using over 100% of CPU is rarer.</p>
+</div>
+</div>
+<p>Another useful command for finding runaway processes is <code>ps aux</code>. It lists a snapshot of all processes running on the system, along with how much CPU or RAM they’re using. You can sort the output with the <code>--sort</code> flag and specify sorting by cpu with <code>--sort -%cpu</code> or by memory with <code>--sort -%mem</code>.</p>
+<p>Because <code>ps aux</code> returns <em>every</em> running process on the system, you’ll probably want to pipe the output into <code>head</code>. In addition to CPU and Memory usage, <code>ps aux</code> gets you who launched the command and the PID.</p>
+<p>For example, here are the RStudio processes currently running on my system.</p>
+<div class="code-with-filename">
+<div class="code-with-filename-file">
+<pre><strong>Terminal</strong></pre>
+</div>
+<div class="sourceCode" id="cb2"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb2-1"><a href="#cb2-1"></a><span class="ex">USER</span>               PID  %CPU %MEM      VSZ    RSS   TT  STAT STARTED      TIME COMMAND</span>
+<span id="cb2-2"><a href="#cb2-2"></a><span class="ex">alexkgold</span>        23583   0.9  1.7 37513368 564880   <span class="pp">??</span>  S    Sat09AM  17:15.27 /Applications/RStudio.app/Contents/MacOS/RStudio</span>
+<span id="cb2-3"><a href="#cb2-3"></a><span class="ex">alexkgold</span>        23605   0.5  0.4 36134976 150828   <span class="pp">??</span>  S    Sat09AM   1:58.16 /Applications/RStudio.app/Contents/MacOS/rsession <span class="at">--config-file</span> none <span class="at">--program-mode</span> desktop </span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+</div>
+<p>One of the times you’ll be most interested in the output of <code>top</code> or <code>ps aux</code> is when something is going rogue on your system and using more resources than you intended. If you have some sense of who started the runaway process or what it it, it can be useful to pipe the output of <code>ps aux</code> into <code>grep</code>.</p>
+<p>For example, the command to get the output above was <code>ps aux | RStudio</code>.</p>
+<p>If you’ve got a rogue process, the pattern is to try to find the process and make note of its <code>pid</code>. Then you can immediately end the process by <code>pid</code> with the <code>kill</code> command.</p>
+<p>If I were to find something concerning – perhaps an R process that is using 500% of CPU – I would want to take notice of its <code>pid</code> to kill it with <code>kill</code>.</p>
+</section>
+<section id="examining-at-storage-usage" class="level2" data-number="11.11">
+<h2 data-number="11.11" class="anchored" data-anchor-id="examining-at-storage-usage"><span class="header-section-number">11.11</span> Examining at storage usage</h2>
+<p>A common culprit for weird server behavior is running out of storage space. There are two handy commands for monitoring the amount of storage you’ve got – <code>du</code> and <code>df</code>.</p>
+<p>These commands are almost always used with the <code>-h</code> flag to put file sizes in human-readable formats.</p>
+<p><code>df</code>, for disk free, shows the capacity left on the device where the directory sits.</p>
+<p>For example, here’s the result of running the <code>df</code> command on the chapters directory on my laptop that includes this chapter.</p>
+<div class="code-with-filename">
+<div class="code-with-filename-file">
+<pre><strong>Terminal</strong></pre>
+</div>
+<div class="sourceCode" id="cb3"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb3-1"><a href="#cb3-1"></a><span class="op">&gt;</span> df <span class="ex">-h</span> chapters</span>
+<span id="cb3-2"><a href="#cb3-2"></a><span class="ex">Filesystem</span>     Size   Used  Avail Capacity iused      ifree %iused  Mounted on</span>
+<span id="cb3-3"><a href="#cb3-3"></a><span class="ex">/dev/disk3s5</span>  926Gi  227Gi  686Gi    25% 1496100 7188673280    0%   /System/Volumes/Data</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+</div>
+<p>So you can see that the chapters folder lives on a disk called <code>/dev/disk3s5</code> that’s a little less than 1Tb and is 25% full – no problem. On a server this can be really useful to know, because it’s quite easy to switch a disk out for a bigger one in the same spot.</p>
+<p>If you’ve figured out that a disk is full, it’s usually most cost effective to just buy a bigger disk. But sometimes something weird happens. Maybe there are a few exceptionally big files, or you think unnecessary copies are being made.</p>
+<p>If so, the <code>du</code> command, short for disk usage, gives you the size of individual files inside a directory. It’s particularly useful in combination with the sort command.</p>
+<p>For example, here’s the result of running <code>du</code> on the chapters directory where the text files for this book live.</p>
+<div class="code-with-filename">
+<div class="code-with-filename-file">
+<pre><strong>Terminal</strong></pre>
+</div>
+<div class="sourceCode" id="cb4"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb4-1"><a href="#cb4-1"></a><span class="op">&gt;</span> du <span class="ex">-h</span> chapters <span class="kw">|</span> <span class="fu">sort</span></span>
+<span id="cb4-2"><a href="#cb4-2"></a><span class="ex">12M</span> chapters</span>
+<span id="cb4-3"><a href="#cb4-3"></a><span class="ex">1.7M</span>    chapters/sec1/images</span>
+<span id="cb4-4"><a href="#cb4-4"></a><span class="ex">1.8M</span>    chapters/sec1</span>
+<span id="cb4-5"><a href="#cb4-5"></a><span class="ex">236K</span>    chapters/images</span>
+<span id="cb4-6"><a href="#cb4-6"></a><span class="ex">488K</span>    chapters/sec2/images-traffic</span>
+<span id="cb4-7"><a href="#cb4-7"></a><span class="ex">5.3M</span>    chapters/sec2/images-networking</span>
+<span id="cb4-8"><a href="#cb4-8"></a><span class="ex">552K</span>    chapters/sec2/images</span>
+<span id="cb4-9"><a href="#cb4-9"></a><span class="ex">6.6M</span>    chapters/sec2</span>
+<span id="cb4-10"><a href="#cb4-10"></a><span class="ex">892K</span>    chapters/append/images-append</span>
+<span id="cb4-11"><a href="#cb4-11"></a><span class="ex">948K</span>    chapters/append</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+</div>
+<p>So if I were thinking about cleaning up this directory, I could see that my <code>sec1/images</code> directory is my biggest single directory. If you find yourself needing to find big files on your Linux server, it’s worth spending some time with the help pages for <code>du</code>. There are lots of really useful options.</p>
+</section>
+<section id="running-out-of-resources" class="level2" data-number="11.12">
+<h2 data-number="11.12" class="anchored" data-anchor-id="running-out-of-resources"><span class="header-section-number">11.12</span> Running out of Resources</h2>
+<p>If you recognize that you’re running out of resources on your current server, you may want to move to something bigger. There are two main reasons servers run out of room.</p>
+<p>The first reason is because people are running big jobs. This can happen at any scale of organization. There are data science teams of one who have use cases that necessitate terrabytes of data.</p>
+<p>The second reason is because you have a lot of people using your server. This is generally a feature of big data science teams, irrespective of the size of the workloads.</p>
+<p>Either way, there are two basic options for how to scale your data science workbench. The first is <em>vertical scaling</em>, which is just a fancy way of saying get a bigger server. The second option is <em>horizontal scaling</em>, which means running a whole fleet of servers in parallel and spreading the workload across them.</p>
+<p>As a data scientist, you shouldn’t be shy about vertically scaling if your budget allows it. The complexity of managing a <code>t3.nano</code> with 2 cores and 0.5 Gb of memory is exactly the same as a <code>C5.24xlarge</code> with 96 cores and 192 Gb of memory. In fact, the bigger one may well be easier to manage, since you won’t have to worry about running low on resources.</p>
+<p>There are limits to the capacity of vertical scaling. As of this writing, AWS’s general-use instance types max out at 96-128 cores. That can quickly get eaten up by 50 data scientists with reasonably heavy computational demands.</p>
+<p>Once you’re thinking about horizontal scaling, you’ve got a distributed service problem on your hand, which is inherently difficult. You should almost certainly get an IT/Admin professional involved. See <a href="../sec3/3-4-ent-servers.html">Chapter&nbsp;<span>18</span></a> for more on how to talk to them about it.</p>
+<section id="aws-instances-for-data-science" class="level3" data-number="11.12.1">
+<h3 data-number="11.12.1" class="anchored" data-anchor-id="aws-instances-for-data-science"><span class="header-section-number">11.12.1</span> AWS Instances for data science</h3>
+<p>AWS offers a variety of different EC2 instance types split up by <em>family</em> and <em>size</em>. The family is the category of EC2 instance. Different families of instances are optimized for different kinds of workloads.</p>
+<p>Here’s a table of common instance types for data science purposes:</p>
+<table class="table">
+<colgroup>
+<col style="width: 31%">
+<col style="width: 68%">
+</colgroup>
+<thead>
+<tr class="header">
+<th>Instance Type</th>
+<th>What it is</th>
+</tr>
+</thead>
+<tbody>
+<tr class="odd">
+<td><code>t3</code></td>
+<td>The “standard” configuration. Relatively cheap. Sizes may be limited.</td>
+</tr>
+<tr class="even">
+<td><code>C</code></td>
+<td>CPU-optimized instances, aka faster CPUs</td>
+</tr>
+<tr class="odd">
+<td><code>R</code></td>
+<td>Higher ratio of RAM to CPU</td>
+</tr>
+<tr class="even">
+<td><code>P</code></td>
+<td>GPU instances, very expensive</td>
+</tr>
+</tbody>
+</table>
+<p>Within each family, there are different sizes available, ranging from <em>nano</em> to multiples of <em>xl</em>. Instances are denoted by <em>&lt;family&gt;.&lt;size&gt;</em>. So, for example, when we put our instance originally on a free tier machine, we put it on a <code>t2.micro</code>.</p>
+<p>In most cases, going up a size doubles the amount of RAM, the number of cores, and the cost. So you should do some quick math before you stand up a <code>C5.24xlarge</code> or a GPU-based <code>P</code> instance. If your instance won’t be up very long, it may be fine, but make sure you take it down when you’re done lest you rack up a huge bill.</p>
+</section>
+</section>
+<section id="comprehension-questions" class="level2" data-number="11.13">
+<h2 data-number="11.13" class="anchored" data-anchor-id="comprehension-questions"><span class="header-section-number">11.13</span> Comprehension Questions</h2>
+<ol type="1">
+<li><p>Think about the scenarios below – which part of your computer would you want to upgrade to solve the problem?</p>
+<ol type="1">
+<li><p>You try to load a big csv file into pandas in Python. It churns for a while and then crashes.</p></li>
+<li><p>You go to build a new ML model on your data. You’d like to re-train the model once a day, but it turns out training this model takes 26 hours on your laptop.</p></li>
+<li><p>You design an visualization <code>Matplotlib</code> , and create a whole bunch in a loop, you want to parallelize the operation. Right now you’re running on a <code>t2.small</code> with 1 CPU.</p></li>
+</ol></li>
+<li><p>Draw a mind map of the following: CPU, RAM, Storage, Operations Per Second, Parallel Operations, GPU, Machine Learning</p></li>
+<li><p>What are the architectural differences between a CPU and a GPU? Why does this make a GPU particularly good for Machine Learning?</p></li>
+<li><p>How would you do the following:</p>
+<ol type="1">
+<li><p>Find all running Jupyter processes that belong to the user <code>alexkgold</code>.</p></li>
+<li><p>Find the different disks attached to your server and see how full each one is.</p></li>
+<li><p>Find the biggest files in each user’s home directory.</p></li>
+</ol></li>
+</ol>
+</section>
+<section id="lab-changing-instance-size" class="level2" data-number="11.14">
+<h2 data-number="11.14" class="anchored" data-anchor-id="lab-changing-instance-size"><span class="header-section-number">11.14</span> Lab: Changing Instance Size</h2>
+<p>In this lab, we’re going to upgrade the size of our server. And the best part is that because we’re in the cloud, it’ll take only a few minutes.</p>
+<section id="step-1-confirm-current-server-size" class="level3" data-number="11.14.1">
+<h3 data-number="11.14.1" class="anchored" data-anchor-id="step-1-confirm-current-server-size"><span class="header-section-number">11.14.1</span> Step 1: Confirm current server size</h3>
+<p>First, let’s confirm what we’ve got available. You can check the number of CPUs you’ve got with <code>lscpu</code> in a terminal. Similarly, you can check the amount of RAM with <code>free -h</code>. This is just so you can prove to yourself later that the instance really changed.</p>
+</section>
+<section id="step-2-change-the-instance-type-and-bring-it-back" class="level3" data-number="11.14.2">
+<h3 data-number="11.14.2" class="anchored" data-anchor-id="step-2-change-the-instance-type-and-bring-it-back"><span class="header-section-number">11.14.2</span> Step 2: Change the instance type and bring it back</h3>
+<p>Now, you can go to the instance page in the AWS console. The first step is to stop (not terminate!) the instance. This means that changing instance type <em>does</em> require some downtime for the instance, but it’s quite limited.</p>
+<p>Once the instance has stopped, you can change the instance type under Actions &gt; Instance Settings. Then start the instance. It’ll take a few seconds to start the instance.</p>
+</section>
+<section id="step-3-confirm-new-server-size" class="level3" data-number="11.14.3">
+<h3 data-number="11.14.3" class="anchored" data-anchor-id="step-3-confirm-new-server-size"><span class="header-section-number">11.14.3</span> Step 3: Confirm new server size</h3>
+<p>So, for example, I changed from a <code>t2.micro</code> to a <code>t2.small</code>. Both only have 1 CPU, so I won’t see any difference in <code>lscpu</code>, but running <code>free -h</code> before and after the switch reveals the difference in the total column:</p>
+<pre><code>test-user@ip-172-31-53-181:~$ free -h
+               total        used        free      shared  buff/cache   available
+Mem:           966Mi       412Mi       215Mi       0.0Ki       338Mi       404Mi
+Swap:             0B          0B          0B
+test-user@ip-172-31-53-181:~$ free -h
+               total        used        free      shared  buff/cache   available
+Mem:           1.9Gi       225Mi       1.3Gi       0.0Ki       447Mi       1.6Gi
+Swap:             0B          0B          0B</code></pre>
+<p>I got twice as much RAM!</p>
+<p>There are some rules around being able to change from one instance type to another, but this is a superpower if you’ve got variable workloads or a team that’s growing. Once you’re done with your larger server, it’s just as easy to scale it back down.</p>
+</section>
+<section id="step-4-upgrade-storage-maybe" class="level3" data-number="11.14.4">
+<h3 data-number="11.14.4" class="anchored" data-anchor-id="step-4-upgrade-storage-maybe"><span class="header-section-number">11.14.4</span> Step 4: Upgrade storage (maybe)</h3>
+<p>If you want more storage, it’s similarly easy to resize the EBS volume attached to your server.</p>
+<p>I wouldn’t recommend doing it for this lab, because you can only automatically adjust volume sizes up, so you’d have to manually transfer all of your data if you ever wanted to scale back down.</p>
+<p>If you do resize the volume, you’ll have to let Linux know so it can resize the filesystem with the new space available. AWS has a great walk through called <a href="https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/recognize-expanded-volume-linux.html">Extend a Linux filesystem after resizing the volume</a> that I recommend you follow.</p>
+
+
+</section>
+</section>
+<section id="footnotes" class="footnotes footnotes-end-of-document" role="doc-endnotes">
+<hr>
+<ol>
+<li id="fn1"><p>This was proved in Alan Turing’s 1936 paper on computability. If you’re interested in learning more, I recommend <a href="https://www.goodreads.com/en/book/show/2333956.The_Annotated_Turing">The Annotated Turing: A Guided Tour Through Alan Turing’s Historic Paper on Computability and the Turing Machine</a> by Charles Petzold for a surprisingly readable walkthrough.<a href="#fnref1" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
+<li id="fn2"><p>You probably don’t experience this personally. Modern computers are pretty smart about dumping RAM onto the hard disk before shutting down, and bringing it back on startup, so you usually won’t notice this happening.<a href="#fnref2" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
+</ol>
+</section>
+
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+    <h2 id="toc-title">Table of contents</h2>
+   
+  <ul>
+  <li><a href="#understanding-digital-addresses" id="toc-understanding-digital-addresses" class="nav-link active" data-scroll-target="#understanding-digital-addresses"><span class="header-section-number">12.1</span> Understanding digital addresses</a></li>
+  <li><a href="#finding-the-right-digital-address" id="toc-finding-the-right-digital-address" class="nav-link" data-scroll-target="#finding-the-right-digital-address"><span class="header-section-number">12.2</span> Finding the right digital address</a></li>
+  <li><a href="#recognizing-ip-addresses" id="toc-recognizing-ip-addresses" class="nav-link" data-scroll-target="#recognizing-ip-addresses"><span class="header-section-number">12.3</span> Recognizing IP addresses</a></li>
+  <li><a href="#basic-network-administration" id="toc-basic-network-administration" class="nav-link" data-scroll-target="#basic-network-administration"><span class="header-section-number">12.4</span> Basic network administration</a>
+  <ul class="collapse">
+  <li><a href="#browser-devtools" id="toc-browser-devtools" class="nav-link" data-scroll-target="#browser-devtools"><span class="header-section-number">12.4.1</span> Browser devtools</a></li>
+  <li><a href="#ssh-tunnelingport-forwarding" id="toc-ssh-tunnelingport-forwarding" class="nav-link" data-scroll-target="#ssh-tunnelingport-forwarding"><span class="header-section-number">12.4.2</span> SSH tunneling/port forwarding</a></li>
+  <li><a href="#checking-what-ports-are-open" id="toc-checking-what-ports-are-open" class="nav-link" data-scroll-target="#checking-what-ports-are-open"><span class="header-section-number">12.4.3</span> Checking what ports are open</a></li>
+  <li><a href="#checking-if-a-host-is-accessible" id="toc-checking-if-a-host-is-accessible" class="nav-link" data-scroll-target="#checking-if-a-host-is-accessible"><span class="header-section-number">12.4.4</span> Checking if a host is accessible</a></li>
+  </ul></li>
+  <li><a href="#comprehension-questions" id="toc-comprehension-questions" class="nav-link" data-scroll-target="#comprehension-questions"><span class="header-section-number">12.5</span> Comprehension Questions</a></li>
+  <li><a href="#lab-making-it-accessible-in-one-place" id="toc-lab-making-it-accessible-in-one-place" class="nav-link" data-scroll-target="#lab-making-it-accessible-in-one-place"><span class="header-section-number">12.6</span> Lab: Making it accessible in one place</a>
+  <ul class="collapse">
+  <li><a href="#step-1-configure-nginx" id="toc-step-1-configure-nginx" class="nav-link" data-scroll-target="#step-1-configure-nginx"><span class="header-section-number">12.6.1</span> Step 1: Configure Nginx</a></li>
+  <li><a href="#step-2-open-port-80" id="toc-step-2-open-port-80" class="nav-link" data-scroll-target="#step-2-open-port-80"><span class="header-section-number">12.6.2</span> Step 2: Open port 80</a></li>
+  <li><a href="#step-3-configure-your-subpaths" id="toc-step-3-configure-your-subpaths" class="nav-link" data-scroll-target="#step-3-configure-your-subpaths"><span class="header-section-number">12.6.3</span> Step 3: Configure your subpaths</a></li>
+  <li><a href="#step-4-try-it-out" id="toc-step-4-try-it-out" class="nav-link" data-scroll-target="#step-4-try-it-out"><span class="header-section-number">12.6.4</span> Step 4: Try it out!</a></li>
+  <li><a href="#lab-extensions" id="toc-lab-extensions" class="nav-link" data-scroll-target="#lab-extensions"><span class="header-section-number">12.6.5</span> Lab Extensions</a></li>
+  </ul></li>
+  </ul>
+<div class="toc-actions"><div><i class="bi bi-github"></i></div><div class="action-links"><p><a href="https://github.com/akgold/do4ds/edit/main/chapters/sec2/2-6-networking.qmd" class="toc-action">Edit this page</a></p></div></div></nav>
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+<header id="title-block-header" class="quarto-title-block default">
+<div class="quarto-title">
+<h1 class="title"><span id="sec-networking" class="quarto-section-identifier"><span class="chapter-number">12</span>&nbsp; <span class="chapter-title">Intro to Computer Networks</span></span></h1>
+</div>
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+<p>If you’ve got a server but no one can access it, is it really even there? AWS would say yes, and they will still bill you. But it won’t be useful.</p>
+<p><em>Computer networking</em> – the subject of how computers send information back and forth – is the second big part of administering a server. Once you’ve got a server up and running with the applications you want, you need to make it accessible to the people who need it.</p>
+<p>In this chapter, you’ll learn about the basics of how computer networks work and how one computer successfully sends a message to another. In the lab, you’ll get to finally make your data science workbench available on the actual internet.</p>
+<p>To learn about computer networks, let’s talk about the mail. The real kind that goes in an envelope and is delivered in trucks. When you want to send a letter, you need to use a valid envelope. You need to address the letter properly and apply a stamp in the right place.</p>
+<p>The same is true of digital traffic. While the envelope, stamp, and address are all digital, there are shared rules that define what is valid mail. In networking terms, these rules are called <em>protocols</em>. These days, pretty much all computer networking is accomplished with a stack of protocols called <em>TCP/IP (Transmission Control Protocol/Internet Protocol)</em>.</p>
+<p>TCP/IP defines all kinds of things about network traffic, from the digital equivalent of what a valid envelope size is to how to load and unload the virtual trucks. Luckily, using a cloud server takes care of almost all of that.</p>
+<p>I imagine the server as like an apartment building. Each service lives in one apartment and is waiting for incoming mail. We, as the server admin, are responsible for properly configuring the incoming traffic to make sure it can get to where it’s going.</p>
+<p>So the main things you’ll need to understand is how to make sure the incoming mail properly arrives at the building and how it knows which apartment to head to once it gets there.</p>
+<section id="understanding-digital-addresses" class="level2" data-number="12.1">
+<h2 data-number="12.1" class="anchored" data-anchor-id="understanding-digital-addresses"><span class="header-section-number">12.1</span> Understanding digital addresses</h2>
+<p>You already use digital addresses all the time in the form of a <em>URL</em> (<em>Uniform Resource Locator)</em>.<a href="#fn1" class="footnote-ref" id="fnref1" role="doc-noteref"><sup>1</sup></a> A URL fully specifies the network location of a resource and looks like this:</p>
+<p><span class="math display">\[\overbrace{\text{https://}}^\text{protocol}\underbrace{\text{google.com}}_\text{domain}\overbrace{\text{:443}}^\text{port}\underbrace{\text{/}}_\text{path}\]</span></p>
+<p>This may look a little strange. You’re probably used to using just the domain and maybe a path in your web browser like <span class="math inline">\(\text{google.com}\)</span> or <span class="math inline">\(\text{google.com/maps}\)</span>. The reason is that you’re usually fine with the default protocol and port, so you may never have realized they’re there.<a href="#fn2" class="footnote-ref" id="fnref2" role="doc-noteref"><sup>2</sup></a></p>
+<p>Here’s what each of those four parts are:</p>
+<ul>
+<li><p>The <em>application layer protocol</em> (often just called the protocol) specifies what type of traffic this is. It’s like agreeing that your letter will be in English or Arabic or Dutch.</p></li>
+<li><p>The <em>domain</em> is a human-readable way of providing the digital street address of the server. We’ll get into the actual address later in the chapter.</p></li>
+<li><p>The <em>port</em> specifies where on the server to direct the traffic. It’s the digital equivalent of the apartment number.</p></li>
+<li><p>The <em>path</em> is a human-friendly way of specifying who you intend the message to go to. It’s like the name of person you’re addressing on your letter.</p></li>
+</ul>
+<p>As a cloud server admin, most of the networking you’ll do is to ensure someone can just use a domain with a path and access the resources they need from your server.</p>
+</section>
+<section id="finding-the-right-digital-address" class="level2" data-number="12.2">
+<h2 data-number="12.2" class="anchored" data-anchor-id="finding-the-right-digital-address"><span class="header-section-number">12.2</span> Finding the right digital address</h2>
+<p>A domain is the human-readable way of addressing a resource on the internet. But it’s not actually the digital street address of any particular server (host). Instead, hosts are actually identified with an <em>IP Address</em>. When that IP address is valid across the entire internet, it’s a <em>public</em> IP address.</p>
+<div class="callout callout-style-default callout-note callout-titled">
+<div class="callout-header d-flex align-content-center">
+<div class="callout-icon-container">
+<i class="callout-icon"></i>
+</div>
+<div class="callout-title-container flex-fill">
+Note
+</div>
+</div>
+<div class="callout-body-container callout-body">
+<p>IP Addresses are mapped to domains via the <em>Domain Name Service (DNS)</em>, which you’ll learn about in <a href="2-7-dns.html">Chapter&nbsp;<span>13</span></a></p>
+</div>
+</div>
+<p>Network traffic arrives in the form of <em>packets</em>, which are routed to the correct IP address in a process called <em>packet switching</em>. You don’t need to understand any more about packet switching than that it reliable gets packets to the right IP Address.<a href="#fn3" class="footnote-ref" id="fnref3" role="doc-noteref"><sup>3</sup></a></p>
+<p>Once the traffic arrives at the server, it has to get to the right service by getting to the right port. Every computer has just over 65,000 ports. Each port is uniquely identified by a number, and there’s a 1-1 mapping between listening services and open ports. Since you’re probably running no more than a handful of services, the overwhelming majority of the ports are closed at any given time.<a href="#fn4" class="footnote-ref" id="fnref4" role="doc-noteref"><sup>4</sup></a></p>
+<p>By default, HTTP traffic goes to port <span class="math inline">\(80\)</span> and HTTPS traffic goes to port <span class="math inline">\(443\)</span>. So if there’s just one service, you would configure the application to listen on port <span class="math inline">\(80\)</span> and/or <span class="math inline">\(443\)</span>. Then, when people come in, they’d automatically get to the right service.</p>
+<p>But sometimes you’ve got multiple services on the server. In that case, each one will need to run on a unique port. However, you don’t want to force users to remember, for example, that they access JupyterHub on port <span class="math inline">\(8000\)</span>. Instead, you want them just to know that it’s on <span class="math inline">\(\text{/jupyter}\)</span>.</p>
+<p>A <em>proxy</em> is a piece of software that can be used to map paths to another location. Common proxies you might hear about include the open source <em>NGINX</em> and <em>Apache</em> and the paid <em>F5</em>, which is the developer of NGINX. Depending on the configuration, the proxy can be on the same server or a different one.</p>
+<p>If you’re using a proxy, you’d put each of the server’s services on a different port and use the proxy to redirect incoming traffic to the right place based on the subpath.</p>
+<p>Now, if you were just to put something on port <span class="math inline">\(80\)</span> on your EC2 instance and try to access it from the web, it still wouldn’t work. That’s because there’s a <em>firewall</em> sitting in front of your EC2 instance, which blocks traffic to all but certain ports. In AWS, the default firewall is the <em>security group</em>.</p>
+<p>In addition to blocking traffic to arriving at certain ports, firewalls can be restricted to allow access only from certain IP Addresses. This can be used, for example, to only allow access from your office to a server. Unless a particular server will only ever be accessed by other servers with known IP addresses, this is a brittle way to configure security and I generally don’t recommend it.</p>
+<div class="callout callout-style-default callout-tip callout-titled">
+<div class="callout-header d-flex align-content-center">
+<div class="callout-icon-container">
+<i class="callout-icon"></i>
+</div>
+<div class="callout-title-container flex-fill">
+Tip
+</div>
+</div>
+<div class="callout-body-container callout-body">
+<p>If you think you’ve configured a service correctly and you just can’t seem to access it, one of the first things to check is whether you’ve got the port open in the security group.</p>
+<p>One symptom that may indicate a security group issue is if you try to go to your service and it just hangs with no response before eventually timing out.</p>
+</div>
+</div>
+<p><img src="images/firewall-proxy.png" class="img-fluid" alt="Traffic coming through firewall only on port 80. Proxy routes /jupyter to port 8000 on server and /rstudio to port 8787." width="600"></p>
+<p>Once the traffic makes it to the right server, through the firewall and proxy, and to the right port, it has to communicate using the right application layer protocol. We’ve been talking exclusively about the HTTP and HTTPS application layer protocols, because web traffic arrives as a series of HTTP <code>GET</code> requests, but there are many other application layer protocols, each with its own default port.</p>
+<p>For example, you’ve already seen a lot about SSH in this book, which is an application layer protocol for allowing secure login and communication over an unsecured network. SSH defaults to port <span class="math inline">\(22\)</span>.</p>
+<p>Other important protocols that you might see in this book or elsewhere are SFTP for file transfers, SMTP for emails, LDAP(S) for auth, and websockets, which are used by Shiny and Streamlit.</p>
+</section>
+<section id="recognizing-ip-addresses" class="level2" data-number="12.3">
+<h2 data-number="12.3" class="anchored" data-anchor-id="recognizing-ip-addresses"><span class="header-section-number">12.3</span> Recognizing IP addresses</h2>
+<p>If you’ve seen an IP address before, it probably was an <em>IPv4</em> <em>address</em>, which are four blocks of 8-bit fields (numbers between <span class="math inline">\(0\)</span> and <span class="math inline">\(255\)</span>) with dots in between, so they look like <span class="math inline">\(64.56.223.5\)</span>.</p>
+<p>If you do the math, you’ll realize there are “only” about 4 billion of these. There are so many things on the public internet that we are running out of IPv4 addresses. The good news is that smart people started planning for this a while ago and the adoption of the new <em>IPv6</em> standard started a few years ago.</p>
+<p>IPv6 addresses are eight blocks of hexadecimal (<span class="math inline">\(\text{0-9}\)</span> and <span class="math inline">\(\text{a-f}\)</span>) digits separated by colons, with certain rules that allow them to be shortened, so <span class="math inline">\(\text{4b01:0db8:85a3:0000:0000:8a2e:0370:7334}\)</span> or <span class="math inline">\(\text{3da4:66a::1}\)</span> are both examples of valid IPv6 addresses. There’s no worry about running out of IPv6 addresses any time soon, because the total quantity of IPv6 addresses is a number with 39 zeroes.</p>
+<p>IPv6 will coexist with IPv4 for a few decades and we’ll eventually switch entirely to IPv6.</p>
+<p>There are a few special IPv4 addresses it’s worth knowing. You’ll probably see <span class="math inline">\(127.0.0.1\)</span> a lot, which is also known as <span class="math inline">\(\text{localhost}\)</span> or loopback. This is the way a machine refers to itself.</p>
+<p>For example, if you open a Shiny app in RStudio Desktop, the app will pop up in a little window along with a notice that says</p>
+<div class="sourceCode" id="cb1"><pre class="sourceCode numberSource {bash} number-lines code-with-copy"><code class="sourceCode"><span id="cb1-1"><a href="#cb1-1"></a>Listening on http://127.0.0.1:6311</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+<p>That means that the Shiny app is running on the same computer and is available on port <span class="math inline">\(6311\)</span>. You can open that location in your browser to view the app as it runs.</p>
+<p>There are also a few blocks of IPv4 addresses – those that start with <span class="math inline">\(192.168\)</span>, <span class="math inline">\(172.16\)</span>, and <span class="math inline">\(10\)</span> that are reserved for use on private networks, so they’re never assigned in public.</p>
+</section>
+<section id="basic-network-administration" class="level2" data-number="12.4">
+<h2 data-number="12.4" class="anchored" data-anchor-id="basic-network-administration"><span class="header-section-number">12.4</span> Basic network administration</h2>
+<p>Networking can be difficult to manage because there are so many layers. It will frequently happen that you think a service is configured, but you just can’t seem to access it. Here are some basic tools for network debugging.</p>
+<section id="browser-devtools" class="level3" data-number="12.4.1">
+<h3 data-number="12.4.1" class="anchored" data-anchor-id="browser-devtools"><span class="header-section-number">12.4.1</span> Browser devtools</h3>
+<p>One of the most useful tools for debugging networking issues can be found in the menus of your web browser. It has developer tools that allow you to inspect the network traffic going back and forth between your machine and a remote.</p>
+<p>This can be really handy if things are going slowly or if you’re not sure why the page isn’t loading. By inspecting the status codes of different HTTP calls and the time they take, you can develop a pretty good idea of where things might be getting stuck.</p>
+</section>
+<section id="ssh-tunnelingport-forwarding" class="level3" data-number="12.4.2">
+<h3 data-number="12.4.2" class="anchored" data-anchor-id="ssh-tunnelingport-forwarding"><span class="header-section-number">12.4.2</span> SSH tunneling/port forwarding</h3>
+<p>When you start a new EC2 instance in AWS, the default security group opens only port <span class="math inline">\(22\)</span>, so only SSH traffic is allowed.</p>
+<p>So far, you’ve seen SSH used to access the command line on that remote server, but SSH can actually be used to access any port in a process called <em>tunneling</em> or <em>port forwarding</em>.</p>
+<p>When you tunnel, you make a port on the remote host available at the same port on <span class="math inline">\(\text{localhost}\)</span> on your machine. The most common usage is to use your browser to look at what’s available at a specific port on a server via HTTP without configuring the host to accept HTTP traffic on that port.</p>
+<p>You can create an SSH tunnel to a remote host with</p>
+<div class="code-with-filename">
+<div class="code-with-filename-file">
+<pre><strong>Terminal</strong></pre>
+</div>
+<div class="sourceCode" id="cb2"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb2-1"><a href="#cb2-1"></a><span class="fu">ssh</span> <span class="at">-L</span> <span class="op">&lt;</span>remote port<span class="op">&gt;</span>:localhost:<span class="op">&lt;</span>local port<span class="op">&gt;</span> <span class="op">&lt;</span>user<span class="op">&gt;</span>@<span class="op">&lt;</span>server<span class="op">&gt;</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+</div>
+<p>I find that the syntax for port forwarding completely defies my memory and I have to google it every time I use it.<a href="#fn5" class="footnote-ref" id="fnref5" role="doc-noteref"><sup>5</sup></a></p>
+<p>So, for example, if your server were running at <span class="math inline">\(64.56.223.5\)</span> and you has the SSH user <code>test-user</code>, you might forward JupyterHub on port <span class="math inline">\(8000\)</span> with <code>ssh -L 8000:localhost:8000 test-user@64.56.223.5</code>. Once the tunnel is established, you could access JupyerHub in your browser on <span class="math inline">\(\text{localhost:8000}\)</span>.</p>
+</section>
+<section id="checking-what-ports-are-open" class="level3" data-number="12.4.3">
+<h3 data-number="12.4.3" class="anchored" data-anchor-id="checking-what-ports-are-open"><span class="header-section-number">12.4.3</span> Checking what ports are open</h3>
+<p>Sometimes you can just forget what ports are open on your machine and for what purposes. Or you want to double check that a configuration change took. In that case, you want to use the <code>netstat</code> command to get the services that are running and their associated ports.</p>
+<p>For this use, <code>netstat</code> is generally most useful with the <code>-tlp</code> flags to show programs that are listening and the programs associated.</p>
+</section>
+<section id="checking-if-a-host-is-accessible" class="level3" data-number="12.4.4">
+<h3 data-number="12.4.4" class="anchored" data-anchor-id="checking-if-a-host-is-accessible"><span class="header-section-number">12.4.4</span> Checking if a host is accessible</h3>
+<p>The <code>ping</code> command can be useful for checking whether your server is reachable on the network. For example, the server where this book lives is at <span class="math inline">\(185.199.110.153\)</span>. So I can ping that domain to check if it’s accessible.</p>
+<div class="sourceCode" id="cb3"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb3-1"><a href="#cb3-1"></a><span class="op">&gt;</span> ping <span class="ex">-o</span> 185.199.110.153</span>
+<span id="cb3-2"><a href="#cb3-2"></a></span>
+<span id="cb3-3"><a href="#cb3-3"></a><span class="ex">PING</span> 185.199.110.153 <span class="er">(</span><span class="ex">185.199.110.153</span><span class="kw">)</span><span class="bu">:</span> 56 data bytes</span>
+<span id="cb3-4"><a href="#cb3-4"></a><span class="ex">64</span> bytes from 185.199.110.153: icmp_seq=0 ttl=58 time=23.322 ms</span>
+<span id="cb3-5"><a href="#cb3-5"></a></span>
+<span id="cb3-6"><a href="#cb3-6"></a><span class="ex">---</span> 185.199.110.153 ping statistics <span class="at">---</span></span>
+<span id="cb3-7"><a href="#cb3-7"></a><span class="ex">1</span> packets transmitted, 1 packets received, 0.0% packet loss</span>
+<span id="cb3-8"><a href="#cb3-8"></a><span class="ex">round-trip</span> min/avg/max/stddev = 23.322/23.322/23.322/nan ms</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+<p>The <code>-o</code> flag tells <code>ping</code> to try just once as opposed to pinging continuously. The fact that I transmitted and received one packet means that everything is working properly.</p>
+<p>Seeing an unreachable host or packet loss would be an indication that my networking probably isn’t configured correctly somewhere between me and the server. That means it’s time to check that the server is actually up, followed by firewalls (security groups) and proxies. You can also use ping with a domain, so it can also be used to see if DNS is working properly.</p>
+<p>If <code>ping</code> succeeds but a particular resource is inaccessible, <code>curl</code> is can be useful. <code>curl</code> actually attempts to fetch the website at a particular URL. It’s often useful to use <code>curl</code> with the <code>-I</code> option so it just returns a simple status report, not the full contents of what it finds there.</p>
+<p>For example, here’s what I get when I <code>curl</code> the website for this book.</p>
+<div class="sourceCode" id="cb4"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb4-1"><a href="#cb4-1"></a><span class="op">&gt;</span> curl <span class="ex">-I</span> https://do4ds.com                                         </span>
+<span id="cb4-2"><a href="#cb4-2"></a></span>
+<span id="cb4-3"><a href="#cb4-3"></a><span class="ex">HTTP/2</span> 200</span>
+<span id="cb4-4"><a href="#cb4-4"></a><span class="ex">server:</span> GitHub.com</span>
+<span id="cb4-5"><a href="#cb4-5"></a><span class="ex">content-type:</span> text/html<span class="kw">;</span> <span class="va">charset</span><span class="op">=</span>utf-8</span>
+<span id="cb4-6"><a href="#cb4-6"></a><span class="ex">last-modified:</span> Tue, 04 Jul 2023 16:23:38 GMT</span>
+<span id="cb4-7"><a href="#cb4-7"></a><span class="ex">access-control-allow-origin:</span> <span class="pp">*</span></span>
+<span id="cb4-8"><a href="#cb4-8"></a><span class="ex">etag:</span> <span class="st">"64a4478a-79cb"</span></span>
+<span id="cb4-9"><a href="#cb4-9"></a><span class="ex">...</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+<p>The important thing here is that first line. The server is returning a <code>200</code> HTTP status code, which means all is well. If you get something else, take a look at the http code cheatsheet in <a href="../append/cheatsheets.html">Appendix&nbsp;<span>C</span></a>.</p>
+<p>If <code>ping</code> succeeds, but <code>curl</code> does not, it means that the server is up, but the path or port is incorrect. If you’re running inside a container, you should check that you’ve properly configured the port inside container to be forwarded to the outside.</p>
+</section>
+</section>
+<section id="comprehension-questions" class="level2" data-number="12.5">
+<h2 data-number="12.5" class="anchored" data-anchor-id="comprehension-questions"><span class="header-section-number">12.5</span> Comprehension Questions</h2>
+<ol type="1">
+<li>What are the 4 components of a URL? What’s the significance of each?</li>
+<li>Are there any inherent differences between public and private IP addresses?</li>
+<li>Draw a mind map of trying to access the following in your browser. Include the following terms: URL, domain, IP Address, port, path, <span class="math inline">\(80\)</span>, <span class="math inline">\(443\)</span>, <code>8000</code>, proxy, server, HTTP, HTTPS, status code, protocol
+<ol type="1">
+<li>A Shiny app on a server at <span class="math inline">\(\text{http://my-shiny.com}\)</span> where Shiny Server is sitting on port <span class="math inline">\(80\)</span>.</li>
+<li>JupyterHub on a server at <span class="math inline">\(\text{https://example.com/jupyter}\)</span> where Jupyter is on port <span class="math inline">\(8000\)</span>.</li>
+</ol></li>
+</ol>
+</section>
+<section id="lab-making-it-accessible-in-one-place" class="level2" data-number="12.6">
+<h2 data-number="12.6" class="anchored" data-anchor-id="lab-making-it-accessible-in-one-place"><span class="header-section-number">12.6</span> Lab: Making it accessible in one place</h2>
+<p>In this lab, we’re going to set up a proxy to be able to access all of our services over HTTP.</p>
+<p>But first, you might want to try out accessing the various services where they are.</p>
+<p>You could either try SSH tunneling to them and seeing them on localhost or you could apply custom TCP rules to your security group to temporarily allow access directly to the services. If you want to try, here’s a reminder of where everything is:</p>
+<table class="table">
+<thead>
+<tr class="header">
+<th>Service</th>
+<th>Port</th>
+</tr>
+</thead>
+<tbody>
+<tr class="odd">
+<td>JupyterHub</td>
+<td><span class="math inline">\(8000\)</span></td>
+</tr>
+<tr class="even">
+<td>RStudio</td>
+<td><span class="math inline">\(8787\)</span></td>
+</tr>
+<tr class="odd">
+<td>Penguin model API</td>
+<td><span class="math inline">\(8080\)</span></td>
+</tr>
+<tr class="even">
+<td>Shiny App</td>
+<td><span class="math inline">\(3838\)</span></td>
+</tr>
+</tbody>
+</table>
+<p>If you’re through playing and ready to get everything configured, let’s go ahead. If you changed your security group rules, change them back.</p>
+<section id="step-1-configure-nginx" class="level3" data-number="12.6.1">
+<h3 data-number="12.6.1" class="anchored" data-anchor-id="step-1-configure-nginx"><span class="header-section-number">12.6.1</span> Step 1: Configure Nginx</h3>
+<p>Honestly, configuring proxies is a somewhat advanced networking topic, and in most cases you’d just put one service per server. But if you want to be able to save money and run everything on one server, you’ll want a proxy.</p>
+<p>Configuring Nginx is pretty straightforward – you install Nginx, put the configuration file into place, and restart the service to pick up the changes. The hard part is figuring out the right configuration. Configuring proxies can be quite painful, as the configuration is very sensitive to seemingly meaningless syntax issues.</p>
+<p>Here are the steps to configure your proxy on your server for JupyterHub and RStudio Server:</p>
+<ol type="1">
+<li>SSH into your server.</li>
+<li>Install Nginx with <code>sudo apt install nginx</code>.</li>
+<li>Save a backup of the default <code>nginx.conf</code>, <code>cp /etc/nginx/nginx.conf /etc/nginx/nginx-backup.conf</code>.<a href="#fn6" class="footnote-ref" id="fnref6" role="doc-noteref"><sup>6</sup></a></li>
+<li>Edit the Nginx configuration with <code>sudo vim /etc/nginx/nginx.conf</code> and replace it with:</li>
+</ol>
+<div class="code-with-filename">
+<div class="code-with-filename-file">
+<pre><strong>/etc/nginx/nginx.conf</strong></pre>
+</div>
+<div class="sourceCode" id="cb5"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb5-1"><a href="#cb5-1"></a><span class="ex">user</span> www-data<span class="kw">;</span></span>
+<span id="cb5-2"><a href="#cb5-2"></a><span class="ex">worker_processes</span> auto<span class="kw">;</span></span>
+<span id="cb5-3"><a href="#cb5-3"></a><span class="ex">pid</span> /run/nginx.pid<span class="kw">;</span></span>
+<span id="cb5-4"><a href="#cb5-4"></a><span class="ex">include</span> /etc/nginx/modules-enabled/<span class="pp">*</span>.conf<span class="kw">;</span></span>
+<span id="cb5-5"><a href="#cb5-5"></a></span>
+<span id="cb5-6"><a href="#cb5-6"></a><span class="ex">events</span> {</span>
+<span id="cb5-7"><a href="#cb5-7"></a>	<span class="ex">worker_connections</span> 768<span class="kw">;</span></span>
+<span id="cb5-8"><a href="#cb5-8"></a>	<span class="co"># multi_accept on;</span></span>
+<span id="cb5-9"><a href="#cb5-9"></a><span class="er">}</span></span>
+<span id="cb5-10"><a href="#cb5-10"></a></span>
+<span id="cb5-11"><a href="#cb5-11"></a><span class="ex">http</span> {</span>
+<span id="cb5-12"><a href="#cb5-12"></a></span>
+<span id="cb5-13"><a href="#cb5-13"></a> <span class="ex">map</span> <span class="va">$http_upgrade</span> <span class="va">$connection_upgrade</span> {</span>
+<span id="cb5-14"><a href="#cb5-14"></a>    		<span class="ex">default</span> upgrade<span class="kw">;</span></span>
+<span id="cb5-15"><a href="#cb5-15"></a>    		<span class="st">''</span>      close<span class="kw">;</span></span>
+<span id="cb5-16"><a href="#cb5-16"></a>  <span class="er">}</span></span>
+<span id="cb5-17"><a href="#cb5-17"></a></span>
+<span id="cb5-18"><a href="#cb5-18"></a>  <span class="ex">server</span> {</span>
+<span id="cb5-19"><a href="#cb5-19"></a>    <span class="ex">listen</span> 80<span class="kw">;</span></span>
+<span id="cb5-20"><a href="#cb5-20"></a></span>
+<span id="cb5-21"><a href="#cb5-21"></a>    <span class="ex">location</span> /rstudio/ {</span>
+<span id="cb5-22"><a href="#cb5-22"></a>      <span class="co"># Needed only for a custom path prefix of /rstudio</span></span>
+<span id="cb5-23"><a href="#cb5-23"></a>      <span class="ex">rewrite</span> ^/rstudio/<span class="er">(</span><span class="bu">.</span><span class="pp">*</span><span class="kw">)</span><span class="ex">$</span> /<span class="va">$1</span> break<span class="kw">;</span></span>
+<span id="cb5-24"><a href="#cb5-24"></a></span>
+<span id="cb5-25"><a href="#cb5-25"></a>      <span class="co"># Use http here when ssl-enabled=0 is set in rserver.conf</span></span>
+<span id="cb5-26"><a href="#cb5-26"></a>      <span class="ex">proxy_pass</span> http://localhost:8787<span class="kw">;</span></span>
+<span id="cb5-27"><a href="#cb5-27"></a></span>
+<span id="cb5-28"><a href="#cb5-28"></a>      <span class="ex">proxy_http_version</span> 1.1<span class="kw">;</span></span>
+<span id="cb5-29"><a href="#cb5-29"></a>      <span class="ex">proxy_set_header</span> Upgrade <span class="va">$http_upgrade</span><span class="kw">;</span></span>
+<span id="cb5-30"><a href="#cb5-30"></a>      <span class="ex">proxy_set_header</span> Connection <span class="va">$connection_upgrade</span><span class="kw">;</span></span>
+<span id="cb5-31"><a href="#cb5-31"></a>      <span class="ex">proxy_read_timeout</span> 20d<span class="kw">;</span></span>
+<span id="cb5-32"><a href="#cb5-32"></a></span>
+<span id="cb5-33"><a href="#cb5-33"></a>      <span class="co"># Not needed if www-root-path is set in rserver.conf</span></span>
+<span id="cb5-34"><a href="#cb5-34"></a>      <span class="ex">proxy_set_header</span> X-RStudio-Root-Path /rstudio<span class="kw">;</span></span>
+<span id="cb5-35"><a href="#cb5-35"></a></span>
+<span id="cb5-36"><a href="#cb5-36"></a>      <span class="co"># Optionally, use an explicit hostname and omit the port if using 80/443</span></span>
+<span id="cb5-37"><a href="#cb5-37"></a>      <span class="ex">proxy_set_header</span> Host <span class="va">$host</span>:<span class="va">$server_port</span><span class="kw">;</span></span>
+<span id="cb5-38"><a href="#cb5-38"></a>    <span class="er">}</span></span>
+<span id="cb5-39"><a href="#cb5-39"></a></span>
+<span id="cb5-40"><a href="#cb5-40"></a>    <span class="ex">location</span> /jupyter/ {</span>
+<span id="cb5-41"><a href="#cb5-41"></a>      <span class="co"># </span><span class="al">NOTE</span><span class="co"> important to also set bind url of jupyterhub to /jupyter in its config</span></span>
+<span id="cb5-42"><a href="#cb5-42"></a>      <span class="ex">proxy_pass</span> http://127.0.0.1:8000<span class="kw">;</span></span>
+<span id="cb5-43"><a href="#cb5-43"></a></span>
+<span id="cb5-44"><a href="#cb5-44"></a>      <span class="ex">proxy_redirect</span>   off<span class="kw">;</span></span>
+<span id="cb5-45"><a href="#cb5-45"></a>      <span class="ex">proxy_set_header</span> X-Real-IP <span class="va">$remote_addr</span><span class="kw">;</span></span>
+<span id="cb5-46"><a href="#cb5-46"></a>      <span class="ex">proxy_set_header</span> Host <span class="va">$host</span><span class="kw">;</span></span>
+<span id="cb5-47"><a href="#cb5-47"></a>      <span class="ex">proxy_set_header</span> X-Forwarded-For <span class="va">$proxy_add_x_forwarded_for</span><span class="kw">;</span></span>
+<span id="cb5-48"><a href="#cb5-48"></a>      <span class="ex">proxy_set_header</span> X-Forwarded-Proto <span class="va">$scheme</span><span class="kw">;</span></span>
+<span id="cb5-49"><a href="#cb5-49"></a></span>
+<span id="cb5-50"><a href="#cb5-50"></a>      <span class="co"># websocket headers</span></span>
+<span id="cb5-51"><a href="#cb5-51"></a>      <span class="ex">proxy_set_header</span> Upgrade <span class="va">$http_upgrade</span><span class="kw">;</span></span>
+<span id="cb5-52"><a href="#cb5-52"></a>      <span class="ex">proxy_set_header</span> Connection <span class="va">$connection_upgrade</span><span class="kw">;</span></span>
+<span id="cb5-53"><a href="#cb5-53"></a>    <span class="er">}</span></span>
+<span id="cb5-54"><a href="#cb5-54"></a>  <span class="er">}</span></span>
+<span id="cb5-55"><a href="#cb5-55"></a><span class="er">}</span></span>
+<span id="cb5-56"><a href="#cb5-56"></a></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+</div>
+<ol start="4" type="1">
+<li>Test that your configuration is valid <code>sudo nginx -t</code>.</li>
+<li>Start Nginx with <code>sudo systemctl start nginx</code>. If you see nothing all is well.</li>
+</ol>
+<p>If you need to change anything, update the config and then restart with <code>sudo systemctl restart nginx</code>.</p>
+</section>
+<section id="step-2-open-port-80" class="level3" data-number="12.6.2">
+<h3 data-number="12.6.2" class="anchored" data-anchor-id="step-2-open-port-80"><span class="header-section-number">12.6.2</span> Step 2: Open port 80</h3>
+<p>Now, if you try to go to your your server’s public IP address or DNS, your browser will spin for a while and nothing will happen. That’s because the AWS security group still only allows SSH access on port <span class="math inline">\(22\)</span>. We need to add a rule that will allow HTTP access on port <span class="math inline">\(80\)</span>.</p>
+<p>On the AWS console page for your instance, find the Security section and click into the security group for your instance. You want to add a new inbound HTTP rule that allows access on port <span class="math inline">\(80\)</span> from anywhere. Make sure not to get rid of the rule that allows SSH access on <span class="math inline">\(22\)</span>. You still need that one too.</p>
+<p>Once you do this, you should be able to visit your server address and get the default Nginx landing page.</p>
+</section>
+<section id="step-3-configure-your-subpaths" class="level3" data-number="12.6.3">
+<h3 data-number="12.6.3" class="anchored" data-anchor-id="step-3-configure-your-subpaths"><span class="header-section-number">12.6.3</span> Step 3: Configure your subpaths</h3>
+<p>Complex web apps like RStudio and JupyterHub frequently proxy traffic back to themselves. For example, when you launch a Shiny app in RStudio, you’re actually just opening a “headless” browser window that gets proxied back into your session.</p>
+<p>This works by default when those apps are on the root path <span class="math inline">\(\text{/}\)</span>. That’s not true in this case, so we’ve got to let the services know where they’re actually located.</p>
+<p>Configuring RStudio Server is already done. The <code>X-RStudio-Root-Path</code> line in the Nginx configuration adds a header to each request coming through the proxy that tells RStudio Server that it’s on the <span class="math inline">\(\text{/rstudio}\)</span> path.</p>
+<p>JupyterHub needs a configuration update to let it know that it’s on a subpath. Luckily it’s a very simple change. You can edit the Jupyter configuration with</p>
+<div class="code-with-filename">
+<div class="code-with-filename-file">
+<pre><strong>Terminal</strong></pre>
+</div>
+<div class="sourceCode" id="cb6"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb6-1"><a href="#cb6-1"></a><span class="fu">sudo</span> vim /etc/jupyterhub/jupyterhub_config.py</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+</div>
+<p>Find the line that reads <code># c.JupyterHub.bind_url = 'http://:8000'</code>.</p>
+<div class="callout callout-style-default callout-tip callout-titled">
+<div class="callout-header d-flex align-content-center">
+<div class="callout-icon-container">
+<i class="callout-icon"></i>
+</div>
+<div class="callout-title-container flex-fill">
+Tip
+</div>
+</div>
+<div class="callout-body-container callout-body">
+<p>You can search in vim from normal mode with <code>/ &lt;thing you're searching for&gt;</code>. Go to the next hit with <code>n</code>.</p>
+</div>
+</div>
+<p>Delete the <code>#</code> to uncomment the line and add the subpath on the end. If you’re using the <span class="math inline">\(\text{/jupyter}\)</span> subpath and the default <span class="math inline">\(8000\)</span> port, that line will read <code>c.JupyterHub.bind_url = 'http://:8000/jupyter'</code>.</p>
+<p>JupyterHub should pick up the new config when it’s restarted with</p>
+<div class="code-with-filename">
+<div class="code-with-filename-file">
+<pre><strong>Terminal</strong></pre>
+</div>
+<div class="sourceCode" id="cb7"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb7-1"><a href="#cb7-1"></a><span class="fu">sudo</span> systemctl restart jupyterhub</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+</div>
+</section>
+<section id="step-4-try-it-out" class="level3" data-number="12.6.4">
+<h3 data-number="12.6.4" class="anchored" data-anchor-id="step-4-try-it-out"><span class="header-section-number">12.6.4</span> Step 4: Try it out!</h3>
+<p>Now we should have each service configured on a subpath. RStudio Server at <span class="math inline">\(\text{/rstudio}\)</span>, JupyterHub at <span class="math inline">\(\text{/jupyter}\)</span>. For example, with my server at <span class="math inline">\(\text{64.56.223.5}\)</span>, I can get to RStudio Server at <span class="math inline">\(\text{http://64.56.223.5/rstudio}\)</span>.</p>
+<p>Note that right now, this server is on HTTP, which is not a best practice. In fact, it’s such a bad practice that your browser will probably autocorrect the url to <code>https</code> and you’ll have to manually correct it back to <code>http</code> and ignore some scary warnings. Don’t worry, we’ll fix this in <a href="2-8-ssl.html">Chapter&nbsp;<span>14</span></a>.</p>
+</section>
+<section id="lab-extensions" class="level3" data-number="12.6.5">
+<h3 data-number="12.6.5" class="anchored" data-anchor-id="lab-extensions"><span class="header-section-number">12.6.5</span> Lab Extensions</h3>
+<p>If you’ve gone to the root URL for your server, you’ve probably noticed that it’s just the default Nginx landing page, which is not very attractive.</p>
+<p>You might want to create a landing page with links to the subpath by serving a static html page off of <span class="math inline">\(\text{/}\)</span>. Or maybe you want one of the services at <span class="math inline">\(\text{/}\)</span> and the others at a different subpath.</p>
+<p>Right now, neither the penguins model API or the Shiny app are available from the outside. You might want to add them to the proxy to make them accessible. I’ll leave that as an exercise for you.</p>
+<div class="callout callout-style-default callout-tip callout-titled">
+<div class="callout-header d-flex align-content-center">
+<div class="callout-icon-container">
+<i class="callout-icon"></i>
+</div>
+<div class="callout-title-container flex-fill">
+Tip
+</div>
+</div>
+<div class="callout-body-container callout-body">
+<p>It’s very common to put an API and/or a Shiny app behind a proxy. Googling “Shiny app behind nginx” or “FastAPI with nginx” will yield good results.</p>
+</div>
+</div>
+<p>One thing to consider is whether the model API should be publicly accessible at all. If the only thing calling it is the Shiny app, maybe it shouldn’t be?</p>
+
+
+</section>
+</section>
+<section id="footnotes" class="footnotes footnotes-end-of-document" role="doc-endnotes">
+<hr>
+<ol>
+<li id="fn1"><p>URLs are a subset of a broader category called <em>Uniform Resource Identifiers (URIs)</em>, which look like a URL and are used to <strong>identify</strong> a resource by may not be a valid address. I mention them only because you may run across them in certain contexts, like configuring SSO.<a href="#fnref1" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
+<li id="fn2"><p>Different resources divide URLs into somewhere between three and seven parts. I think these four are the most useful for this chapter’s purpose.<a href="#fnref2" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
+<li id="fn3"><p>How packet switching works isn’t super relevant, but it is cool. Packets are addressed with their target IP address when they’re first created and are passed off to the router to which the computer is connected. Routers are arranged in a tree-style hierarchy. What’s clever is that each router <strong>only</strong> keeps track of downstream addresses and a single upstream <em>default address</em>. So the packet gets passed upstream until it hits a router that knows about the target IP address and then back downstream to the host.<a href="#fnref3" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
+<li id="fn4"><p>Ports are also used for outbound communication. Computers know how to automatically open ports for outbound communication and specify that’s where the response should come, so we’re not going to get into them here.<a href="#fnref4" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
+<li id="fn5"><p>As you might guess from this complicated syntax, you can do a lot more than this with SSH tunneling, but this is most often what I use it for.<a href="#fnref5" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
+<li id="fn6"><p>This is generally a good practice before you start messing with config files. Bad configuration is usually preferable to a service that can’t start at all because you’ve messed up the config so badly. It happens.<a href="#fnref6" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
+</ol>
+</section>
+
+</main> <!-- /main -->
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+        <i class="bi bi-arrow-left-short"></i> <span class="nav-page-text"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Server Resources and Scaling</span></span>
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+      <nav class="quarto-page-breadcrumbs" aria-label="breadcrumb"><ol class="breadcrumb"><li class="breadcrumb-item"><a href="../../chapters/sec2/2-0-sec-intro.html">IT/Admin for Data Science</a></li><li class="breadcrumb-item"><a href="../../chapters/sec2/2-7-dns.html"><span class="chapter-number">13</span>&nbsp; <span class="chapter-title">DNS allows for human-readable addresses</span></a></li></ol></nav>
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@@ -213,13 +213,19 @@
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  <span class="menu-text"><span class="chapter-number">5</span>&nbsp; <span class="chapter-title">Deployments and code promotion</span></span></a>
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+</li>
+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/sec1/1-6-docker.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">6</span>&nbsp; <span class="chapter-title">Demystifying Docker</span></span></a>
+  </div>
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- <span class="menu-text">IT/Admin Tools</span></a>
+ <span class="menu-text">IT/Admin for Data Science</span></a>
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- <span class="menu-text"><span class="chapter-number">6</span>&nbsp; <span class="chapter-title">Opening the Command Line</span></span></a>
+  <a href="../../chapters/sec2/2-1-cloud.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">7</span>&nbsp; <span class="chapter-title">The Cloud</span></span></a>
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- <span class="menu-text"><span class="chapter-number">7</span>&nbsp; <span class="chapter-title">Using the Command Line</span></span></a>
+  <a href="../../chapters/sec2/2-2-cmd-line.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">8</span>&nbsp; <span class="chapter-title">Customizing the command line</span></span></a>
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- <span class="menu-text"><span class="chapter-number">8</span>&nbsp; <span class="chapter-title">Secure server connections with SSH</span></span></a>
+  <a href="../../chapters/sec2/2-3-linux.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">9</span>&nbsp; <span class="chapter-title">Intro to Linux Administration</span></span></a>
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- <span class="menu-text"><span class="chapter-number">9</span>&nbsp; <span class="chapter-title">Demystifying Docker</span></span></a>
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- <span class="menu-text"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Getting Started with the Cloud</span></span></a>
+  <a href="../../chapters/sec2/2-4-app-admin.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Application administration</span></span></a>
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- <span class="menu-text"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Basic Linux SysAdmin</span></span></a>
+  <a href="../../chapters/sec2/2-5-scale.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Server Resources and Scaling</span></span></a>
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-  <a href="../../chapters/sec3/3-3-networking.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-6-networking.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">12</span>&nbsp; <span class="chapter-title">Intro to Computer Networks</span></span></a>
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-  <a href="../../chapters/sec3/3-4-dns.html" class="sidebar-item-text sidebar-link active">
+  <a href="../../chapters/sec2/2-7-dns.html" class="sidebar-item-text sidebar-link active">
  <span class="menu-text"><span class="chapter-number">13</span>&nbsp; <span class="chapter-title">DNS allows for human-readable addresses</span></span></a>
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-  <a href="../../chapters/sec3/3-5-ssl.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-8-ssl.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">14</span>&nbsp; <span class="chapter-title">You should use SSL/HTTPS</span></span></a>
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- <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Choosing the right server for you</span></span></a>
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+            <a href="../../chapters/sec3/3-0-sec-intro.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text">Making it Enterprise-Grade</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true" aria-label="Toggle section">
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+      <ul id="quarto-sidebar-section-3" class="collapse list-unstyled sidebar-section depth1 show">  
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-  <a href="../../chapters/sec4/4-1-os-ds-in-ent.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></a>
+  <a href="../../chapters/sec3/3-1-os-ds-in-ent.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></a>
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- <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></a>
+  <a href="../../chapters/sec3/3-2-ent-networks.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></a>
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- <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></a>
+  <a href="../../chapters/sec3/3-3-auth.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></a>
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- <span class="menu-text"><span class="chapter-number">19</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></a>
+  <a href="../../chapters/sec3/3-4-ent-servers.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></a>
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       <div class="sidebar-item-container"> 
-            <a class="sidebar-item-text sidebar-link text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-5" aria-expanded="true">
+            <a class="sidebar-item-text sidebar-link text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true">
  <span class="menu-text">Appendices</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-5" aria-expanded="true" aria-label="Toggle section">
+          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true" aria-label="Toggle section">
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+      <ul id="quarto-sidebar-section-4" class="collapse list-unstyled sidebar-section depth1 show">  
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@@ -353,6 +336,12 @@
   <a href="../../chapters/append/lab-map.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">B</span>&nbsp; <span class="chapter-title">Lab Map</span></span></a>
   </div>
+</li>
+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/append/cheatsheets.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">C</span>&nbsp; <span class="chapter-title">Cheatsheets</span></span></a>
+  </div>
 </li>
       </ul>
   </li>
@@ -366,19 +355,19 @@
     <h2 id="toc-title">Table of contents</h2>
    
   <ul>
-  <li><a href="#how-dns-lookups-work" id="toc-how-dns-lookups-work" class="nav-link active" data-scroll-target="#how-dns-lookups-work"><span class="header-section-number">13.1</span> How DNS lookups work</a></li>
+  <li><a href="#basics-of-dns-and-domains" id="toc-basics-of-dns-and-domains" class="nav-link active" data-scroll-target="#basics-of-dns-and-domains"><span class="header-section-number">13.1</span> Basics of DNS and domains</a></li>
   <li><a href="#how-dns-is-configured" id="toc-how-dns-is-configured" class="nav-link" data-scroll-target="#how-dns-is-configured"><span class="header-section-number">13.2</span> How DNS is configured</a></li>
   <li><a href="#comprehension-questions" id="toc-comprehension-questions" class="nav-link" data-scroll-target="#comprehension-questions"><span class="header-section-number">13.3</span> Comprehension Questions</a></li>
   <li><a href="#lab-configuring-dns-for-your-server" id="toc-lab-configuring-dns-for-your-server" class="nav-link" data-scroll-target="#lab-configuring-dns-for-your-server"><span class="header-section-number">13.4</span> Lab: Configuring DNS for your server</a>
   <ul class="collapse">
-  <li><a href="#step-1-allocate-elastic-ip" id="toc-step-1-allocate-elastic-ip" class="nav-link" data-scroll-target="#step-1-allocate-elastic-ip"><span class="header-section-number">13.4.1</span> Step 1: Allocate Elastic IP</a></li>
+  <li><a href="#step-1-allocate-an-elastic-ip" id="toc-step-1-allocate-an-elastic-ip" class="nav-link" data-scroll-target="#step-1-allocate-an-elastic-ip"><span class="header-section-number">13.4.1</span> Step 1: Allocate an Elastic IP</a></li>
   <li><a href="#step-2-buy-a-domain" id="toc-step-2-buy-a-domain" class="nav-link" data-scroll-target="#step-2-buy-a-domain"><span class="header-section-number">13.4.2</span> Step 2: Buy a domain</a></li>
   <li><a href="#step-3-configure-dns" id="toc-step-3-configure-dns" class="nav-link" data-scroll-target="#step-3-configure-dns"><span class="header-section-number">13.4.3</span> Step 3: Configure DNS</a></li>
   <li><a href="#step-4-wait-an-annoyingly-long-time" id="toc-step-4-wait-an-annoyingly-long-time" class="nav-link" data-scroll-target="#step-4-wait-an-annoyingly-long-time"><span class="header-section-number">13.4.4</span> Step 4: Wait an annoyingly long time</a></li>
   <li><a href="#step-5-add-the-shiny-app-to-your-site" id="toc-step-5-add-the-shiny-app-to-your-site" class="nav-link" data-scroll-target="#step-5-add-the-shiny-app-to-your-site"><span class="header-section-number">13.4.5</span> Step 5: Add the Shiny app to your site</a></li>
   </ul></li>
   </ul>
-<div class="toc-actions"><div><i class="bi bi-github"></i></div><div class="action-links"><p><a href="https://github.com/akgold/do4ds/edit/main/chapters/sec3/3-4-dns.qmd" class="toc-action">Edit this page</a></p></div></div></nav>
+<div class="toc-actions"><div><i class="bi bi-github"></i></div><div class="action-links"><p><a href="https://github.com/akgold/do4ds/edit/main/chapters/sec2/2-7-dns.qmd" class="toc-action">Edit this page</a></p></div></div></nav>
     </div>
 <!-- main -->
 <main class="content" id="quarto-document-content">
@@ -400,92 +389,51 @@ <h1 class="title"><span id="sec-dns" class="quarto-section-identifier"><span cla
 
 </header>
 
-<p>In <a href="3-3-networking.html">Chapter&nbsp;<span>12</span></a> you learned all about how IP addresses are where a resource lives on a computer network. But you’ve been using the internet for a long time and you’ve rarely – if ever – actually used an IP address. What gives?</p>
-<p>IP addresses are hard to remember. And worse, they can change when servers are replaced or changed.</p>
-<p>To make the internet a little more human-friendly, the creators of the internet built the <em>domain name system</em> (DNS) that translates between human-readable <em>domains</em> and the IP addresses where the resources actually live.</p>
-<p>When you create or launch a website, you’ll purchase <em>domain</em> like <span class="math inline">\(do4ds.com\)</span>. Purchasing a domain (renting one, really) gives you the right to attach that domain to an IP address so people can access the resources you choose at that address.</p>
-<p><a href="3-3-networking.html">Chapter&nbsp;<span>12</span></a> introduced full URLs. Where the main address goes, I handwaved a little because I was switching back and forth between IP addresses and domains. In this chapter, we’re going to get really specific about how that substitution works, so we’re going to focus on the address part of it. In particular, we’re going to learn about Fully-Qualified Domain Names (FQDN).</p>
-<p>A site’s FQDN looks like this:</p>
+<p>In <a href="2-6-networking.html">Chapter&nbsp;<span>12</span></a> you learned all about how IP Addresses are where a host actually lives on a computer network. But you’ve been using the internet for a long time and you’ve rarely – if ever – actually used an IP Address. What gives?</p>
+<p>IP Addresses are hard to remember. And worse, they can change when servers are replaced.</p>
+<p>To make the internet a little more human-friendly, the creators of the internet built the <em>domain name system</em> (DNS) that translates between human-readable <em>domains</em> and the IP Addresses where the resources actually live.</p>
+<p>In this chapter, you’ll learn the basics about how DNS works and how it gets configured.<a href="#fn1" class="footnote-ref" id="fnref1" role="doc-noteref"><sup>1</sup></a> In the lab, you’ll configure your workbench with an actual domain.</p>
+<section id="basics-of-dns-and-domains" class="level2" data-number="13.1">
+<h2 data-number="13.1" class="anchored" data-anchor-id="basics-of-dns-and-domains"><span class="header-section-number">13.1</span> Basics of DNS and domains</h2>
+<p>When you create or launch a website, you’ll purchase (rent, really) a domain like <span class="math inline">\(\text{do4ds.com}\)</span> from a <em>domain name registrar</em>. Purchasing a domain gives you the right to attach that domain to an IP Address.</p>
+<p>When someone comes to visit your website, their computer <em>resolves</em> the IP Address via a <em>DNS lookup</em> against public DNS nameservers. So when you purchase a domain, you register the association between your domain and the IP Address with the DNS nameservers so users can look them up.</p>
+<p>A complete domain is called a <em>Fully-Qualified Domain Name (FQDN)</em> and consists of three parts:</p>
 <p><span class="math display">\[
-\overbrace{https}^{\text{protocol}}://\overbrace{blog}^{\text{Subdomain}}.\underbrace{\overbrace{example}^{\text{Domain Name}}.\overbrace{com}^{\text{Top-Level Domain}}}_{\text{Root Domain}}
+\overbrace{\text{blog}}^{\text{Subdomain}}.\overbrace{\underbrace{\text{example}}_{\text{Domain Name}}.\underbrace{\text{com}}_{\text{Top-Level Domain}}}^{\text{Root Domain}}
 \]</span></p>
-<p>The <em>root domain</em> is the thing you actually purchase. It has two parts. The top-level domain specifies the root domain name server to use.</p>
-<p>Each <em>domain name</em> is unique <em>only within the top-level domain</em>, so if you own the root domain <span class="math inline">\(example.com\)</span>, there’s nothing stopping someone else from getting <span class="math inline">\(example.org\)</span> or <span class="math inline">\(example.ai\)</span>.</p>
+<p>When you get a domain from a registrar, the thing you’ll actually rent is the root domain. You can choose any root domain you want, as long as it’s not already taken. Domain names are unique only within top-level domains, so you might be able to get <span class="math inline">\(\text{example.fun}\)</span> even if someone else owns <span class="math inline">\(\text{example.com}\)</span>.</p>
 <div class="callout callout-style-default callout-note callout-titled">
 <div class="callout-header d-flex align-content-center">
 <div class="callout-icon-container">
 <i class="callout-icon"></i>
 </div>
 <div class="callout-title-container flex-fill">
-So many top-level domains
+Top-level domains
 </div>
 </div>
 <div class="callout-body-container callout-body">
-<p>If you feel like the number of top-level domains has exploded in the last few years, you’re right.</p>
-<p>When the web first launched, there were only a limited number of top-level domains like <code>.com</code>, <code>.org</code>, and <code>.net</code> and ICANN – the group that controls how domains are assigned – controlled them all.</p>
-<p>In 2013, ICANN decided to allow people and organizations to register <em>their own</em> top-level domains. That’s why there’s been an explosion in websites at top level domains like <code>.io</code>, <code>.ai</code>, and <code>.fun</code> in the last decade or so.</p>
+<p>When the web first launched, there were only a limited number of top-level domains like <span class="math inline">\(\text{.com}\)</span>, <span class="math inline">\(\text{.org}\)</span>, and <span class="math inline">\(\text{.net}\)</span>. ICANN, the group that controls how domains are assigned, controlled them all.</p>
+<p>In 2013, ICANN decided to allow people and organizations to register their own top-level domains. That’s why there’s been an explosion in websites at top level domains like <span class="math inline">\(\text{.io}\)</span>, <span class="math inline">\(\text{.ai}\)</span>, and <span class="math inline">\(\text{.fun}\)</span> in the last decade or so.</p>
 <p>I think it’d be fun to have my own top-level domain, so it’s unfortunate that owning a top-level domain is not something to do on a whim. In 2012, the initial application fee was $185,000.</p>
 </div>
 </div>
-<p>The <em>protocol</em> is the application layer protocol, which we discussed in some depth in <a href="3-3-networking.html">Chapter&nbsp;<span>12</span></a>. For most web traffic, the protocol is <code>http</code>. We’ll discuss where the <code>s</code> comes from in <a href="3-5-ssl.html">Chapter&nbsp;<span>14</span></a> on SSL.</p>
-<p><em>Subdomains</em> are a way to specify a <em>part</em> of a domain, usually to signify to users that its for a distinct purpose. If you control a domain, you also have ownership over all the subdomains in that domain.</p>
-<p>Subdomains are entirely about organizing how users experience your website. They don’t need to have any relationship to the technical implementation of your website. For example, you might want to have a blog for your engineering team at <span class="math inline">\(example.com\)</span>. Whether you choose to host it at <span class="math inline">\(example.com/engineering/blog\)</span> or at <span class="math inline">\(blog.engineering.example.com\)</span> is purely a choice of user experience and organizational preference.</p>
-<p>Poking around different Google services illustrates the arbitrary-ness of using subdomains vs paths. Some Google services are at subdomains. Gmail is at <span class="math inline">\(mail.google.com\)</span> and Google Drive is at <span class="math inline">\(drive.google.com\)</span>. Each of these is a distinct site I might visit for different purposes, but they’re all owned and maintained by Google – though probably by different teams.</p>
-<p>On the other hand, Google Maps is accessible at <span class="math inline">\(maps.google.com\)</span>, but it just redirects to <span class="math inline">\(google.com/maps\)</span>. Google slides is also accessible at <span class="math inline">\(slides.google.com\)</span> and redirects to a path on a subdomain: <span class="math inline">\(docs.google.com/presentation\)</span>. This most likely reflects internal organizational divisions at Google.</p>
-<div class="callout callout-style-default callout-note callout-titled">
-<div class="callout-header d-flex align-content-center">
-<div class="callout-icon-container">
-<i class="callout-icon"></i>
-</div>
-<div class="callout-title-container flex-fill">
-<code>www</code> is just a subdomain
-</div>
-</div>
-<div class="callout-body-container callout-body">
-<p>Sometimes the domains of websites are prefixed with <code>www</code> and sometimes not. What gives?</p>
-<p><code>www</code> is just a subdomain. It’s short for <em>world wide web</em>.</p>
-<p>When the internet was first started, it seemed like it might be important to differentiate the subdomain where the website would live from, for example, the email domain people at that organization would use.</p>
-<p>That turned out not really to be the case.</p>
-<p>These days, it is convention to make the <code>www</code> subdomain and the bare domain go to the same place.</p>
-</div>
-</div>
-<section id="how-dns-lookups-work" class="level2" data-number="13.1">
-<h2 data-number="13.1" class="anchored" data-anchor-id="how-dns-lookups-work"><span class="header-section-number">13.1</span> How DNS lookups work</h2>
-<p>In <a href="3-3-networking.html">Chapter&nbsp;<span>12</span></a>, we discussed how packets gets routed to successively higher-level routers until there’s one that knows where the packet is going and sends it back down. It turns out that this process essentially happens <em>twice.</em> The first time is to get the IP address for the domain in a process called <em>DNS resolution.</em> The second time is when it actually sends the information to that IP address.</p>
-<p>You can see the basic structure of a DNS lookup using the terminal command <code>nslookup</code>. Here’s the DNS routing for <span class="math inline">\(google.com\)</span>:</p>
-<pre><code> ❯ nslookup google.com                                              
-Server:     192.168.86.1
-Address:    192.168.86.1#53
-
-Non-authoritative answer:
-Name:   google.com
-Address: 142.251.163.113
-Name:   google.com
-Address: 142.251.163.100
-Name:   google.com
-Address: 142.251.163.138
-Name:   google.com
-Address: 142.251.163.101
-Name:   google.com
-Address: 142.251.163.102
-Name:   google.com
-Address: 142.251.163.139</code></pre>
-<p>These addresses do change periodically, so they may no longer be valid by the time you read this. But if you want to go do an <code>nslookup</code> yourself, you can visit one of those IP addresses and see that it takes you right to the familiar <span class="math inline">\(google.com\)</span>.<a href="#fn1" class="footnote-ref" id="fnref1" role="doc-noteref"><sup>1</sup></a></p>
-<p>DNS resolution is actually quite a complex process because every computer in the world needs to be able to resolve a DNS entry to the same IP address in a timely fashion. The simplest form of DNS lookup would be easy – there would just be one nameserver with the top-level domains and then one server for each top-level domain.</p>
-<p>There are two problems with this theoretical DNS lookup – it wouldn’t be very resilient because of a lack of redundancy and it would be <em>slow</em>. In order to speed things up, the DNS system is highly decentralized.</p>
-<p>Along with decentralization, DNS resolution relies on a lot of cacheing. When your computer or an intermediate DNS server looks up an IP address for you, it caches it. This is because its likely that if you’ve looked up a domain once, you’re going to do it again soon.</p>
-<p>This is great if you are <em>using</em> the internet and don’t want to wait for DNS lookups, but when you’re changing the domains on servers you control, there are thousands of public DNS servers that a request could get routed to, and many of them may have outdated cache entries. DNS changes can take up to 24 hours to propagate.</p>
-<p>That means that if you make a change and it’s not working, you have no idea whether you made a mistake or it just hasn’t propagated yet. It’s very annoying.</p>
-<p>Sometimes, using a private browsing window will cause DNS cache refreshes, but not always.</p>
+<p>Subdomains are a way to specify a part of a domain, usually to signify to users that its for a distinct purpose. You can generally register as many subdomains as you want against a root domain.</p>
 </section>
 <section id="how-dns-is-configured" class="level2" data-number="13.2">
 <h2 data-number="13.2" class="anchored" data-anchor-id="how-dns-is-configured"><span class="header-section-number">13.2</span> How DNS is configured</h2>
-<p>From the perspective of someone trying to set up their own website, there’s only one DNS server that matters to you personally – the DNS server for your <em>domain name registrar</em>.</p>
-<p>Domain name registrars are the companies that actually own domains. You can buy or rent one from them in order to have a domain on the internet.</p>
-<p>Your first stop would be a domain name registrar where you’d find an available domain you like and pull out your credit card.</p>
-<p>Costs for domain names vary widely. Buying a meaningless domain in a less popular top-level domain, say <code>ladskfmlsdf.me</code> can cost as little as $3 per year. On the other hand, buying a <code>.com</code> domain that’s a real word or phrase can be a few thousand dollars. There are articles every few years about some major company accidentally allowing their domain name to lapse and ransoming it back for stupid amounts of money.</p>
-<p>Configuration of DNS is done by way of <em>records</em>, of which there are a menagerie of types you <em>can</em> configure. Luckily, most simple configurations only need <em>CNAME</em> and <em>A</em> records.</p>
-<p>Here’s an imaginary DNS record table for the domain <code>example.com</code>:</p>
+<p>DNS is configured by giving the proper IP Address information to the domain name registrar where you bought your domain. There’s often some minor configuration on the server side as well to let the server know where it lives.</p>
+<p>Most places you might serve a website from have instructions on how to do configure it you can google. The point of this section is just to make you comfortable with whatever instructions you find in your googling.</p>
+<p>There are a variety of different domain name registrars. Each of the big 3 has their own and there are a number of others including Namecheap (my personal favorite as it is indeed, cheap), Cloudflare, and GoDaddy.</p>
+<p>Costs for domain names vary widely. Buying a meaningless domain in a less popular top-level domain can cost as little as a few dollars per year. For example, I was able to get the domain <span class="math inline">\(\text{do4ds-lab.shop}\)</span> for $1.98 for a year on Namecheap.</p>
+<p>On the other hand, buying a <span class="math inline">\(\text{.com}\)</span> domain that’s a real word or phrase can be thousands of dollars. There are articles every few years about some major company accidentally allowing their domain name to lapse and ransoming it back for stupid amounts of money.</p>
+<p>Once you’ve purchased your domain, you need to configure the public DNS records of your domain to point to the IP Address you want. Configuration of DNS is done by way of <em>records</em>. Records map a <em>path</em> or <em>host</em> to a <em>target</em>.</p>
+<p>Depending on the type of mapping, records fall into a number of different categories, but there are only a few you’re likely to see:</p>
+<ul>
+<li><em>A records</em> (or their IPv6 cousin <em>AAAA records</em>) map a domain to an actual IP Address.</li>
+<li><em>CNAME records</em> alias subdomains to another record.</li>
+<li><em>NS records</em> tells the DNS server to forward the request on to another namespace server. This is usually only used by big organizations that run their own domain name servers for their subdomains.</li>
+</ul>
+<p>When you go to configure DNS with your domain name registrar, you’ll configure the records in a record table. Here’s an imaginary DNS record table for the domain <span class="math inline">\(\text{example.com}\)</span>:</p>
 <table class="table">
 <thead>
 <tr class="header">
@@ -496,44 +444,86 @@ <h2 data-number="13.2" class="anchored" data-anchor-id="how-dns-is-configured"><
 </thead>
 <tbody>
 <tr class="odd">
-<td><code>@</code></td>
-<td>A</td>
-<td><code>143.122.8.32</code></td>
+<td><span class="math inline">\(\text{@}\)</span></td>
+<td><code>A</code></td>
+<td><span class="math inline">\(\text{64.56.223.5}\)</span></td>
 </tr>
 <tr class="even">
-<td><code>www</code></td>
-<td>CNAME</td>
-<td>example.com</td>
+<td><span class="math inline">\(\text{www}\)</span></td>
+<td><code>CNAME</code></td>
+<td><span class="math inline">\(\text{example.com}\)</span></td>
 </tr>
 <tr class="odd">
-<td><code>*</code></td>
-<td>A</td>
-<td><code>143.122.8.33</code></td>
+<td><span class="math inline">\(\text{blog}\)</span></td>
+<td><code>A</code></td>
+<td><span class="math inline">\(\text{114.13.56.77}\)</span></td>
+</tr>
+<tr class="even">
+<td><span class="math inline">\(\text{*}\)</span></td>
+<td><code>A</code></td>
+<td><span class="math inline">\(\text{64.56.223.5}\)</span></td>
 </tr>
 </tbody>
 </table>
-<p>Let’s go through how to read this table.</p>
-<p>Since we’re configuring <code>example.com</code>, the paths/hosts in this table are relative to <code>example.com</code>.</p>
-<p>In the first row we’re configuring an A record to go to the target IP address. <em>A records</em> (or their IPv6 cousin <em>AAAA records</em>) map a domain to an actual IP address. The path <code>@</code> is a special symbol meaning exact match. So by this configuration, any traffic to <code>example.com</code> will be passed straight through to the specified IP address.</p>
-<p>The second row deals with traffic to the <code>www</code> subdomain. <em>CNAME records</em> alias sub-domains. They’re most frequently used to map sub-domains to the main domain. Since this is a <code>CNAME</code> record for example.com, this record indicates that traffic to www.example.com should be treated exactly like traffic to <code>example.com</code>. Some domain providers do automatic redirection of <code>www</code> traffic, and so this row may not be necessary in some configurations.</p>
-<p>The last record uses the wildcard symbol <code>*</code> to send all subdomain traffic that’s not already spoken for – say <code>blog.example.com</code> or <code>info.example.com</code> directly to the IP address specified. In this case, I’m sending all of those subdomains to a different IP address, maybe a 404 (not found) page – or maybe I’m serving all the subdomains off a different server.</p>
-<p>So what happens is that your query goes through several layers of public DNS servers to get to the DNS entry for your domain name registrar. In many cases, you’ll directly configure your domain name registrar to point to your website or server – but you also can configure the domain name registrar to point at another set of DNS servers you actually control with an <em>NS record</em>.</p>
-<p>If you’re setting up your own server, this probably isn’t the case, but some large enterprises do run their own private DNS servers.</p>
+<p>The first row provides an <code>A</code> record for the special <span class="math inline">\(\text{@}\)</span> symbol meaning exact match. So by this configuration, any traffic to <span class="math inline">\(\text{example.com}\)</span> will be passed straight through to the specified IP Address.</p>
+<p>The second row deals with traffic to the <span class="math inline">\(\text{www}\)</span> subdomain. Since this is a <code>CNAME</code> record, this record indicates that traffic to <span class="math inline">\(\text{www.example.com}\)</span> should be treated exactly like traffic to the bare <span class="math inline">\(\text{example.com}\)</span>. Some domain providers do automatic redirection of <span class="math inline">\(\text{www}\)</span> traffic, and so this row may not be necessary in some configurations.</p>
+<p>The next record sends the <span class="math inline">\(\text{blog}\)</span> subdomain to a completely different IP Address. This is a common configuration when the subdomain might be owned by a completely different group than the main website or is served from a different server.</p>
+<p>The last record uses the wildcard symbol <span class="math inline">\(\text{*}\)</span> to send all subdomain traffic that’s not already spoken for back to the main IP Address.</p>
+<p>Other than the <span class="math inline">\(\text{www}\)</span> subdomain, which stands for world wide web, and is generally routed to the same place as the bare root domain, using subdomains and choosing between subdomains and paths is entirely about organizing how users experience your website and what’s easiest for your organization to maintain.</p>
+<div class="callout callout-style-default callout-note callout-titled">
+<div class="callout-header d-flex align-content-center">
+<div class="callout-icon-container">
+<i class="callout-icon"></i>
+</div>
+<div class="callout-title-container flex-fill">
+<span class="math inline">\(\text{www}\)</span> is just a subdomain
+</div>
+</div>
+<div class="callout-body-container callout-body">
+<p>When the internet was first started, it seemed like it might be important to differentiate the subdomain where the website would live from, for example, the email domain people at that organization would use.</p>
+<p>That turned out not really to be the case and these days <span class="math inline">\(\text{www}\)</span> and the bare root domain are generally used interchangeably.</p>
+</div>
+</div>
+<p>Once you’ve configured your DNS records, you will need to wait an annoyingly long time to see if you did it correctly.</p>
+<p>When your computer does a DNS lookup, there are often at least three nameservers involved. First, your computer talks to a <em>resolver</em>, which is a server that keeps track of where the nameservers are. Then you’re routed to the correct nameserver for the top-level domain, which routes you to the nameserver for your actual domain.</p>
+<p>And then there are various geographic repeats of this whole set of servers to make sure your query doesn’t get slowed down by having to travel too far.</p>
+<p>That means that when you update a DNS record, it can take some time to propagate to all these servers. The other issue is that your computer, and each of these servers, tries to do as few lookups as possible, because they’re slow.</p>
+<p>When you configure a DNS record, you configure something called the <em>TTL (time to live)</em>. Each level of DNS lookup, may cache the results of looking up a domain to avoid having to ask the next level. How long that cache lasts is configured by the TTL.</p>
+<p>This is great if you are <em>using</em> the internet and don’t want to wait for DNS lookups, but when you’re changing the domains on servers you control, there are many DNS servers that a request could get routed to, and many of them may have outdated cache entries. That’s why DNS changes can take up to 24 hours to propagate.</p>
+<p>That means that if you make a change and it’s not working, you have no idea whether you made a mistake or it just hasn’t propagated yet. It’s very annoying.</p>
 </section>
 <section id="comprehension-questions" class="level2" data-number="13.3">
 <h2 data-number="13.3" class="anchored" data-anchor-id="comprehension-questions"><span class="header-section-number">13.3</span> Comprehension Questions</h2>
-<p>TODO</p>
+<ol type="1">
+<li>What are the parts of a fully-qualified domain name? How does each of them get created?</li>
+<li>How does your computer find the IP Address for a domain? Why could it sometimes be wrong?</li>
+<li>What are the different kinds of DNS records you’re likely to use?</li>
+</ol>
 </section>
 <section id="lab-configuring-dns-for-your-server" class="level2" data-number="13.4">
 <h2 data-number="13.4" class="anchored" data-anchor-id="lab-configuring-dns-for-your-server"><span class="header-section-number">13.4</span> Lab: Configuring DNS for your server</h2>
 <p>In the last lab, we configured the server so that all of the services were served off of one single port that redirected to various subpaths.</p>
-<p>Now we want to get a real URL for the server so that you don’t have to remember some random <code>ec2-</code> URL for your server. In this lab, we’ll configure DNS records for our server so it’s available at a real URL.</p>
-<section id="step-1-allocate-elastic-ip" class="level3" data-number="13.4.1">
-<h3 data-number="13.4.1" class="anchored" data-anchor-id="step-1-allocate-elastic-ip"><span class="header-section-number">13.4.1</span> Step 1: Allocate Elastic IP</h3>
-<p>EC2 instances get assigned a public IP when they are started. That’s great – it makes it easy to do the kind of work we’ve done. But if you’ve stopped or restarted your server, you’ve you’ve probably noticed that the public IP address changed!</p>
-<p>This is no good for configuring a long-lived DNS record that consistently routes to your server. So we’re going to use AWS’s <em>Elastic IP</em> service, which gives you a stable public IP address you can keep and move around from one instance to another as you wish.</p>
-<p>Elastic IP payment is a little weird. You don’t get charged for Elastic IPs <em>as long as you’re using them</em>. So if your server is up and using an elastic IP, it’s all free. If you take your server down and want to reserve the Elastic IP so it’s the same when you bring it back up, you’ll pay. It’s very cheap for one IP (12 cents per day as of this writing), so don’t worry about it.</p>
-<p>Basically AWS doesn’t want you hoarding Elastic IPs. Great – just make sure to give back the elastic IP if you take down your instance permanently.</p>
+<p>Now we want to get a real, memorable domain for the server so that you and your users don’t have to remember some random <code>ec2-</code> domain or an IP Address. In this lab, we’ll configure DNS records for our server so it’s available at a real domain.</p>
+<section id="step-1-allocate-an-elastic-ip" class="level3" data-number="13.4.1">
+<h3 data-number="13.4.1" class="anchored" data-anchor-id="step-1-allocate-an-elastic-ip"><span class="header-section-number">13.4.1</span> Step 1: Allocate an Elastic IP</h3>
+<p>EC2 instances get assigned a public IP when they are started. The issue is that every time the server stops that IP is released and a new one is assigned when it comes back up. This means you’d have to change your DNS record every time you temporarily take your server offline – no good.</p>
+<p>Luckily, AWS has a great solution here called <em>Elastic IP</em>. which gives you a stable public IP Address you can move from one instance to another as you wish.</p>
+<div class="callout callout-style-default callout-tip callout-titled">
+<div class="callout-header d-flex align-content-center">
+<div class="callout-icon-container">
+<i class="callout-icon"></i>
+</div>
+<div class="callout-title-container flex-fill">
+Paying for Elastic IPs
+</div>
+</div>
+<div class="callout-body-container callout-body">
+<p>Elastic IPs are free as long as they’re attached to a running EC2 instance. You pay when they’re not in use to discourage hoarding them.</p>
+<p>If you do take your server down for a short time, it’s no big deal. As of this writing, it’s 12 cents per day for a single IP. But do make sure to release the Elastic IP if/when you take your server down permanently.</p>
+</div>
+</div>
+<p>To set up your Elastic IP, find it in the AWS console and allocate an address. Then you will associate your Elastic IP as the default public IP Address for your instance.</p>
+<p>Note that once you make this change, your server will no longer be available at its old IP Address, so you’ll have to SSH in at the new one. If you have SSH terminals open when you make the change, they will break.</p>
 <div class="callout callout-style-default callout-note callout-titled">
 <div class="callout-header d-flex align-content-center">
 <div class="callout-icon-container">
@@ -544,35 +534,73 @@ <h3 data-number="13.4.1" class="anchored" data-anchor-id="step-1-allocate-elasti
 </div>
 </div>
 <div class="callout-body-container callout-body">
-<p>The labs in this book are ordered to promote learning.</p>
-<p>If you configure a server later for real, I’d recommend setting up an Elastic IP as soon as you bring the server up so you have a permanent IP address right off the bat.</p>
+<p>Next time you stand up a server, you should start by giving it an Elastic IP so you are immediately using it’s permanent IP Address. The labs in this book are ordered to promote learning, not the right order to configure things.</p>
 </div>
 </div>
-<p>To actually do it, find Elastic IP in the AWS console and allocate an address. Once it has been allocated, click through to the elastic IP and associate it with the default private IP address for your instance.</p>
-<p>Note that once you make this change, your server will no longer be available at its old IP address, so you’ll have to SSH in at the new one. If you have SSH terminals open when you make the change, they will break.</p>
 </section>
 <section id="step-2-buy-a-domain" class="level3" data-number="13.4.2">
 <h3 data-number="13.4.2" class="anchored" data-anchor-id="step-2-buy-a-domain"><span class="header-section-number">13.4.2</span> Step 2: Buy a domain</h3>
-<p>You can buy a domain from any of the many domain purchasing services on the web. Now, it won’t be free, but many domains are very cheap.</p>
-<p>The easiest place to buy a domain is via AWS’s <em>Route53</em> service. You can get domains on <em>Route53</em> for as little as $9 per year – but there are even cheaper services. For example, I was able to get the domain <span class="math inline">\(do4ds-lab.shop\)</span> for $1.98 for a year on <code>namecheap.com</code>, which has long been my choice for purchasing domains because it is indeed, cheap.</p>
+<p>You can buy a domain from any of the many domain purchasing services on the web. This won’t be free, but many domains are very cheap.</p>
+<p>The easiest place to buy a domain is via AWS’s <em>Route53</em> service, but you can feel free to use another provider. I usually use Namecheap just because all of the domains I own are there.</p>
 </section>
 <section id="step-3-configure-dns" class="level3" data-number="13.4.3">
 <h3 data-number="13.4.3" class="anchored" data-anchor-id="step-3-configure-dns"><span class="header-section-number">13.4.3</span> Step 3: Configure DNS</h3>
-<p>Once you’ve got your domain, you have to configure your DNS. You’ll have to create 2 A records – one each for the @ host and the * host pointing to your IP and one for the CNAME at the <code>www</code> with the value being your bare domain.</p>
-<p>Exactly how you configure this will depend on the domain name provider you choose.</p>
-<p>In NameCheap, my Advanced DNS configuration looks like this:</p>
-<p><img src="images-traffic/namecheap-config.png" class="img-fluid"></p>
+<p>Once you’ve got your domain, you have to configure your DNS. You’ll have to create 2 A records – one each for the <span class="math inline">\(\text{@}\)</span> host and the <span class="math inline">\(\text{*}\)</span> host pointing to your IP and one for the CNAME at the <span class="math inline">\(\text{www}\)</span> with the value being your bare domain.</p>
+<p>Exactly how you configure this will depend on the domain name provider you choose. In NameCheap, you configure this via a table under Advanced DNS, which looks like this.</p>
+<table class="table">
+<thead>
+<tr class="header">
+<th>Type</th>
+<th>Host</th>
+<th>Value</th>
+<th>TTL</th>
+</tr>
+</thead>
+<tbody>
+<tr class="odd">
+<td><code>A</code> Record</td>
+<td><span class="math inline">\(\text{*}\)</span></td>
+<td><span class="math inline">\(\text{64.56.223.5}\)</span></td>
+<td>Automatic</td>
+</tr>
+<tr class="even">
+<td><code>CNAME</code> Record</td>
+<td><span class="math inline">\(\text{www}\)</span></td>
+<td><span class="math inline">\(\text{do4ds-lab.shop}\)</span></td>
+<td>Automatic</td>
+</tr>
+<tr class="odd">
+<td><code>A</code> Record</td>
+<td><span class="math inline">\(\text{@}\)</span></td>
+<td><span class="math inline">\(\text{64.56.223.5}\)</span></td>
+<td>Automatic</td>
+</tr>
+</tbody>
+</table>
+<p>I would recommend sticking with the default for TTL.</p>
 </section>
 <section id="step-4-wait-an-annoyingly-long-time" class="level3" data-number="13.4.4">
 <h3 data-number="13.4.4" class="anchored" data-anchor-id="step-4-wait-an-annoyingly-long-time"><span class="header-section-number">13.4.4</span> Step 4: Wait an annoyingly long time</h3>
 <p>Now you just have to be patient. Unfortunately DNS takes time to propagate. After a few minutes (or hours?), your server should be reachable at your domain.</p>
-<p>If it’s not (yet) reachable, try seeing if an incognito browser works. If it doesn’t, wait some more. When you run out of patience, try reconfiguring everything and check if it works now.</p>
-<p>Note that we still haven’t configured SSL, so you’ll need to make sure to correct your browser away from the <code>https</code> URL.</p>
+<p>If it’s not (yet) reachable, try seeing if an incognito browser works because that sidesteps the browser level of caching. If it doesn’t, wait some more. When you run out of patience, try reconfiguring everything and check if it works now.</p>
+<div class="callout callout-style-default callout-tip callout-titled">
+<div class="callout-header d-flex align-content-center">
+<div class="callout-icon-container">
+<i class="callout-icon"></i>
+</div>
+<div class="callout-title-container flex-fill">
+Tip
+</div>
+</div>
+<div class="callout-body-container callout-body">
+<p>We still haven’t configured HTTPS, so you’ll need to manually input the URL as <span class="math inline">\(\text{http://}\)</span>, because your browser will otherwise assume it’s HTTPS.</p>
+</div>
+</div>
 </section>
 <section id="step-5-add-the-shiny-app-to-your-site" class="level3" data-number="13.4.5">
 <h3 data-number="13.4.5" class="anchored" data-anchor-id="step-5-add-the-shiny-app-to-your-site"><span class="header-section-number">13.4.5</span> Step 5: Add the Shiny app to your site</h3>
-<p>Now that the Shiny app is at a stable URL, let’s put it on our site so people can look at our penguin size prediction model.</p>
-<p>We’re going to use something called an <em>iFrame</em>, which lets you embed one website inside another. Luckily, it’s really easy to create an iFrame in a Quarto site.</p>
+<p>Now that the Shiny app is at a stable URL, let’s put it on our site so people can look at our penguin size prediction model. I put the app at the subpath <span class="math inline">\(\text{/penguins}\)</span>, so it’s now at <span class="math inline">\(\text{http://do4ds-lab.shop/penguins}\)</span>.</p>
+<p>We’re going to use something called an <em>iFrame</em>, which lets you embed one website inside another. An iFrame is a basic HTML construct and it’s easy to put one in a Quarto site.</p>
 <div class="callout callout-style-default callout-note callout-titled">
 <div class="callout-header d-flex align-content-center">
 <div class="callout-icon-container">
@@ -586,12 +614,12 @@ <h3 data-number="13.4.5" class="anchored" data-anchor-id="step-5-add-the-shiny-a
 <p>Once you change your website to go over HTTPS in the next section, you’ll have to adjust the iFrame URL as well.</p>
 </div>
 </div>
-<p>In Quarto, you can just add an <code>html</code> block into your <code>index.qmd</code>. In my case, that block just says</p>
+<p>In Quarto, you can just add an <code>html</code> block to a any document and it will get loaded in automatically. I want the app on the landing page of my site, <code>index.qmd</code>. So I’ve added a block that looks like:</p>
 <div class="code-with-filename">
 <div class="code-with-filename-file">
 <pre><strong>index.qmd</strong></pre>
 </div>
-<div class="sourceCode" id="cb2"><pre class="sourceCode numberSource html number-lines code-with-copy"><code class="sourceCode html"><span id="cb2-1"><a href="#cb2-1"></a><span class="kw">&lt;iframe</span> <span class="er">width</span><span class="ot">=</span><span class="st">"780"</span> <span class="er">height</span><span class="ot">=</span><span class="st">"500"</span> <span class="er">src</span><span class="ot">=</span><span class="st">"https://do4ds-lab.shop/penguins/"</span> <span class="er">title</span><span class="ot">=</span><span class="st">"Penguin Model Explorer"</span><span class="kw">&gt;&lt;/iframe&gt;</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+<div class="sourceCode" id="cb1"><pre class="sourceCode numberSource html number-lines code-with-copy"><code class="sourceCode html"><span id="cb1-1"><a href="#cb1-1"></a><span class="kw">&lt;iframe</span> <span class="er">width</span><span class="ot">=</span><span class="st">"780"</span> <span class="er">height</span><span class="ot">=</span><span class="st">"500"</span> <span class="er">src</span><span class="ot">=</span><span class="st">"http://do4ds-lab.shop/penguins/"</span> <span class="er">title</span><span class="ot">=</span><span class="st">"Penguin Model Explorer"</span><span class="kw">&gt;&lt;/iframe&gt;</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </div>
 
 
@@ -600,7 +628,7 @@ <h3 data-number="13.4.5" class="anchored" data-anchor-id="step-5-add-the-shiny-a
 <section id="footnotes" class="footnotes footnotes-end-of-document" role="doc-endnotes">
 <hr>
 <ol>
-<li id="fn1"><p>If you try to do an <code>nslookup</code> on some websites – like <span class="math inline">\(do4ds.com\)</span>, you’ll notice the IP address doesn’t actually take you to this book’s site. That’s because this book isn’t actually hosted directly on a server. It’s instead hosted on GitHub pages – so the IP addresses <code>nslookup</code> finds are the Google Pages servers, which themselves know how to resolve <span class="math inline">\(do4ds.com\)</span>.<a href="#fnref1" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
+<li id="fn1"><p>This is really a very shallow intro to DNS. If you want to go a little deeper, I highly recommend Julia Evans’s zines on a variety of technical topics, including DNS. You can find them at wizardzines.com.<a href="#fnref1" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
 </ol>
 </section>
 
@@ -840,12 +868,12 @@ <h3 data-number="13.4.5" class="anchored" data-anchor-id="step-5-add-the-shiny-a
 </script>
 <nav class="page-navigation">
   <div class="nav-page nav-page-previous">
-      <a href="../../chapters/sec3/3-3-networking.html" class="pagination-link">
+      <a href="../../chapters/sec2/2-6-networking.html" class="pagination-link">
         <i class="bi bi-arrow-left-short"></i> <span class="nav-page-text"><span class="chapter-number">12</span>&nbsp; <span class="chapter-title">Intro to Computer Networks</span></span>
       </a>          
   </div>
   <div class="nav-page nav-page-next">
-      <a href="../../chapters/sec3/3-5-ssl.html" class="pagination-link">
+      <a href="../../chapters/sec2/2-8-ssl.html" class="pagination-link">
         <span class="nav-page-text"><span class="chapter-number">14</span>&nbsp; <span class="chapter-title">You should use SSL/HTTPS</span></span> <i class="bi bi-arrow-right-short"></i>
       </a>
   </div>
diff --git a/chapters/sec3/3-5-ssl.html b/chapters/sec2/2-8-ssl.html
similarity index 58%
rename from chapters/sec3/3-5-ssl.html
rename to chapters/sec2/2-8-ssl.html
index 8d85e0b6a..a9d324fc8 100644
--- a/chapters/sec3/3-5-ssl.html
+++ b/chapters/sec2/2-8-ssl.html
@@ -64,8 +64,8 @@
 <script src="../../site_libs/quarto-search/fuse.min.js"></script>
 <script src="../../site_libs/quarto-search/quarto-search.js"></script>
 <meta name="quarto:offset" content="../../">
-<link href="../../chapters/sec3/3-6-servers.html" rel="next">
-<link href="../../chapters/sec3/3-4-dns.html" rel="prev">
+<link href="../../chapters/sec3/3-0-sec-intro.html" rel="next">
+<link href="../../chapters/sec2/2-7-dns.html" rel="prev">
 <script src="../../site_libs/quarto-html/quarto.js"></script>
 <script src="../../site_libs/quarto-html/popper.min.js"></script>
 <script src="../../site_libs/quarto-html/tippy.umd.min.js"></script>
@@ -103,9 +103,6 @@
 gtag('js', new Date());
 gtag('config', 'G-EQR1RYSHQK', { 'anonymize_ip': true});
 </script>
-<script src="../../site_libs/quarto-diagram/mermaid.min.js"></script>
-<script src="../../site_libs/quarto-diagram/mermaid-init.js"></script>
-<link href="../../site_libs/quarto-diagram/mermaid.css" rel="stylesheet">
 
   <script src="https://polyfill.io/v3/polyfill.min.js?features=es6"></script>
   <script src="https://cdn.jsdelivr.net/npm/mathjax@3/es5/tex-chtml-full.js" type="text/javascript"></script>
@@ -121,7 +118,7 @@
       <button type="button" class="quarto-btn-toggle btn" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar,#quarto-sidebar-glass" aria-controls="quarto-sidebar" aria-expanded="false" aria-label="Toggle sidebar navigation" onclick="if (window.quartoToggleHeadroom) { window.quartoToggleHeadroom(); }">
         <i class="bi bi-layout-text-sidebar-reverse"></i>
       </button>
-      <nav class="quarto-page-breadcrumbs" aria-label="breadcrumb"><ol class="breadcrumb"><li class="breadcrumb-item"><a href="../../chapters/sec3/3-0-sec-intro.html">IT/Admin for Data Science</a></li><li class="breadcrumb-item"><a href="../../chapters/sec3/3-5-ssl.html"><span class="chapter-number">14</span>&nbsp; <span class="chapter-title">You should use SSL/HTTPS</span></a></li></ol></nav>
+      <nav class="quarto-page-breadcrumbs" aria-label="breadcrumb"><ol class="breadcrumb"><li class="breadcrumb-item"><a href="../../chapters/sec2/2-0-sec-intro.html">IT/Admin for Data Science</a></li><li class="breadcrumb-item"><a href="../../chapters/sec2/2-8-ssl.html"><span class="chapter-number">14</span>&nbsp; <span class="chapter-title">You should use SSL/HTTPS</span></a></li></ol></nav>
       <a class="flex-grow-1" role="button" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar,#quarto-sidebar-glass" aria-controls="quarto-sidebar" aria-expanded="false" aria-label="Toggle sidebar navigation" onclick="if (window.quartoToggleHeadroom) { window.quartoToggleHeadroom(); }">      
       </a>
       <button type="button" class="btn quarto-search-button" aria-label="Search" onclick="window.quartoOpenSearch();">
@@ -216,13 +213,19 @@
   <a href="../../chapters/sec1/1-5-deployments.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">5</span>&nbsp; <span class="chapter-title">Deployments and code promotion</span></span></a>
   </div>
+</li>
+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/sec1/1-6-docker.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">6</span>&nbsp; <span class="chapter-title">Demystifying Docker</span></span></a>
+  </div>
 </li>
       </ul>
   </li>
         <li class="sidebar-item sidebar-item-section">
       <div class="sidebar-item-container"> 
             <a href="../../chapters/sec2/2-0-sec-intro.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text">IT/Admin Tools</span></a>
+ <span class="menu-text">IT/Admin for Data Science</span></a>
           <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-2" aria-expanded="true" aria-label="Toggle section">
             <i class="bi bi-chevron-right ms-2"></i>
           </a> 
@@ -230,121 +233,98 @@
       <ul id="quarto-sidebar-section-2" class="collapse list-unstyled sidebar-section depth1 show">  
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec2/2-1-cmd-line.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">6</span>&nbsp; <span class="chapter-title">Opening the Command Line</span></span></a>
+  <a href="../../chapters/sec2/2-1-cloud.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">7</span>&nbsp; <span class="chapter-title">The Cloud</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec2/2-2-cmd-line-use.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">7</span>&nbsp; <span class="chapter-title">Using the Command Line</span></span></a>
+  <a href="../../chapters/sec2/2-2-cmd-line.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">8</span>&nbsp; <span class="chapter-title">Customizing the command line</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec2/2-3-ssh.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">8</span>&nbsp; <span class="chapter-title">Secure server connections with SSH</span></span></a>
+  <a href="../../chapters/sec2/2-3-linux.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">9</span>&nbsp; <span class="chapter-title">Intro to Linux Administration</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec2/2-4-docker.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">9</span>&nbsp; <span class="chapter-title">Demystifying Docker</span></span></a>
-  </div>
-</li>
-      </ul>
-  </li>
-        <li class="sidebar-item sidebar-item-section">
-      <div class="sidebar-item-container"> 
-            <a href="../../chapters/sec3/3-0-sec-intro.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text">IT/Admin for Data Science</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-3" aria-expanded="true" aria-label="Toggle section">
-            <i class="bi bi-chevron-right ms-2"></i>
-          </a> 
-      </div>
-      <ul id="quarto-sidebar-section-3" class="collapse list-unstyled sidebar-section depth1 show">  
-          <li class="sidebar-item">
-  <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-1-cloud.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Getting Started with the Cloud</span></span></a>
+  <a href="../../chapters/sec2/2-4-app-admin.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Application administration</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-2-linux-admin.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Basic Linux SysAdmin</span></span></a>
+  <a href="../../chapters/sec2/2-5-scale.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Server Resources and Scaling</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-3-networking.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-6-networking.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">12</span>&nbsp; <span class="chapter-title">Intro to Computer Networks</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-4-dns.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-7-dns.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">13</span>&nbsp; <span class="chapter-title">DNS allows for human-readable addresses</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-5-ssl.html" class="sidebar-item-text sidebar-link active">
+  <a href="../../chapters/sec2/2-8-ssl.html" class="sidebar-item-text sidebar-link active">
  <span class="menu-text"><span class="chapter-number">14</span>&nbsp; <span class="chapter-title">You should use SSL/HTTPS</span></span></a>
   </div>
-</li>
-          <li class="sidebar-item">
-  <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-6-servers.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Choosing the right server for you</span></span></a>
-  </div>
 </li>
       </ul>
   </li>
         <li class="sidebar-item sidebar-item-section">
       <div class="sidebar-item-container"> 
-            <a href="../../chapters/sec4/4-0-sec-intro.html" class="sidebar-item-text sidebar-link">
+            <a href="../../chapters/sec3/3-0-sec-intro.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text">Making it Enterprise-Grade</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true" aria-label="Toggle section">
+          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-3" aria-expanded="true" aria-label="Toggle section">
             <i class="bi bi-chevron-right ms-2"></i>
           </a> 
       </div>
-      <ul id="quarto-sidebar-section-4" class="collapse list-unstyled sidebar-section depth1 show">  
+      <ul id="quarto-sidebar-section-3" class="collapse list-unstyled sidebar-section depth1 show">  
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec4/4-1-os-ds-in-ent.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></a>
+  <a href="../../chapters/sec3/3-1-os-ds-in-ent.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec4/4-2-ent-networks.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></a>
+  <a href="../../chapters/sec3/3-2-ent-networks.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec4/4-3-auth.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></a>
+  <a href="../../chapters/sec3/3-3-auth.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec4/4-4-ent-servers.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">19</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></a>
+  <a href="../../chapters/sec3/3-4-ent-servers.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></a>
   </div>
 </li>
       </ul>
   </li>
         <li class="sidebar-item sidebar-item-section">
       <div class="sidebar-item-container"> 
-            <a class="sidebar-item-text sidebar-link text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-5" aria-expanded="true">
+            <a class="sidebar-item-text sidebar-link text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true">
  <span class="menu-text">Appendices</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-5" aria-expanded="true" aria-label="Toggle section">
+          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true" aria-label="Toggle section">
             <i class="bi bi-chevron-right ms-2"></i>
           </a> 
       </div>
-      <ul id="quarto-sidebar-section-5" class="collapse list-unstyled sidebar-section depth1 show">  
+      <ul id="quarto-sidebar-section-4" class="collapse list-unstyled sidebar-section depth1 show">  
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
   <a href="../../chapters/append/auth.html" class="sidebar-item-text sidebar-link">
@@ -356,6 +336,12 @@
   <a href="../../chapters/append/lab-map.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">B</span>&nbsp; <span class="chapter-title">Lab Map</span></span></a>
   </div>
+</li>
+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/append/cheatsheets.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">C</span>&nbsp; <span class="chapter-title">Cheatsheets</span></span></a>
+  </div>
 </li>
       </ul>
   </li>
@@ -369,19 +355,19 @@
     <h2 id="toc-title">Table of contents</h2>
    
   <ul>
-  <li><a href="#the-problems-https-solves" id="toc-the-problems-https-solves" class="nav-link active" data-scroll-target="#the-problems-https-solves"><span class="header-section-number">14.1</span> The problems <code>https</code> solves</a></li>
-  <li><a href="#configuring-https" id="toc-configuring-https" class="nav-link" data-scroll-target="#configuring-https"><span class="header-section-number">14.2</span> Configuring <code>https</code></a></li>
-  <li><a href="#comprehension-questions" id="toc-comprehension-questions" class="nav-link" data-scroll-target="#comprehension-questions"><span class="header-section-number">14.3</span> Comprehension Questions</a></li>
-  <li><a href="#lab-configure-ssl" id="toc-lab-configure-ssl" class="nav-link" data-scroll-target="#lab-configure-ssl"><span class="header-section-number">14.4</span> Lab: Configure SSL</a>
+  <li><a href="#what-https-does" id="toc-what-https-does" class="nav-link active" data-scroll-target="#what-https-does"><span class="header-section-number">14.1</span> What HTTPS does</a></li>
+  <li><a href="#how-ssltls-works" id="toc-how-ssltls-works" class="nav-link" data-scroll-target="#how-ssltls-works"><span class="header-section-number">14.2</span> How SSL/TLS works</a></li>
+  <li><a href="#getting-and-using-ssl-certificates" id="toc-getting-and-using-ssl-certificates" class="nav-link" data-scroll-target="#getting-and-using-ssl-certificates"><span class="header-section-number">14.3</span> Getting and using SSL certificates</a></li>
+  <li><a href="#comprehension-questions" id="toc-comprehension-questions" class="nav-link" data-scroll-target="#comprehension-questions"><span class="header-section-number">14.4</span> Comprehension Questions</a></li>
+  <li><a href="#lab-configure-ssl" id="toc-lab-configure-ssl" class="nav-link" data-scroll-target="#lab-configure-ssl"><span class="header-section-number">14.5</span> Lab: Configure SSL</a>
   <ul class="collapse">
-  <li><a href="#step-1-update-nginx-configuration" id="toc-step-1-update-nginx-configuration" class="nav-link" data-scroll-target="#step-1-update-nginx-configuration"><span class="header-section-number">14.4.1</span> Step 1: Update Nginx configuration</a></li>
-  <li><a href="#step-2-certbot-does-its-thing" id="toc-step-2-certbot-does-its-thing" class="nav-link" data-scroll-target="#step-2-certbot-does-its-thing"><span class="header-section-number">14.4.2</span> Step 2: Certbot does its thing</a></li>
-  <li><a href="#step-3-let-rstudio-know-its-on-https" id="toc-step-3-let-rstudio-know-its-on-https" class="nav-link" data-scroll-target="#step-3-let-rstudio-know-its-on-https"><span class="header-section-number">14.4.3</span> Step 3: Let RStudio know it’s on <code>https</code></a></li>
-  <li><a href="#step-4-configure-security-groups" id="toc-step-4-configure-security-groups" class="nav-link" data-scroll-target="#step-4-configure-security-groups"><span class="header-section-number">14.4.4</span> Step 4: Configure security groups</a></li>
-  <li><a href="#step-5-check-it-out" id="toc-step-5-check-it-out" class="nav-link" data-scroll-target="#step-5-check-it-out"><span class="header-section-number">14.4.5</span> Step 5: Check it out!</a></li>
+  <li><a href="#step-1-follow-instructions-to-add-ssl-for-nginx" id="toc-step-1-follow-instructions-to-add-ssl-for-nginx" class="nav-link" data-scroll-target="#step-1-follow-instructions-to-add-ssl-for-nginx"><span class="header-section-number">14.5.1</span> Step 1: Follow instructions to add SSL for NGINX</a></li>
+  <li><a href="#step-2-let-rstudio-server-know-its-on-https" id="toc-step-2-let-rstudio-server-know-its-on-https" class="nav-link" data-scroll-target="#step-2-let-rstudio-server-know-its-on-https"><span class="header-section-number">14.5.2</span> Step 2: Let RStudio Server know it’s on HTTPS</a></li>
+  <li><a href="#step-3-configure-security-groups" id="toc-step-3-configure-security-groups" class="nav-link" data-scroll-target="#step-3-configure-security-groups"><span class="header-section-number">14.5.3</span> Step 3: Configure security groups</a></li>
+  <li><a href="#step-4-we-did-it" id="toc-step-4-we-did-it" class="nav-link" data-scroll-target="#step-4-we-did-it"><span class="header-section-number">14.5.4</span> Step 4: We did it!</a></li>
   </ul></li>
   </ul>
-<div class="toc-actions"><div><i class="bi bi-github"></i></div><div class="action-links"><p><a href="https://github.com/akgold/do4ds/edit/main/chapters/sec3/3-5-ssl.qmd" class="toc-action">Edit this page</a></p></div></div></nav>
+<div class="toc-actions"><div><i class="bi bi-github"></i></div><div class="action-links"><p><a href="https://github.com/akgold/do4ds/edit/main/chapters/sec2/2-8-ssl.qmd" class="toc-action">Edit this page</a></p></div></div></nav>
     </div>
 <!-- main -->
 <main class="content" id="quarto-document-content">
@@ -403,161 +389,115 @@ <h1 class="title"><span id="sec-ssl" class="quarto-section-identifier"><span cla
 
 </header>
 
-<p>Throughout the book to this point, we’ve been talking a lot about the <code>http</code> application layer protocol. But these days you rarely see <code>http</code> when you go to a website. Instead, you see <code>https</code>.</p>
-<p><code>https</code> is the secured version of <code>http</code>. It’s a mashup of <code>http</code> and secure sockets layer/transport layer security (SSL/TLS). It’s one of a number of application layer protocols that are just secured versions of other protocols, like (S)FTP and LDAP(S).</p>
-<div class="callout callout-style-default callout-note callout-titled">
-<div class="callout-header d-flex align-content-center">
-<div class="callout-icon-container">
-<i class="callout-icon"></i>
-</div>
-<div class="callout-title-container flex-fill">
-SSL and TLS
-</div>
-</div>
-<div class="callout-body-container callout-body">
-<p>These days, almost everyone actually uses the successor to SSL, transport layer security (TLS). In fact, we’re now on the 4th version to TLS – version 1.3.</p>
-<p>However, because the experience of configuring TLS is identical to SSL, admins usually just talk about configuring SSL even when they mean TLS.</p>
-</div>
-</div>
-<p>Securing your website or server using SSL/TLS is one of the most basic things you can do to make sure your website traffic is safe. You should always configure <code>https</code> for a public website – full stop.</p>
-<p>In this chapter we’ll go through why using <code>https</code> is so important, how it works, and how to configure <code>https</code> for yourself on your website.</p>
-<section id="the-problems-https-solves" class="level2" data-number="14.1">
-<h2 data-number="14.1" class="anchored" data-anchor-id="the-problems-https-solves"><span class="header-section-number">14.1</span> The problems <code>https</code> solves</h2>
-<p>For a long time, most web traffic was just plain <code>http</code> traffic.</p>
-<p>If you recall, there used to be a lot of warnings around that you shouldn’t just connect to and use the WiFi at your neighborhood Starbucks. That was (mostly) because of the risks of using plain <code>http</code> traffic.</p>
-<p>Over the last 10 years or so, almost all web traffic has migrated to <code>https</code>, particularly since 2015 when Google Chrome began the process of marking any site using plain <code>http</code> as insecure. These days it’s actually pretty safe to use any random WiFi network you want – because of <code>https</code>.</p>
-<p>The biggest risk with those public WiFi networks was that someone could compromise the router. If the router was compromised, there were two things a bad actor could do.</p>
-<p><code>http</code> has no way to verify that the website you <em>think</em> you’re interacting with is actually that website. So a bad actor could mess with the router’s DNS resolution, and make it so that <span class="math inline">\(bankofamerica.com\)</span> went to a lookalike website to capture your banking login. That’s called a <em>man-in-the-middle attack</em>.</p>
-<p><code>http</code> traffic is also completely unencrypted. So that packet you’re sending would be just as readable by someone who installed spyware on the router that’s passing it along as by the website you intended to send it to. This is called a <em>packet sniffing</em> attack.</p>
-<p>Both of these risks are defanged when you’re using <code>https</code> rather than plain <code>http</code>.</p>
+<p>In <a href="2-6-networking.html">Chapter&nbsp;<span>12</span></a>, I used the analogy of putting a letter in the mail for sending HTTP traffic over the web. But that’s actually not right. HTTP traffic sent in plaintext, which means it’s actually like sending a postcard. Anyone along the way can just look right at what you’re sending. That’s bad.</p>
+<p>HTTPS is the digital equivalent of putting your HTTP mail inside an opaque envelope. It doesn’t change anything about the application layer protocol, but it does secure the whole thing.</p>
+<p>In this chapter, you’ll learn the basics of how HTTPS works. In the lab, you’ll configure your site to use HTTPS so that it can be accessed securely.</p>
+<section id="what-https-does" class="level2" data-number="14.1">
+<h2 data-number="14.1" class="anchored" data-anchor-id="what-https-does"><span class="header-section-number">14.1</span> What HTTPS does</h2>
+<p>HTTPS is the same as HTTP, but secured with a technology called <em>SSL/TLS (secure sockets layer/transport layer security)</em>. SSL/TLS works by configuring the resource to provide an <em>SSL certificate</em> upon demand, which is used to verify the site’s identity and establish an encrypted session.</p>
 <div class="callout callout-style-default callout-note callout-titled">
 <div class="callout-header d-flex align-content-center">
 <div class="callout-icon-container">
 <i class="callout-icon"></i>
 </div>
 <div class="callout-title-container flex-fill">
-What doesn’t <code>https</code> do?
+SSL vs TLS
 </div>
 </div>
 <div class="callout-body-container callout-body">
-<p>Using SSL/TLS helps a lot with security – but it’s worth noting that it ends at the domain. Using <code>https</code> validates that you’ve gotten to the real <code>example.com</code> if that’s the website you think you’re visiting. It doesn’t in any way validate who owns <code>example.com</code>, whether they’re reputable, or whether you should trust them.</p>
-<p>There are higher levels of SSL certification that do validate that, for example, the company that owns <code>google.com</code> is actually the company Google.</p>
-</div>
-</div>
-<p>Here’s the process of connecting to a website that uses <code>https</code>. Before your browser starts exchanging any real data with the website, the website sends over its signature, which is generated with its private certificate.</p>
-<p>Your computer checks this signature with a trusted <em>certificate authority</em> (CA) who has a copy of the site’s public certificate. Once your browser has verified that the signature is valid, you know that you’re actually communicating with <span class="math inline">\(bankofamerica.com\)</span> and you’re not victim to a man-in-the-middle attack.</p>
-<p>Once the verification process is done, your browser then establishes an encryption routine with the website on the other end. Only then does it start sending real data – now encrypted so that only the website on the other end can read the contents.</p>
-<div class="cell" data-eval="true">
-<div class="cell-output-display">
-<div>
-<div>
-<pre class="mermaid mermaid-js">graph TD
-    A[Browser] --&gt;|Request| B[SSL Certificate]
-    B --&gt; |Sent| A
-    C[Certificate Authority] --&gt; |Verifies| B
-    A --&gt; |Consults| C
-</pre>
-</div>
-</div>
+<p>TLS is actually what’s in use these, but you’ll mostly talk about SSL. TLS is the successor to SSL, but the configuration is identical, so most people didn’t update how they talk about it.</p>
 </div>
 </div>
+<p>You use HTTPS constantly. Go to a website in your browser and look for a little lock icon near the search bar. That little lock indicates that the domain is secured using HTTPS. If you click on it, you can get more information about the site’s SSL certificate.</p>
+<p>If you’re of a certain age, you may recall warnings that you shouldn’t use the WiFi at your neighborhood Starbucks. The issue was twofold.</p>
+<p>HTTP has no way to verify that the website you <strong>think</strong> you’re interacting with is actually that website. So a bad actor could put up a fake WiFi network that makes <span class="math inline">\(\text{bankofamerica.com}\)</span> resolve to a lookalike website to capture your banking information. That’s called a <em>man-in-the-middle</em> attack.</p>
+<p>And even if they didn’t do that, they could inspect the traffic going back and forth and just read whatever you’re sending over the web in what’s called a <em>packet sniffing</em> attack.</p>
+<p>In 2015, Google Chrome began the process of marking any site using plain HTTP as insecure, which led to nearly complete adoption of HTTPS across the internet. The risk of both of these kinds of attacks has been neutered and it’s actually pretty safe to use any random WiFi network you want these days – because of HTTPS.</p>
+<p>As a website administrator, securing your website or server with HTTPS is one of the most basic things you can do to make sure your website traffic is safe. You should always configure HTTPS for a public website – full stop.</p>
+<p>It’s worth noting that this SSL/TLS security can be applied to a number of different application layer protocols, including (S)FTP and LDAP(S). You may run across these depending on your organization. In any case, the SSL/TLS part works the same and all that changes is what’s inside the secure digital envelope.</p>
+</section>
+<section id="how-ssltls-works" class="level2" data-number="14.2">
+<h2 data-number="14.2" class="anchored" data-anchor-id="how-ssltls-works"><span class="header-section-number">14.2</span> How SSL/TLS works</h2>
+<p>SSL/TLS uses public key encryption (remember, we learned about that in <a href="2-2-cmd-line.html">Chapter&nbsp;<span>8</span></a>) to do two things – validate that the site you’re visiting is the site you intend and encrypt the traffic back and forth to the site.</p>
+<p>To set up SSL for a website, you create or acquire an SSL certificate, which has a public and a private component (sound familiar?).<a href="#fn1" class="footnote-ref" id="fnref1" role="doc-noteref"><sup>1</sup></a> Then, verify the public certificate with a trusted <em>Certificate Authority</em> (CA) and put the private certificate in the right place on the website.<a href="#fn2" class="footnote-ref" id="fnref2" role="doc-noteref"><sup>2</sup></a></p>
+<p>Then, when you go to access that resource, the first thing your machine asks for is a <em>signature</em>. The site uses its private key to generate the signature and your machine verifies the signature against it’s internal trusted <em>CA store</em>.</p>
+<p>Now your machine knows it’s communicating with the right host on the other side and you’re not falling victim to a man-in-the-middle attack.</p>
+<p>Once the verification process is done, your machine and the remote on the other side create temporary <em>session keys</em> to establish encryption with the website on the other end.<a href="#fn3" class="footnote-ref" id="fnref3" role="doc-noteref"><sup>3</sup></a> Only then does it start sending real data, now encrypted securely inside a digital envelope.</p>
+<p><img src="images/ssl.png" class="img-fluid" alt="SSL initialization. 1 client request, 2 public key sent by server, 3 validate key against CA store, 4 establish session w/ session keys." width="600"></p>
 </section>
-<section id="configuring-https" class="level2" data-number="14.2">
-<h2 data-number="14.2" class="anchored" data-anchor-id="configuring-https"><span class="header-section-number">14.2</span> Configuring <code>https</code></h2>
-<p>There are three steps to configuring <code>https</code> on a website you control – getting an SSL certificate, putting the certificate on the server, and making sure the server <em>only</em> accepts <code>https</code> traffic.</p>
-<p>It used to be that getting an SSL certificate was somewhat of a pain. While it could cost less than $10 per year to get a basic SSL certificate for particular subdomains, getting a wildcard certificate that covered all the subdomains of a root domain could be quite pricey.</p>
-<p>The main alternative at the time was to use a <em>self-signed cert</em>. With a self-signed cert, you would create a certificate yourself and add the certificate directly to any machine that needed to access that site. This is a pain. You need to share the certificate with everyone and get them to install it on their machine. Certificates do expire and so this would have to be periodically repeated. The alternative is just to ignore the scary warning that you might be the victim of a man-in-the-middle attack – and some software doesn’t even allow that.</p>
-<p>Luckily there’s now another option. With the rise of <code>https</code> everywhere, there’s now an organization called letsencrypt. It’s a free CA that issues basic SSL/TLS certificates for free. They even have some nice tooling that makes it super easy to create and configure your certificate right on your server.</p>
-<p>When you’re talking about communications that run entirely inside private networks, you have a choice to make. Large organizations often run their own private CA that verifies all the certificates inside your private network.</p>
-<p>This is a bit of a hassle, since you’ve got to maintain the CA and configure every host inside the network to trust your private CA. Many organizations decide they’re fine with plain <code>http</code> communication within private networks.</p>
-<p>Either way, once you’ve configured your server with <code>https</code>, you generally want to shut down access via plain <code>http</code>, usually by redirecting <code>http</code> traffic, which comes in on port <code>80</code> to come in over <code>https</code> via port <code>443</code>.</p>
+<section id="getting-and-using-ssl-certificates" class="level2" data-number="14.3">
+<h2 data-number="14.3" class="anchored" data-anchor-id="getting-and-using-ssl-certificates"><span class="header-section-number">14.3</span> Getting and using SSL certificates</h2>
+<p>When you buy a computer, it comes configured out of the box to trust a small number of official CAs. So if you’re a website wanting to get a certificate, you generally want to get it from one of those CAs.</p>
+<p>This used to be kinda a pain. The CAs charged to issue certificates. While it was only $10 per year to for a basic SSL certificate, they typically would only cover a single subdomain. A <em>wildcard</em> certificate to cover all the subdomains of a root domain was expensive enough to discourage hobbyists.</p>
+<p>If you wanted a free certificate, your only option was to use a <em>self-signed certificate</em>, which you’d create similarly to creating an SSH key. This was a pain because you had to manually add the public certificate to the CA store of every machine that would be accessing the site, and then re-add it when the certificate expired.<a href="#fn4" class="footnote-ref" id="fnref4" role="doc-noteref"><sup>4</sup></a></p>
+<p>Luckily there’s now another option. For most small organizations, I recommend getting a free SSL certificate from the nonprofit CA <em>Let’s Encrypt</em>. They even have some nice tooling that makes it super easy to create and configure your certificate right on your server.</p>
+<p>For most organizations, using a public CA to get SSL on public-facing resources is sufficient and use plain HTTP inside private networks. Some large organizations want to encrypt their private traffic as well and run their own private CA. If this is the case, your organization’s policies will make it clear. This can be a pain, because you’ve got to make sure every host inside the network trusts the private CA.</p>
+<p>Once you’ve configured SSL/TLS, you generally want to <strong>only</strong> allow HTTPS traffic to your site. You’ll accomplish this by redirecting all HTTP traffic on port <span class="math inline">\(80\)</span> to come in via HTTPS on port <span class="math inline">\(443\)</span>.</p>
+<p>Some web applications support configuring a certificate directly, while others only accept HTTP traffic, so you’d need to do <em>SSL termination</em> with a proxy in front of the application.</p>
 </section>
-<section id="comprehension-questions" class="level2" data-number="14.3">
-<h2 data-number="14.3" class="anchored" data-anchor-id="comprehension-questions"><span class="header-section-number">14.3</span> Comprehension Questions</h2>
+<section id="comprehension-questions" class="level2" data-number="14.4">
+<h2 data-number="14.4" class="anchored" data-anchor-id="comprehension-questions"><span class="header-section-number">14.4</span> Comprehension Questions</h2>
 <ol type="1">
-<li>What are the two risks of using plain <code>http</code> and how does <code>https</code> mitigate that?</li>
+<li>What are the two risks of using plain HTTP and how does HTTPS mitigate them?</li>
 <li>Write down a mental map of how SSL secures your web traffic. Include the following: public certificate, private certificate, certificate authority, encrypted traffic, port 80, port 443</li>
 </ol>
 </section>
-<section id="lab-configure-ssl" class="level2" data-number="14.4">
-<h2 data-number="14.4" class="anchored" data-anchor-id="lab-configure-ssl"><span class="header-section-number">14.4</span> Lab: Configure SSL</h2>
-<p>We’re going to use letsencrypt’s certbot utility to automatically generate an SSL certificate, share it with the CA, install it on the server, and even update your nginx configuration.</p>
-<p>For anyone who’s never dealt with self-signing certificates in the past, let me tell you, the fact that it does this all automatically is magical!</p>
-<section id="step-1-update-nginx-configuration" class="level3" data-number="14.4.1">
-<h3 data-number="14.4.1" class="anchored" data-anchor-id="step-1-update-nginx-configuration"><span class="header-section-number">14.4.1</span> Step 1: Update Nginx configuration</h3>
-<p>In our nginx configuration, we’ll need to add a line certbot will use to know which site to generate the certificate for.</p>
-<p>Somewhere inside the nginx configuration’s server block, add</p>
-<div class="code-with-filename">
-<div class="code-with-filename-file">
-<pre><strong>/etc/nginx/nginx.conf</strong></pre>
-</div>
-<div class="sourceCode" id="cb1"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb1-1"><a href="#cb1-1"></a><span class="ex">server_name</span> do4ds-lab.shop www.do4ds-lab.shop<span class="kw">;</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-</div>
-<p>substituting in your domain for mine. Make sure to include both the bare domain and the <code>www</code> subdomain.</p>
-</section>
-<section id="step-2-certbot-does-its-thing" class="level3" data-number="14.4.2">
-<h3 data-number="14.4.2" class="anchored" data-anchor-id="step-2-certbot-does-its-thing"><span class="header-section-number">14.4.2</span> Step 2: Certbot does its thing</h3>
-<p>If you google “configure nginx with letsencrypt”, there’s a <a href="https://www.nginx.com/blog/using-free-ssltls-certificates-from-lets-encrypt-with-nginx/">great article</a> by someone at Nginx walking you through the process.</p>
-<p>As of this writing, that was as simple as running these lines on the server</p>
-<div class="code-with-filename">
-<div class="code-with-filename-file">
-<pre><strong>Terminal</strong></pre>
-</div>
-<div class="sourceCode" id="cb2"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb2-1"><a href="#cb2-1"></a><span class="fu">sudo</span> apt-get install certbot python3-certbot-nginx </span>
-<span id="cb2-2"><a href="#cb2-2"></a><span class="fu">sudo</span> systemctl restart nginx </span>
-<span id="cb2-3"><a href="#cb2-3"></a><span class="fu">sudo</span> certbot <span class="at">--nginx</span> <span class="at">-d</span> do4ds-lab.shop <span class="at">-d</span> www.do4ds-lab.shop</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-</div>
+<section id="lab-configure-ssl" class="level2" data-number="14.5">
+<h2 data-number="14.5" class="anchored" data-anchor-id="lab-configure-ssl"><span class="header-section-number">14.5</span> Lab: Configure SSL</h2>
+<p>We’re going to use Let’s Encrypt’s <em>certbot</em> utility to automatically generate an SSL certificate, share it with the CA, install it on the server, and even update your NGINX configuration.</p>
+<p>If you’ve never had to manually configure SSL in the past, let me tell you, this is magical!</p>
+<section id="step-1-follow-instructions-to-add-ssl-for-nginx" class="level3" data-number="14.5.1">
+<h3 data-number="14.5.1" class="anchored" data-anchor-id="step-1-follow-instructions-to-add-ssl-for-nginx"><span class="header-section-number">14.5.1</span> Step 1: Follow instructions to add SSL for NGINX</h3>
+<p>Using Let’s Encrypt to add an SSL certificate to NGINX configuration is a super common task. As of this writing, there’s a great blog post entitled <a href="https://www.nginx.com/blog/using-free-ssltls-certificates-from-lets-encrypt-with-nginx/"><em>Using Free Let’s Encrypt SSL/TLS Certificates with NGINX</em></a>. I’d encourage you to look for that article (or something similar) and follow the steps there.</p>
+<p>At a high level, what you’ll do is</p>
+<ol type="1">
+<li>Configure the NGINX configuration to know what domain its on.</li>
+<li>Install certbot on the system.</li>
+<li>Run certbot to get the certificate, apply it to the server, and update the NGINX configuration.</li>
+</ol>
 <p>Before you move along, I’d recommend you take a moment and inspect the <code>/etc/nginx/nginx.conf</code> file to look at what certbot added.</p>
-<p>You’ll notice two things. You’ll notice that the <code>listen 80</code> is gone from inside the server block. We’re no longer listening for <code>http</code> traffic.</p>
-<p>Instead there’s a <code>listen 443</code> – the default port for <code>https</code>, and a bunch of stuff that tells Nginx where to find the certificate on the server.</p>
-<p>Scrolling down a little, there’s a new server block that <em>is</em> listening on <code>80</code>. This block returns a <code>301</code>, which you might recall is a redirect code (specifically for a <em>permanent</em> redirect) sending all <code>http</code> traffic to <code>https</code>.</p>
+<p>Relative to the old version, you’ll notice two things. First, the line that read <code>listen 80</code> is gone from the server block because we’re no longer listening for HTTP traffic. In it’s place, there’s now a <code>listen 443</code> along with a bunch of stuff that tells NGINX where to find the certificate on the server.</p>
+<p>Scrolling down a little, there’s a new server block that <strong>is listening</strong> on <span class="math inline">\(80\)</span>. This block returns a <code>301</code> status code (permanent redirect) and sends traffic to HTTPS on <span class="math inline">\(443\)</span>.</p>
 </section>
-<section id="step-3-let-rstudio-know-its-on-https" class="level3" data-number="14.4.3">
-<h3 data-number="14.4.3" class="anchored" data-anchor-id="step-3-let-rstudio-know-its-on-https"><span class="header-section-number">14.4.3</span> Step 3: Let RStudio know it’s on <code>https</code></h3>
-<p>Before we exit and test it out, let’s do one more thing. RStudio does a bunch of sending traffic back to itself. For that reason, the <code>/rstudio</code> proxy location <em>also</em> needs to know to upgrade traffic from <code>http</code> to <code>https</code>.</p>
-<p>So add the following line to the Nginx config:</p>
+<section id="step-2-let-rstudio-server-know-its-on-https" class="level3" data-number="14.5.2">
+<h3 data-number="14.5.2" class="anchored" data-anchor-id="step-2-let-rstudio-server-know-its-on-https"><span class="header-section-number">14.5.2</span> Step 2: Let RStudio Server know it’s on HTTPS</h3>
+<p>Before we exit and test it out, let’s do one more thing. As mentioned when we configured NGINX the first time, RStudio Server does a bunch of proxying traffic back to itself, so it needs to know that it’s on HTTPS.</p>
+<p>You can let RStudio Server know that it’s on HTTPS by adding a header to all traffic letting RStudio Server know the protocol is HTTPS. You can add this line to your <code>nginx.conf</code>:</p>
 <div class="code-with-filename">
 <div class="code-with-filename-file">
 <pre><strong>/etc/nginx/nginx.conf</strong></pre>
 </div>
-<div class="sourceCode" id="cb3"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb3-1"><a href="#cb3-1"></a><span class="ex">proxy_set_header</span> X-Forwarded-Proto https<span class="kw">;</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
+<div class="sourceCode" id="cb1"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb1-1"><a href="#cb1-1"></a><span class="ex">proxy_set_header</span> X-Forwarded-Proto https<span class="kw">;</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 </div>
-<p>This line adds a header to the traffic the proxy forwards specifying the protocol to be <code>https</code>. RStudio Server uses this header to know that it should send traffic back to itself using <code>https</code>, not <code>http</code>.</p>
-<p>Ok, now try it by going to the URL your server is hosted at, and you’ll find that…it’s broken again.</p>
+<p>Ok, now try to visit RStudio Server at your URL, and you’ll find that…it’s broken again.</p>
 <p>Before you read along, think for just a moment. Why is it broken?</p>
 </section>
-<section id="step-4-configure-security-groups" class="level3" data-number="14.4.4">
-<h3 data-number="14.4.4" class="anchored" data-anchor-id="step-4-configure-security-groups"><span class="header-section-number">14.4.4</span> Step 4: Configure security groups</h3>
+<section id="step-3-configure-security-groups" class="level3" data-number="14.5.3">
+<h3 data-number="14.5.3" class="anchored" data-anchor-id="step-3-configure-security-groups"><span class="header-section-number">14.5.3</span> Step 3: Configure security groups</h3>
 <p>If your thoughts went to something involving ports and AWS security groups, you’re right!</p>
-<p>By default, our server was open to SSH traffic on port <code>22</code>. Since then, we may have opened or closed port <code>80</code>, <code>8000</code>, <code>8787</code>, and/or <code>8080</code>.</p>
-<p>But now that we’re exclusively sending <code>https</code> traffic into the proxy on <code>443</code> and letting the proxy redirect things elsewhere. So you have to go into the security group settings and change it so there are only 2 rules – one that allows SSH traffic on <code>22</code> from anywhere and one that allows <code>https</code> traffic on <code>443</code> from anywhere.</p>
-<p>It’s up to you whether you want to leave port <code>80</code> open. If you do, it will redirect people to <code>https</code> on <code>443</code>. If you close it entirely, people who come to port <code>80</code> will just be blocked and will eventually get a timeout. That shouldn’t be an issue as all modern browsers default to <code>https</code>.</p>
-<div class="callout callout-style-default callout-note callout-titled">
-<div class="callout-header d-flex align-content-center">
-<div class="callout-icon-container">
-<i class="callout-icon"></i>
-</div>
-<div class="callout-title-container flex-fill">
-Note
-</div>
-</div>
-<div class="callout-body-container callout-body">
-<p>If you decided to only configure <em>one</em> service on the server, you could have a much simpler setup. Neither RStudio Server nor Plumber support direct configuration of a SSL certificate, so you would still need a proxy – though it could be a much simpler configuration that just passes traffic at the root <code>/</code> on to your service at a different port.</p>
-<p>JupyterHub can be configured directly with an SSL certificate, so you would just configure JupyterHub to be aware of the SSL certificate and put itself on port <code>443</code>.</p>
-</div>
-</div>
+<p>By default, our server was open to SSH traffic on port <span class="math inline">\(22\)</span>. Since then, we may have opened or closed port <span class="math inline">\(80\)</span>, <span class="math inline">\(8000\)</span>, <span class="math inline">\(8080\)</span>, <span class="math inline">\(8787\)</span>, and/or <span class="math inline">\(3838\)</span>.</p>
+<p>But now that we’re exclusively sending HTTPS traffic into the proxy on <span class="math inline">\(443\)</span> and letting the proxy redirect things elsewhere. So you have to go into the security group settings and change it so there are only 2 rules – one that allows SSH traffic on <span class="math inline">\(22\)</span> and one that allows HTTPS traffic on <span class="math inline">\(443\)</span>.</p>
+<p>It’s up to you whether you want to leave port <span class="math inline">\(80\)</span> open. If you do, it will redirect people to HTTPS on <span class="math inline">\(443\)</span>. If you close it entirely, people who come to port <span class="math inline">\(80\)</span> will be blocked and will eventually get a timeout. If people are used to coming to the server via HTTP, it might be nice to leave <span class="math inline">\(80\)</span> open so they get a nice redirect experience instead of getting confusingly blocked.</p>
 </section>
-<section id="step-5-check-it-out" class="level3" data-number="14.4.5">
-<h3 data-number="14.4.5" class="anchored" data-anchor-id="step-5-check-it-out"><span class="header-section-number">14.4.5</span> Step 5: Check it out!</h3>
-<p>NOW you should be able to go to <code>&lt;your-domain&gt;/rstudio</code> and get to RStudio, <code>&lt;your-domain&gt;/jupyter</code> to get to JupyterHub, and <code>&lt;your-domain&gt;/penguins</code> to get the API! Voila!</p>
-<p>And you should still be able to SSH into your server on your domain.</p>
-<p>At this point your server is fully configured. You have a server hosting three real data science services available on a domain of your choosing protected by <code>https</code>. You can really use this server to do real data science work.</p>
-<p>That’s not to say this is fully enterprise-ready. If you’re working on a small team or at a small organization, this may be sufficient. But if you’re working at a large organization, your IT/Admin group is going to have other concerns.</p>
-<p>You can learn more about what those concerns are in the last section of this book, starting with <span class="quarto-unresolved-ref">?sec-4-intro</span>.</p>
+<section id="step-4-we-did-it" class="level3" data-number="14.5.4">
+<h3 data-number="14.5.4" class="anchored" data-anchor-id="step-4-we-did-it"><span class="header-section-number">14.5.4</span> Step 4: We did it!</h3>
+<p>This is the end of the labs in this book.</p>
+<p>At this point your server is fully configured. You have three real data science services available on a domain of your choosing protected by HTTPS and you can SSH in to do admin work.</p>
+<p>Take a moment to celebrate. It’s very cool to be able to stand up and administer your own data science workbench. If you’re working at a small organization or are a hobbyist, you can really use this server to do real data science work.</p>
+<p>But this server isn’t enterprise-ready. If you work at a large organization or one with stringent security or privacy rules, your IT/Admin group is going to have concerns. Read on to learn more about what they are and why they’re completely valid.</p>
 
 
 </section>
 </section>
+<section id="footnotes" class="footnotes footnotes-end-of-document" role="doc-endnotes">
+<hr>
+<ol>
+<li id="fn1"><p>Like with SSL, this makes more sense if you think key where you see private and lock where you see public.<a href="#fnref1" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
+<li id="fn2"><p>The CA verifies the certificate by signing it. Your machine just keeps public certificates for the CAs. Then, when it gets an SSL certificate that’s signed by one of those CAs, it can validate that the CA actually stamped this certificate as valid.<a href="#fnref2" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
+<li id="fn3"><p>Unlike the asymmetric encryption used by SSL and SSH for the public key encryption, the session keys are symmetric, so they work the same in both directions.<a href="#fnref3" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
+<li id="fn4"><p>You also could skip that step, in which case you got the session encryption benefits of SSL/TLS, but not the verification.<a href="#fnref4" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
+</ol>
+</section>
 
 </main> <!-- /main -->
 <script id="quarto-html-after-body" type="application/javascript">
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+      <a href="../../chapters/sec2/2-7-dns.html" class="pagination-link">
         <i class="bi bi-arrow-left-short"></i> <span class="nav-page-text"><span class="chapter-number">13</span>&nbsp; <span class="chapter-title">DNS allows for human-readable addresses</span></span>
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+      <a href="../../chapters/sec3/3-0-sec-intro.html" class="pagination-link">
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diff --git a/chapters/sec3/3-0-sec-intro.html b/chapters/sec3/3-0-sec-intro.html
index c38278ee5..afe9e232b 100644
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-<title>DevOps for Data Science - IT/Admin for Data Science</title>
+<title>DevOps for Data Science - Making it Enterprise-Grade</title>
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-<link href="../../chapters/sec3/3-1-cloud.html" rel="next">
-<link href="../../chapters/sec2/2-4-docker.html" rel="prev">
+<link href="../../chapters/sec3/3-1-os-ds-in-ent.html" rel="next">
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 <script src="../../site_libs/quarto-html/popper.min.js"></script>
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+      <nav class="quarto-page-breadcrumbs" aria-label="breadcrumb"><ol class="breadcrumb"><li class="breadcrumb-item"><a href="../../chapters/sec3/3-0-sec-intro.html">Making it Enterprise-Grade</a></li></ol></nav>
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       <button type="button" class="btn quarto-search-button" aria-label="Search" onclick="window.quartoOpenSearch();">
@@ -177,13 +177,19 @@
   <a href="../../chapters/sec1/1-5-deployments.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">5</span>&nbsp; <span class="chapter-title">Deployments and code promotion</span></span></a>
   </div>
+</li>
+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/sec1/1-6-docker.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">6</span>&nbsp; <span class="chapter-title">Demystifying Docker</span></span></a>
+  </div>
 </li>
       </ul>
   </li>
         <li class="sidebar-item sidebar-item-section">
       <div class="sidebar-item-container"> 
             <a href="../../chapters/sec2/2-0-sec-intro.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text">IT/Admin Tools</span></a>
+ <span class="menu-text">IT/Admin for Data Science</span></a>
           <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-2" aria-expanded="true" aria-label="Toggle section">
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       <ul id="quarto-sidebar-section-2" class="collapse list-unstyled sidebar-section depth1 show">  
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   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec2/2-1-cmd-line.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">6</span>&nbsp; <span class="chapter-title">Opening the Command Line</span></span></a>
+  <a href="../../chapters/sec2/2-1-cloud.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">7</span>&nbsp; <span class="chapter-title">The Cloud</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec2/2-2-cmd-line-use.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">7</span>&nbsp; <span class="chapter-title">Using the Command Line</span></span></a>
+  <a href="../../chapters/sec2/2-2-cmd-line.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">8</span>&nbsp; <span class="chapter-title">Customizing the command line</span></span></a>
   </div>
 </li>
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-  <a href="../../chapters/sec2/2-3-ssh.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">8</span>&nbsp; <span class="chapter-title">Secure server connections with SSH</span></span></a>
+  <a href="../../chapters/sec2/2-3-linux.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">9</span>&nbsp; <span class="chapter-title">Intro to Linux Administration</span></span></a>
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 </li>
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-  <a href="../../chapters/sec2/2-4-docker.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">9</span>&nbsp; <span class="chapter-title">Demystifying Docker</span></span></a>
+  <a href="../../chapters/sec2/2-4-app-admin.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Application administration</span></span></a>
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-      </ul>
-  </li>
-        <li class="sidebar-item sidebar-item-section">
-      <div class="sidebar-item-container"> 
-            <a href="../../chapters/sec3/3-0-sec-intro.html" class="sidebar-item-text sidebar-link active">
- <span class="menu-text">IT/Admin for Data Science</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-3" aria-expanded="true" aria-label="Toggle section">
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-  <a href="../../chapters/sec3/3-1-cloud.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Getting Started with the Cloud</span></span></a>
+  <a href="../../chapters/sec2/2-5-scale.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Server Resources and Scaling</span></span></a>
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-  <a href="../../chapters/sec3/3-2-linux-admin.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Basic Linux SysAdmin</span></span></a>
-  </div>
-</li>
-          <li class="sidebar-item">
-  <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-3-networking.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-6-networking.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">12</span>&nbsp; <span class="chapter-title">Intro to Computer Networks</span></span></a>
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 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-4-dns.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-7-dns.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">13</span>&nbsp; <span class="chapter-title">DNS allows for human-readable addresses</span></span></a>
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 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-5-ssl.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-8-ssl.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">14</span>&nbsp; <span class="chapter-title">You should use SSL/HTTPS</span></span></a>
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-</li>
-          <li class="sidebar-item">
-  <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-6-servers.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Choosing the right server for you</span></span></a>
-  </div>
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       <div class="sidebar-item-container"> 
-            <a href="../../chapters/sec4/4-0-sec-intro.html" class="sidebar-item-text sidebar-link">
+            <a href="../../chapters/sec3/3-0-sec-intro.html" class="sidebar-item-text sidebar-link active">
  <span class="menu-text">Making it Enterprise-Grade</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true" aria-label="Toggle section">
+          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-3" aria-expanded="true" aria-label="Toggle section">
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+      <ul id="quarto-sidebar-section-3" class="collapse list-unstyled sidebar-section depth1 show">  
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   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec4/4-1-os-ds-in-ent.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></a>
+  <a href="../../chapters/sec3/3-1-os-ds-in-ent.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></a>
   </div>
 </li>
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-  <a href="../../chapters/sec4/4-2-ent-networks.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></a>
+  <a href="../../chapters/sec3/3-2-ent-networks.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></a>
   </div>
 </li>
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-  <a href="../../chapters/sec4/4-3-auth.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></a>
+  <a href="../../chapters/sec3/3-3-auth.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></a>
   </div>
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           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec4/4-4-ent-servers.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">19</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></a>
+  <a href="../../chapters/sec3/3-4-ent-servers.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></a>
   </div>
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       </ul>
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         <li class="sidebar-item sidebar-item-section">
       <div class="sidebar-item-container"> 
-            <a class="sidebar-item-text sidebar-link text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-5" aria-expanded="true">
+            <a class="sidebar-item-text sidebar-link text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true">
  <span class="menu-text">Appendices</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-5" aria-expanded="true" aria-label="Toggle section">
+          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true" aria-label="Toggle section">
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-      <ul id="quarto-sidebar-section-5" class="collapse list-unstyled sidebar-section depth1 show">  
+      <ul id="quarto-sidebar-section-4" class="collapse list-unstyled sidebar-section depth1 show">  
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
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@@ -317,6 +300,12 @@
   <a href="../../chapters/append/lab-map.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">B</span>&nbsp; <span class="chapter-title">Lab Map</span></span></a>
   </div>
+</li>
+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/append/cheatsheets.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">C</span>&nbsp; <span class="chapter-title">Cheatsheets</span></span></a>
+  </div>
 </li>
       </ul>
   </li>
@@ -330,7 +319,8 @@
     <h2 id="toc-title">Table of contents</h2>
    
   <ul>
-  <li><a href="#labs-in-this-section" id="toc-labs-in-this-section" class="nav-link active" data-scroll-target="#labs-in-this-section">Labs in this Section</a></li>
+  <li><a href="#what-enterprise-it-is-about" id="toc-what-enterprise-it-is-about" class="nav-link active" data-scroll-target="#what-enterprise-it-is-about">What enterprise IT is about</a></li>
+  <li><a href="#labs-in-this-section" id="toc-labs-in-this-section" class="nav-link" data-scroll-target="#labs-in-this-section">Labs in this Section</a></li>
   </ul>
 <div class="toc-actions"><div><i class="bi bi-github"></i></div><div class="action-links"><p><a href="https://github.com/akgold/do4ds/edit/main/chapters/sec3/3-0-sec-intro.qmd" class="toc-action">Edit this page</a></p></div></div></nav>
     </div>
@@ -339,7 +329,7 @@ <h2 id="toc-title">Table of contents</h2>
 
 <header id="title-block-header" class="quarto-title-block default">
 <div class="quarto-title">
-<h1 class="title"><span id="sec-3-intro" class="quarto-section-identifier">IT/Admin for Data Science</span></h1>
+<h1 class="title"><span id="sec-4-intro" class="quarto-section-identifier">Making it Enterprise-Grade</span></h1>
 </div>
 
 
@@ -354,29 +344,49 @@ <h1 class="title"><span id="sec-3-intro" class="quarto-section-identifier">IT/Ad
 
 </header>
 
-<p>Data scientists shouldn’t be responsible for server administration. There’s a reason IT Administration is a career all to itself. There’s so much to know about servers, networking, managing users, storage, and more.</p>
-<p>You’re probably great at writing R or Python code, cleaning and managing data, or building models. Unless you feel like a career switch, managing servers isn’t in your core skillset.</p>
-<p>And being responsible for a server is scary – you can unknowingly make choices that cause security vulnerabilities, system instability, and general annoyance.</p>
-<p>That said, there are good reasons you might find yourself administering a server. Maybe you’re a student who wants to host a project for portfolio purposes, the hobbyist who’s hosting a toy project, or the data science leader who has no choice but to host things for themselves because they just can’t get IT/Admin support.</p>
-<p>I’ve been in all of these situations. Believe, me <em>I feel you</em>.</p>
-<p>The good news is that if you are in any of those roles, you’ve come to the right place.</p>
-<p>The first section of this book focused on how to move your data science practices closer to the DevOps ideal by doing Dev better.</p>
-<p>This section focuses on how to do Ops. In contrast to the first section, which assumed a pretty high level of understanding and focused on best practices, this section is a lot of introductory IT/Admin knowledge. This section assumes you know nothing about how to administer a server other than the tools introduced in <span class="quarto-unresolved-ref">?sec-2-intro</span>.</p>
-<p>Throughout the chapters in this section, you’re going to learn standard patterns for simple administrative tasks for servers and apply those to a data science use-case. By the time you’re done, you’ll be ready to administer a simple server-based environment for doing or deploying data science in the cloud.</p>
-<p>So what exactly will you learn about in this section?</p>
-<p>We’ll start with an intro to the cloud – what it is, how it works, and how to make use of it for data science purposes. We’ll then spend a chapter on Linux administration. If you’re using a server, it’s going to be a Linux server, and understanding how to administer a Linux server is worth learning. We’ll then spend three chapters on several facets of networking, including a basic intro, how getting and using a domain name works, and how to secure a server with SSL/HTTPS. Lastly, we’ll get into how to choose the size and type of server to use for your data science purposes.</p>
-<p>Each chapter in this section is accompanied by a <em>lab</em>. If you follow along with the labs in this section, you’ll get an AWS server configured and ready to run RStudio Server, JupyterHub, and serve model predictions out of a Docker Container. While these aren’t all the things you could want to do on a server, once you’ve learned to do these tasks, many other things will be reasonably similar.</p>
-<p>What you’ll learn in this section and in the labs should be sufficient for you to do data science on a server for a small group of data scientists who you trust, assuming you’re not using data that is especially sensitive.</p>
-<p>If this isn’t you – if you actually do have IT/Admin support, I’d still recommend skimming this section, especially Chapters <a href="3-3-networking.html"><span>Chapter&nbsp;12</span></a>, <a href="3-4-dns.html"><span>Chapter&nbsp;13</span></a>, and <a href="3-5-ssl.html"><span>Chapter&nbsp;14</span></a>. Being able to understand a little bit about networking will make it way easier to communicate with the IT/Admin group at your organization.</p>
-<p>And don’t forget, there’s still section 4 – where you’ll learn more about how to communicate with IT/Admin professionals for issues that really should be left to them.</p>
-<p>Let’s jump in!</p>
+<p>Over the last few chapters, we walked through getting set up with a server, accessing and managing the server via SSH, understanding DNS and getting a real URL, securing the server with SSL/HTTPS, and right-sizing the server for your needs.</p>
+<p>And if you walked through the process with the labs, you’ve got a data science workbench running RStudio Server, JupyterHub, and a model-serving API all of your own. That’s awesome!</p>
+<p>That server is great if you’re working alone on some data science projects you want to host in the cloud or if you’ve got a small team of data scientists in a small organization.</p>
+<p>But if you work at a large organization, an organization with more-stringent security needs, or a larger team of data scientists, you’re going to need to start considering some more complex ways of managing your data science environment for security and stability.</p>
+<p>Broadly speaking, these concerns fall under the context of <em>enterprise</em>. In this context, Enterprise roughly translates to “a large organization with well-defined IT/Admin responsibilities and roles”. If you’re not in an Enterprise, you likely have the rights and ability to just stand up a data science workbench and use it, like we did in the last section.</p>
+<p>If you are in an Enterprise, you probably had to do all that on a personal account, and almost certainly couldn’t connect to your real data sources.</p>
+<p>In general, organizations are trying to implement something called the <em>principle of least privilege</em>. The idea behind this is that they are trying to keep systems safe and stable by giving people the permissions they need to get their work done – and no more. For example, let’s say you’re working in a data science workbench environment. You need a place where you can write code and load data. It might occasionally be useful to have root access on the server to be able to make updates to the server. But are you going to get that in an enterprise environment? Almost certainly not, because you don’t need it to get your work done day-to-day. Instead, you’ll have to coordinate with the IT/Admin team if you need to get something done that requires root access.</p>
+<p>Doing open source data science in an Enterprise almost certainly means having to work across teams to get your workbench built and having to convince other people that you’ll be a good actor at the end of the day.</p>
+<p>The goal of the next few chapters is to help you understand the ways your data science workbench isn’t enterprise and how to communicate with the IT/Admins at your organization who are responsible for such things. We’ll get into how to integrate open-source data science into an organization, what more complex network architecture might look like, how auth works, and how to scale your environment.</p>
+<p>Hopefully you won’t have to implement much of this yourself. Instead, the hope is that reading and understanding the content in this chapter will help make you a better partner to the teams at your organization who <em>are</em> responsible for these things. You’ll be equipped with the language and mental models to ask good questions and give informative answers to the questions the IT/Admins have about your team’s requirements.</p>
+<section id="what-enterprise-it-is-about" class="level2">
+<h2 class="anchored" data-anchor-id="what-enterprise-it-is-about">What enterprise IT is about</h2>
+<p>As a data scientist, your primary concern about your data science environment is that it’s useful. You want to be able to get all the data you want at your fingertips.</p>
+<p>Many data scientists in enterprises find that this desire runs headlong into requirements from their organization’s IT/Admin teams.</p>
+<p>This can be extremely frustrating, so it’s helpful to understand the concerns enterprise IT/Admins have in mind. Broadly, IT/Admins care about the security and stability of the systems they control.</p>
+<p>Great IT/Admin teams also care about the usefulness of the system to users (that’s you), but it’s usually a distant third. And there is sometimes a tension here. After all the only system that’s completely secure is the one that doesn’t exist at all.</p>
+<p>But that’s not always the case. Often, there’s a lot to gain by partnering with the IT/Admin team at your organization. You may be primarily focused on getting stuff done minute-to-minute, but a data science platform that is insecure and allows bad actors to break in and steal data is not useful. And one where you can do what you want but end up crashing the workbench for 50 other users is ultimately self-defeating.</p>
+<p>Balancing security, stability, and usefulness is always about tradeoffs. Great IT/Admin organizations are constantly in conversations with other parts of the organization to figure out the right stance for your organization given the set of tradeoffs you face.</p>
+<p>Unfortunately, many IT/Admin organizations don’t act that way – they act as gatekeepers to the resources you need to do your job. That means you’ll have to figure out how to communicate with those teams, understand what matters to them, help them understand what matters to you, and reach acceptable organizational outcomes.</p>
+<p>You probably already have a good understanding of how a data science environment can be useful – but what about secure and stable. What do they mean?</p>
+<p>Security is about making sure that the right people can interact with the systems they’re supposed to and that unauthorized people can’t.</p>
+<p>IT security professionals think about <em>security in layers</em>. And while you’ve done a good job setting your server up to comply with basic security best practices, there are no layers. That server front door is open to the internet. Literally anyone in the world can come to that authentication page for your RStudio Server or JupyterHub and start trying out passwords. That means you’re just one person choosing the password <code>password</code> away from a bad actor getting access to your server.</p>
+<p>Lest you think you’re immune because you’re not an interesting target, there are plenty of bots out there randomly trying to break in to every existing IP Address, not because they care about what’s inside, but because they want to co-opt your resources for their own purposes like crypto mining or virtual DDOS attacks on Turkish banks.<a href="#fn1" class="footnote-ref" id="fnref1" role="doc-noteref"><sup>1</sup></a></p>
+<p>Moreover, security and IT professionals aren’t just concerned with bad actors from outside (called outsider threat) or even someone internal who decides to steal data or resources (insider threat). They are (or at least should be) also concerned with accidents and mistakes – data that is accidentally permanently deleted is bad the same way stolen data is bad.</p>
+<p>Stability is ensuring enterprise-grade systems are around when people need them, and that they are stable during whatever load they face during the course of operating. The importance of stability tends to rise along with the scale of the team and the centrality of their operations to the functioning of your organization.</p>
+<p>If you’re a team of three data scientists who sit in a room together, it probably won’t be a huge deal if someone accidentally knocks your data science workbench offline for 30 minutes because they tried to run a job that was too big. You’re probably all sitting in the same room and you can learn something from the experience.</p>
+<p>That’s not the case when you get to enterprise-grade tooling. An enterprise-grade data science workbench probably supports dozens or hundreds of professionals across multiple teams. The server being down isn’t a sorta funny occurrence you can all fix together – it’s a problem that must be fixed immediately – or even better avoided altogether.</p>
+<p>IT/Admins think hard about how to provide resources in a way that avoids having servers go down because they’re hitting resource constraints.</p>
+<p>One thing that is almost certain to be untrue in an enterprise context is that you’ll have root access as a user of the system.</p>
+<p>There is no one-size-fits-all (or even most) position for security. Instead, great security teams are constantly articulating and making decisions about tradeoffs.</p>
+</section>
 <section id="labs-in-this-section" class="level2">
 <h2 class="anchored" data-anchor-id="labs-in-this-section">Labs in this Section</h2>
-<p>Each chapter in this section has a lab. This section is about building out the backend around the website we created in the first section of the book.</p>
-<p>In this section you’ll stand up an EC2 instance to serve as a workbench, add tools to work in R or Python, and host your Dockerized model and Shiny app there. We’ll also add the Shiny app to the website you created and make sure all the plumbing gets hooked up.</p>
-<p>For more details on what you’ll do in each chapter, see <a href="../append/lab-map.html">Appendix&nbsp;<span>B</span></a>.</p>
+<p>There are no labs in this section. This section is about how to interact with a professional IT/Admin group. Since it’s about work you really shouldn’t undertake yourself, there are no labs for you to DIY these things.</p>
+<p>If you want to go deeper into any of the topics, there are plenty of great resources online – a google search should turn them up quickly</p>
 
 
+</section>
+<section id="footnotes" class="footnotes footnotes-end-of-document" role="doc-endnotes">
+<hr>
+<ol>
+<li id="fn1"><p>Yes, these both really happened.<a href="#fnref1" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
+</ol>
 </section>
 
 </main> <!-- /main -->
@@ -615,13 +625,13 @@ <h2 class="anchored" data-anchor-id="labs-in-this-section">Labs in this Section<
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-  <li><a href="#layers-of-cloud-services" id="toc-layers-of-cloud-services" class="nav-link active" data-scroll-target="#layers-of-cloud-services"><span class="header-section-number">10.1</span> Layers of cloud services</a></li>
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-<h1 class="title"><span id="sec-cloud" class="quarto-section-identifier"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Getting Started with the Cloud</span></span></h1>
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-<p>Let’s say your organization decides that they need a server to process a large monthly analytics job. If the year is before 2006, you basically only have one option, hosting a server yourself – usually called on-prem.</p>
-<p>So before you can start running the job, you’ll need to buy a physical server, wait for it to be delivered, install it in a server rack, and get it configured with the proper operating system, networking, and connectivity. Only then can you start configuring it to run analytics workloads.</p>
-<p>Things are different today. While there are still organizations who run on-prem analytics workloads, many organizations are moving or have moved their data science and analytics workloads to <em>the cloud</em>.</p>
-<p>So, what is <em>the cloud</em>? To put it simply, the cloud is the term for the immense server farms owned by the provider companies who rent them to organizations in need of computational capacity. When you want to get a server from the cloud, you can just request a certain configuration from the cloud provider and you’ll have it within seconds.</p>
-<p>In this chapter, we’re going to get into what the cloud is, why you might want to use it, and spend some time on a lab where we’ll get a cloud server of our own.</p>
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-A quick history of the cloud
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-<p>Around the year 2000, the Amazon.com team centralized their IT platform across the company so instead of each team running and hosting its own servers, they would get them from a centralized platform.</p>
-<p>Over the next few years, Amazon execs realized that just like this service was valuable to other <em>teams</em> at Amazon, other <em>organizations</em> would also be interested in renting server capacity from AWS rather than running it themselves. They launched Amazon Web Services (AWS) in 2006. It wasn’t the first cloud service, but it was the first one to get major commercial traction.</p>
-</div>
-</div>
-<p>Before we boost the cloud too much, let’s do some hype-busting.</p>
-<p>Over the last decade, you’d often hear people say that they were going to save money by moving to the cloud. Often, the explanation was that the flexibility of the cloud was going to enable dynamic autoscaling of server capacity. So even if they paid a little more per hour, they were going to save so much by turning capacity way down at night that it’d work out in their favor.</p>
-<p>It turns out that even with the cloud, the engineering needed to make autoscaling happen this smoothly is extremely hard and only the most sophisticated IT/Admin organizations have achieved anything close to this goal.</p>
-<p>While there might be individual examples to the contrary, I think it’s safe to say this hasn’t materialized, and most organizations don’t save money by moving to the cloud.</p>
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-On (not) saving money in the cloud
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-<p>It’s hard to prove that any particular organization lost money in a cloud migration, but there’s a reason why AWS was only 13% of Amazon’s revenue in 2021, but a whopping 74% of the company’s profits for that year.<a href="#fn1" class="footnote-ref" id="fnref1" role="doc-noteref"><sup>1</sup></a></p>
-<p>Additionally, an a16z report found that the total cost of ownership (TCO) – including staffing – for bringing server workloads in-house for large, established companies like Dropbox, was only 1/3 to 1/2 the amount of running the same workloads in a public cloud provider.<a href="#fn2" class="footnote-ref" id="fnref2" role="doc-noteref"><sup>2</sup></a></p>
-<p>There’s a reason why there’s a small consulting industry solely focused on saving money on AWS bills.</p>
-</div>
-</div>
-<p>So let’s assume your organization isn’t going to beat the curve at autoscaling all their cloud services. Why should you move to the cloud?</p>
-<p>The first – and most important – reason is flexibility. While the cloud may be more expensive than hosting servers on-prem, it’s way more flexible. In an on-prem-only world, your organization has to buy and host all the server capacity it needs. But in a world with cloud resources, you can have a new server up or rescale an existing one. This is an incredible ability for a small organization, an organization with unpredictable workloads, or for temporary workloads.<a href="#fn3" class="footnote-ref" id="fnref3" role="doc-noteref"><sup>3</sup></a></p>
-<p>The second reason is about IT team scope and competency. Say you work for a small organization with only a few employees. In the pre-cloud world, you couldn’t run a server until you hired or contracted with someone to run a server rack for you.</p>
-<p>In today’s world, all you need to do is feel comfortable working on the command line – and you can get a server of your own.</p>
-<p>It’s also worth considering the incentives of IT/Admin teams and professionals. IT/Admin teams tend to be stretched really thin, so the chance to offload a major component of their work – physically hosting servers – is really appealing. Moreover, as IT/Admin professionals have observed the world moving in a cloud-first direction, the resume-building incentives of individual professionals have moved towards the clouds. When I’m looking for my next job, it’s probably going to be way more valuable to say that I’m an expert at working with cloud-based Kubernetes clusters than saying that I’m really good at managing physical servers.</p>
-<section id="layers-of-cloud-services" class="level2" data-number="10.1">
-<h2 data-number="10.1" class="anchored" data-anchor-id="layers-of-cloud-services"><span class="header-section-number">10.1</span> Layers of cloud services</h2>
-<p>While the basic premise of the cloud is <em>rent a server</em>, there are layers and layers of services on top of that basic premise. Depending on your organization’s needs, it may make sense to rent a very basic service, or a higher level one.</p>
-<p>Let’s talk about cakes to help make the levels clear. This year, I’m planning to bake and decorate a beautiful cake for my friend’s birthday. It’s going to be a round layer cake with white frosting, and it’s going to say “Happy Birthday!” in teal with giant lavender frosting rosettes.</p>
-<p>Now that I’ve decided what I’m making, I have a few different options for how I get there. If I’m a real DIY kind of person, I could buy all the ingredients from the grocery store and make everything from scratch. Or I could buy a cake mix – reducing the likelihood I’ll buy the wrong ingredients or end up with unnecessary leftovers. Or maybe I don’t want to bake at all – I could just buy a premade cake already covered in white frosting and just do the writing and the rosettes.</p>
-<p>The choice of how much to DIY my friend’s birthday cake and how much to get from a bakery is very much akin to your choices when buying server capacity from the cloud.</p>
-<p>TODO: Image of getting cake w/ IaaS, PaaS, SaaS</p>
-<p>In the US, a huge fraction of server workloads run on servers rented from one of the “big three clouds” – Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). There are also numerous smaller cloud providers, many of which target more specific use cases.</p>
-<p>It’s totally possible to just rent the raw ingredients from these cloud providers – they’ll happily rent you the most basic cloud services like servers, networking, and storage and let you put them together yourself. This kind of cloud service – the equivalent of baking from scratch – is called <em>Infrastructure as a Service</em> (IaaS, pronounced <em>eye-az</em>).</p>
-<p>But then I’m responsible for managing all of the reproducibility stack – I have to make sure the servers are up to date with new operating systems and security patches, while also ensuring there are modern versions of R and Python on the system, and making sure there are RStudio and Jupyter Notebooks present.</p>
-<p>But just as you might not want to have to buy eggs, milk, and sugar just to end up with a pretty cake, IT/Admin organizations are increasingly taking advantage of the cloud equivalent of cake mixes and premade blank sheet cakes.</p>
-<p>If I want to offload more of the work, I can think about a Platform as a Service (PaaS – pronounced pass) solution. This would give me the ability to somehow define an environment and send it somewhere to run without worrying about the underlying servers. For example, I might want to build a docker container with Python and Jupyter Notebook and host it somewhere that autoscales for the number of users and the amount of other resources needed.</p>
-<p>There are a bunch of different entities you can run in this way, and services to match each. For example, if you want to run a general app, you can use something like AWS’s Elastic Beanstalk to run a user-facing app that dynamically scales (TODO: Azure/GCP equivalents), if you want to run a container, you might use XXXX, and if you want to get a Kubernetes cluster as a service, you might use XXXX. If you want to just run a function, there’s always AWS Lambda.</p>
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-Caution
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-<p>I am not recommending you run a data science workbench on a service like Elastic Beanstalk. This actually tends not to work very well, for reasons we’ll get into in a bit.</p>
-</div>
-</div>
-<p>If I want to go one level more abstracted, I might want to go with a Software as a Service (SaaS - pronounced <em>sass</em>) solution. This would be something like one of the cloud providers hosted machine learning environment where you can train, deploy, and monitor machine learning models. AWS has SageMaker, Azure has Azure Machine Learning, and GCP has Vertex AI. And there are organizations that host popular data science tools like Posit.cloud and Saturn Cloud that you can use.</p>
-<p>Sometimes you’ll hear people describe PaaS or SaaS solutions called “going serverless”.</p>
-<p>The first thing to understand about serverless computing is that <em>there is no such thing as serverless computing</em>.</p>
-<p>Every bit of cloud computation runs on a server - the question is whether <strong>you</strong> have to deal with the server or if you just deal with a preconfigured service.</p>
-<p>In this book, we’ll be working exclusively with IaaS services – taking the most basic services and building up a working data science environment. Once you understand how these pieces fit together, you’ll be in a much better place if it turns out your organization wants to leverage more abstracted versions of those services.</p>
-</section>
-<section id="common-services-for-data-science-usage" class="level2" data-number="10.2">
-<h2 data-number="10.2" class="anchored" data-anchor-id="common-services-for-data-science-usage"><span class="header-section-number">10.2</span> Common services for data science usage</h2>
-<p>If you’re not familiar with cloud provider terminology, it can be very hard to tell what service you might need from a cloud provider, and they don’t really help the matter. It’s very common (especially in AWS) to have many different services that fulfill similar needs, and it can be really hard to concretely tell the difference.</p>
-<p>Making the issue even more difficult, many companies go out of their way to make their services sound grand and important and don’t just say, “this is a ___ you can rent”.</p>
-<p>It’s helpful to keep in mind that at the very bottom, all you’re doing is renting servers and storage and managing networking and permissions for the servers and storage. Every other service is just a combination of server, storage, networking, and permissions that comes with software pre-installed or configured to make your life easier.<a href="#fn4" class="footnote-ref" id="fnref4" role="doc-noteref"><sup>4</sup></a></p>
-<p>We’re going to talk through some of the basic services that are offered by each of the three major cloud platforms.</p>
-<div class="callout callout-style-default callout-note callout-titled">
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-Cloud service naming
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-<p>Azure and GCP tend to name their offerings pretty literally, while AWS chooses cutesy names that have, at best, a tangential relationship to the task at hand. I’m going to try to name the services for each of the purposes I’m talking about, but it’s worth noting that feature sets aren’t exactly parallel across cloud providers.</p>
-<p>This makes AWS names a little harder to learn, but much easier to recall once you’ve learned them. In this section – contrary to standard practice – I’m going to use the common abbreviated names for AWS services and put the full name in parentheses as these are just trivia.</p>
-</div>
-</div>
-<p>Remember, at the bottom of all cloud services are servers and each of cloud service provider has a service that is “just rent me a server”. AWS has EC2 (Elastic Cloud Compute) and Azure has Azure VMs, and Google has Google Compute Engine.</p>
-<p>Along with servers, there are two main kinds of storage you’ll rent. The first is file storage, where you’ll store things in a file directory like on your laptop. These are AWS’s EBS (Elastic Block Store), Azure Managed Disk, and Google Persistent Disk.</p>
-<p>The major cloud providers all also have blob (Binary Large Object) storage. Blob storage allows you to store individual objects somewhere and recall them to any other machine that has access to the blob store. The major blob stores are AWS Simple Storage Service (S3), Azure Blob Storage, and Google Cloud Storage.</p>
-<p>There are also two important networking services for each of the clouds – a way to make a private network and a way to do DNS routing. If you don’t know what these mean, there will be a lot more detail in <a href="3-3-networking.html">Chapter&nbsp;<span>12</span></a>. For now, it’s enough to know that private networking is done in AWS’s VPC (Virtual Private Cloud), Azure’s Virtual Network, and Google’s Virtual Private Cloud. DNS is done in AWS’s Route 53, Azure DNS, and Google Cloud DNS.</p>
-<p>Once you’ve got all this stuff up and running, you need to make sure that permissions are set in the right way. AWS has IAM (Identity and Access Management), Azure has Azure Active Directory, and Google has Identity Access Management.</p>
-<p>Now, there are a variety of things you might want to do past these basic tasks of server, storage, networking, and access management. Here are a few more services you’ll likely hear about over time.</p>
-<table class="table">
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-<th>Service</th>
-<th>AWS</th>
-<th>Azure</th>
-<th>GCP</th>
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-<td>Kubernetes cluster</td>
-<td>EKS (Elastic Kubernetes Service)</td>
-<td>AKS (Azure Kubernetes Service)</td>
-<td>GKE (Google Kubernetes Engine)</td>
-</tr>
-<tr class="even">
-<td>Run a function as an API</td>
-<td>Lambda</td>
-<td>Azure Functions</td>
-<td>Google Cloud Functions</td>
-</tr>
-<tr class="odd">
-<td>Database</td>
-<td>RDS/Redshift<a href="#fn5" class="footnote-ref" id="fnref5" role="doc-noteref"><sup>5</sup></a></td>
-<td>Azure Database</td>
-<td>Google Cloud SQL</td>
-</tr>
-<tr class="even">
-<td>ML Platform</td>
-<td>SageMaker</td>
-<td>Azure ML</td>
-<td>Vertex AI</td>
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-</table>
-</section>
-<section id="comprehension-questions" class="level2" data-number="10.3">
-<h2 data-number="10.3" class="anchored" data-anchor-id="comprehension-questions"><span class="header-section-number">10.3</span> Comprehension Questions</h2>
-<ol type="1">
-<li>What is the difference between PaaS, IaaS, and SaaS? What’s an example of each that you’re familiar with?</li>
-<li>What are the names for AWS’s services for: renting a server, file system storage, blob storage</li>
-</ol>
-</section>
-<section id="lab-intro-to-aws" class="level2" data-number="10.4">
-<h2 data-number="10.4" class="anchored" data-anchor-id="lab-intro-to-aws"><span class="header-section-number">10.4</span> Lab: Intro to AWS</h2>
-<p>Welcome to the lab!</p>
-<p>The point of these exercises is to get you hands on with running servers and get you practicing the things you’re learning in the rest of the book.</p>
-<p>If you walk through the labs sequentially, you’ll end up with a working data science workbench. It won’t suffice for any enterprise-level requirements, but it’ll be secure enough for a hobby project or even a small team.</p>
-<p>These days most people are using servers from a cloud provider. We’re going to use AWS, as they’re by far the biggest cloud provider and the one you’re most likely to run into in the real world.</p>
-<p>At a high level, you can do all of this with any cloud provider. Feel free to try if you prefer Azure or GCP, but the details on how to get started and service names will be different.</p>
-<p>In the lab for this chapter, we’re going to get you up and running with an AWS account and show you how to manage, start, and stop EC2 instances in AWS.</p>
-<p>The server we’ll stand up will be from AWS’s <em>free tier</em> – so there will be no cost involved as long as you haven’t used up all your AWS free tier credits before now.</p>
-<p>For AWS things, I’m going to tell you what to do…but not the exact buttons, as AWS frequently changes the interface and this will almost certainly be out-of-date by the time you read it. The high level steps won’t change though.</p>
-<p>Throughout the lab, we’re going to go step by step through getting things done. If you know how to do any of the steps, I’d recommend you at least skim the step for any important details.</p>
-<section id="stand-up-an-ec2-instance" class="level3" data-number="10.4.1">
-<h3 data-number="10.4.1" class="anchored" data-anchor-id="stand-up-an-ec2-instance"><span class="header-section-number">10.4.1</span> Stand up an EC2 instance</h3>
-<section id="step-1-login-to-the-aws-console" class="level4" data-number="10.4.1.1">
-<h4 data-number="10.4.1.1" class="anchored" data-anchor-id="step-1-login-to-the-aws-console"><span class="header-section-number">10.4.1.1</span> Step 1: Login to the AWS Console</h4>
-<p>We’re going to start by logging into AWS.</p>
-<div class="callout callout-style-default callout-note callout-titled">
-<div class="callout-header d-flex align-content-center">
-<div class="callout-icon-container">
-<i class="callout-icon"></i>
-</div>
-<div class="callout-title-container flex-fill">
-Note
-</div>
-</div>
-<div class="callout-body-container callout-body">
-<p>An AWS account is separate from an Amazon account for ordering stuff online and watching movies. If you’ve never created an account for AWS in particular, you’ll have to make an account.</p>
-</div>
-</div>
-<p>Start by signing in at <a href="https://aws.amazon.com" class="uri">https://aws.amazon.com</a>. You most likely haven’t created an IAM account and should just login as root.</p>
-<p>Once you’ve logged in, you’ll be confronted by the AWS console. There are a ton of things here – feel free to poke around if you want – come back to continue when you’re ready.</p>
-</section>
-<section id="step-2-stand-up-an-instance" class="level4" data-number="10.4.1.2">
-<h4 data-number="10.4.1.2" class="anchored" data-anchor-id="step-2-stand-up-an-instance"><span class="header-section-number">10.4.1.2</span> Step 2: Stand up an instance</h4>
-<p>AWS’s most basic “rent a server by the hour” service is called EC2 (Elastic Cloud Compute).</p>
-<p>There are five things we have to configure in the process of launching the server. I’ll give you advice on each of them. If I don’t mention it here, feel free to stick with defaults.</p>
-<section id="name-tags" class="level5" data-number="10.4.1.2.1">
-<h5 data-number="10.4.1.2.1" class="anchored" data-anchor-id="name-tags"><span class="header-section-number">10.4.1.2.1</span> Name + Tags</h5>
-<p>The first choice is instance <strong>name and tags</strong>. They aren’t required, but I’d recommend you name the server something like <code>do4ds-lab</code> so you can remember what this server is later.</p>
-</section>
-<section id="image" class="level5" data-number="10.4.1.2.2">
-<h5 data-number="10.4.1.2.2" class="anchored" data-anchor-id="image"><span class="header-section-number">10.4.1.2.2</span> Image</h5>
-<p>Next, you’ll have to choose the <strong>image</strong>. An image is a snapshot of a system and serves as the starting point for your server. Images can range from just a bare operating system to a running RStudio instance that’s paused in between two computations.</p>
-<p>All clouds have the concept of images. AWS calls their’s <em>Amazon Machine Images</em> or <em>AMIs</em>. Some images are free and some are paid.</p>
-<p>Since we’re going to work on configuring the server from the ground up, we’re going to choose an AMI that’s just the operating system. For the lab, let’s use Ubuntu Server LTS 22.04 image. It should say <em>free tier eligible</em>.</p>
-<div class="callout callout-style-default callout-note callout-titled">
-<div class="callout-header d-flex align-content-center">
-<div class="callout-icon-container">
-<i class="callout-icon"></i>
-</div>
-<div class="callout-title-container flex-fill">
-Note
-</div>
-</div>
-<div class="callout-body-container callout-body">
-<p>If you want to use a different operating system, that’s fine. For the purpose of being able to follow along with this lab, I’d recommend using Ubuntu 22.04.</p>
-<p>If you happen to be reading this after 2026 or so, there will be newer operating systems. A newer version of Ubuntu should work very similarly for the purposes of this lab.</p>
-</div>
-</div>
-</section>
-<section id="instance-type" class="level5" data-number="10.4.1.2.3">
-<h5 data-number="10.4.1.2.3" class="anchored" data-anchor-id="instance-type"><span class="header-section-number">10.4.1.2.3</span> Instance Type</h5>
-<p>You’ll have to choose an <strong>Instance Type</strong>. In AWS, there are two components to instance type – the <em>family</em> and the <em>size</em>. The family is the category of server that you’re using. In AWS, families are denoted by letters and numbers, so there are T2s and T3s, C4s, R5s, and many more.</p>
-<p>Within each family, there are different sizes. The sizes availble vary by the family, but generally range from <em>nano</em> to multiples of <em>xlarge</em> like <em>24xlarge</em>.</p>
-<p>For now, I’d recommend you get the largest server that is free tier eligible, which is a <em>t2.micro</em> with 1 CPU and 1 Gb of memory as of this writing.</p>
-<div class="callout callout-style-default callout-note callout-titled">
-<div class="callout-header d-flex align-content-center">
-<div class="callout-icon-container">
-<i class="callout-icon"></i>
-</div>
-<div class="callout-title-container flex-fill">
-Server sizing for the lab
-</div>
-</div>
-<div class="callout-body-container callout-body">
-<p>A <em>t2.micro</em> with 1 CPU and 1 Gb of memory is a very small server. For example, your laptop probably has at least 8 CPUs and 8 Gb of memory.</p>
-<p>If all you’re doing is walking through the lab, it should be sufficient, but if you actually want to do any data science work, you’ll need a substantially larger server.</p>
-<p>If you want to pick a server for actual data science work, there’s lots of advice on how to choose in <a href="3-6-servers.html">Chaper&nbsp;<span>15</span></a>.</p>
-</div>
-</div>
-</section>
-<section id="keypair" class="level5" data-number="10.4.1.2.4">
-<h5 data-number="10.4.1.2.4" class="anchored" data-anchor-id="keypair"><span class="header-section-number">10.4.1.2.4</span> Keypair</h5>
-<p>Next, you’ll need to make sure you have a <strong>keypair</strong>. A keypair is a special kind of SSH key that’s only valid for a particular server.</p>
-<p>If you aren’t sure what that means, I’d recommend you check out <a href="../sec2/2-1-cmd-line.html">Chapter&nbsp;<span>6</span></a>.</p>
-<p>Even if you have a keypair you already use, I’d suggest creating a new one and naming it <code>do4ds-lab-key</code>. Download the <code>pem</code> version of your key.</p>
-<p>I’ll use that name throughout the lab, so you can just copy commands straight from this book if you use the same name.</p>
-<p>I’d recommend creating a directory for this lab, perhaps something like <code>do4ds-lab</code> and putting your keypair there. If you’re not going to do that, just make sure you keep track of where you downloaded it.</p>
-</section>
-<section id="storage" class="level5" data-number="10.4.1.2.5">
-<h5 data-number="10.4.1.2.5" class="anchored" data-anchor-id="storage"><span class="header-section-number">10.4.1.2.5</span> Storage</h5>
-<p>For storage, you should bump it up to something more than 8 Gb. As of this writing, you can get 30 Gb under the free tier. I’d recommend at least 16 Gb, but feel free to go bigger if you wish.</p>
-</section>
-</section>
-<section id="step-3-start-your-server" class="level4" data-number="10.4.1.3">
-<h4 data-number="10.4.1.3" class="anchored" data-anchor-id="step-3-start-your-server"><span class="header-section-number">10.4.1.3</span> Step 3: Start your Server</h4>
-<p>If you followed these instructions, the summary on the right side should look something like this:</p>
-<div class="quarto-figure quarto-figure-center">
-<figure class="figure">
-<p><img src="images/instance-summary.png" class="img-fluid figure-img" width="362"></p>
-</figure>
-</div>
-<p>Click <code>Launch Instance</code>. AWS is now creating a virtual server <em>just for you</em>.</p>
-<p>If you go back to the EC2 page and click on <code>Instances</code> you can see your instance as it comes up. You may need to remove the filter for <code>State: Running</code> since it’ll take a few moments to be <code>Running</code>.</p>
-</section>
-<section id="step-4-grab-the-address-of-your-server" class="level4" data-number="10.4.1.4">
-<h4 data-number="10.4.1.4" class="anchored" data-anchor-id="step-4-grab-the-address-of-your-server"><span class="header-section-number">10.4.1.4</span> Step 4: Grab the address of your server</h4>
-<p>If you click on the actual instance ID in blue, you can see all the details of your server.</p>
-<p>Wait for a few moments for the instance state to transition to <code>Running</code>.</p>
-<p>Once the instance is up, you’ll be able to see the instance ID and public IP addresses, which were auto-assigned.</p>
-<p>Copy the Public IPv4 DNS address , which starts with <code>ec2-</code> and ends with <code>amazonaws.com</code>. That little icon on the left of the address copies it.</p>
-<div class="callout callout-style-default callout-tip callout-titled">
-<div class="callout-header d-flex align-content-center">
-<div class="callout-icon-container">
-<i class="callout-icon"></i>
-</div>
-<div class="callout-title-container flex-fill">
-Set a Server Address Variable
-</div>
-</div>
-<div class="callout-body-container callout-body">
-<p>In the rest of the labs in this book, I’m going to write the commands using the bash variable <code>SERVER_ADDRESS</code>. That means that if you create that variable, you’ll be able to just copy the commands out of the book.</p>
-<p>For example, as I write this, my server has the address <code>ec2-54-159-134-39.compute-1.amazonaws.com</code>. So would set my server address variable with <code>SERVER_ADDRESS=ec2-54-159-134-39.compute-1.amazonaws.com</code>.</p>
-<p>If you’re used to R or Python, where it’s best practice to put spaces around <code>=</code>, notice that assigning variables in bash <em>requires</em> no spaces around <code>=</code>.</p>
-</div>
-</div>
-</section>
-<section id="step-5-stop-the-server" class="level4" data-number="10.4.1.5">
-<h4 data-number="10.4.1.5" class="anchored" data-anchor-id="step-5-stop-the-server"><span class="header-section-number">10.4.1.5</span> Step 5: Stop the Server</h4>
-<p>Whenever you’re stopping for the day, you may want to suspend your server so you’re not paying for it overnight or using up your free tier hours. You can suspend an instance in the state it’s in so it can be restarted later.</p>
-<p>If you’re storing a lot of data with your instance, it may not be free – but it is quite cheap. In the free tier, a suspended instance should be free for some time.</p>
-<p>Whenever you want to suspend your instance, go to the EC2 page for your server. Under the <code>Instance State</code> drop down in the upper right, choose <code>Stop Instance</code>.</p>
-<p>After a couple minutes the instance will stop. Before you come back to the next lab, you’ll need to start the instance back up so it’s ready to go.</p>
-<div class="callout callout-style-default callout-note callout-titled">
-<div class="callout-header d-flex align-content-center">
-<div class="callout-icon-container">
-<i class="callout-icon"></i>
-</div>
-<div class="callout-title-container flex-fill">
-Note
-</div>
-</div>
-<div class="callout-body-container callout-body">
-<p>If you stop your server, the server address will change and you’ll have to use the new one. In <a href="3-4-dns.html">Chapter&nbsp;<span>13</span></a>, we’ll get into getting a stable IP address and URL for the server.</p>
-</div>
-</div>
-<p>If you want to completely delete the instance at any point, you can choose to <code>Terminate Instance</code> from that same <code>Instance State</code> dropdown.</p>
-</section>
-</section>
-<section id="step-6-put-the-penguins-data-and-model-in-s3" class="level3" data-number="10.4.2">
-<h3 data-number="10.4.2" class="anchored" data-anchor-id="step-6-put-the-penguins-data-and-model-in-s3"><span class="header-section-number">10.4.2</span> Step 6: Put the penguins data and model in S3</h3>
-<p>As discussed in <a href="../sec1/1-3-data-access.html">Chapter&nbsp;<span>3</span></a>, we’re going to want to put our data and our model somewhere other than on our local machine.</p>
-<p>While this data doesn’t get updated, you might want to be able to update the data and the model periodically.</p>
-<p>A bucket is a great place to store non-tabular data like a model. AWS’s bucket storage is called S3. You’ll probably find yourself using it a lot. It can also store flat files to be used by DuckDB.</p>
-<p>For the model, <code>{vetiver}</code> interfaces with another package called <code>{pins}</code> which makes it easy to store data in a variety of backends, including an s3 bucket.</p>
-<p>First, you’ll need to create an S3 bucket in the AWS console. Give it a name that’s descriptive and memorable – it will also have to be unique. I named mine <code>do4ds-lab</code>. You’ll have to choose the AWS region where your bucket is located – take note of this.</p>
-<p>Now, let’s change our code to write to the S3 bucket we created. Vetiver makes this very easy. All you have to do to move the model into S3 is to change the line that creates the bucket in your code so instead of using a <code>board_temp</code>, it uses <code>board_s3</code>.</p>
-<div class="code-with-filename">
-<div class="code-with-filename-file">
-<pre><strong>model.qmd</strong></pre>
-</div>
-<div class="sourceCode" id="cb1" data-startfrom="47"><pre class="sourceCode numberSource python number-lines code-with-copy"><code class="sourceCode python" style="counter-reset: source-line 46;"><span id="cb1-47"><a href="#cb1-47"></a><span class="im">from</span> vetiver <span class="im">import</span> VetiverModel</span>
-<span id="cb1-48"><a href="#cb1-48"></a>v <span class="op">=</span> VetiverModel(model, model_name<span class="op">=</span><span class="st">'penguin_model'</span>, prototype_data<span class="op">=</span>X)</span>
-<span id="cb1-49"><a href="#cb1-49"></a>```</span>
-<span id="cb1-50"><a href="#cb1-50"></a></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-</div>
-<p>That line will now become</p>
-<div class="code-with-filename">
-<div class="code-with-filename-file">
-<pre><strong>model.qmd</strong></pre>
-</div>
-<div class="sourceCode" id="cb2" data-startfrom="64"><pre class="sourceCode numberSource python number-lines code-with-copy"><code class="sourceCode python" style="counter-reset: source-line 63;"><span id="cb2-64"><a href="#cb2-64"></a><span class="im">from</span> vetiver <span class="im">import</span> VetiverAPI</span>
-<span id="cb2-65"><a href="#cb2-65"></a>app <span class="op">=</span> VetiverAPI(v, check_prototype <span class="op">=</span> <span class="va">True</span>)</span>
-<span id="cb2-66"><a href="#cb2-66"></a>```</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-</div>
-<p>Now, if you try this line in your code, it won’t work. Why? Because of authentication. The bucket we’re using isn’t public and AWS needs to know that we’re actually allowed to access it.</p>
-<p>In this case, we’re going to use <a href="@sec-env-vars">environment variables</a> to give access to the S3 bucket. If you play around a little, you’ll discover that <code>{pins}</code> does authentication via the <code>s3fs</code> package, which can do authentication in several different ways. We’re going to use environment variables because they work nicely locally and from GitHub Actions.</p>
-<p>The 3 environment variables are <code>AWS_ACCESS_KEY_ID</code>, <code>AWS_SECRET_ACCESS_KEY</code>, and <code>AWS_REGION</code>. You can get the access key and secret access key from the AWS console.</p>
-<p>Once you’ve done that, create a file in the directory where your project is called <code>.env</code>. In that file you’ll put the access keys, along with the AWS region where you put your bucket.</p>
-<p>It’ll look something like this<a href="#fn6" class="footnote-ref" id="fnref6" role="doc-noteref"><sup>6</sup></a></p>
-<div class="code-with-filename">
-<div class="code-with-filename-file">
-<pre><strong>.env</strong></pre>
-</div>
-<div class="sourceCode" id="cb3"><pre class="sourceCode numberSource yaml number-lines code-with-copy"><code class="sourceCode yaml"><span id="cb3-1"><a href="#cb3-1"></a><span class="at">AWS_ACCESS_KEY_ID=AJAASJKD88ALLKAIS8A</span></span>
-<span id="cb3-2"><a href="#cb3-2"></a><span class="at">AWS_SECRET_ACCESS_KEY=0JAJSduasdjkASDLISjkasd8AD78</span></span>
-<span id="cb3-3"><a href="#cb3-3"></a><span class="at">AWS_REGION=us-east-1</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-</div>
-<p>Now, add a block to the code that loads in the environment variables.</p>
-<div class="code-with-filename">
-<div class="code-with-filename-file">
-<pre><strong>model.qmd</strong></pre>
-</div>
-<div class="sourceCode" id="cb4" data-startfrom="56"><pre class="sourceCode numberSource python number-lines code-with-copy"><code class="sourceCode python" style="counter-reset: source-line 55;"><span id="cb4-56"><a href="#cb4-56"></a></span>
-<span id="cb4-57"><a href="#cb4-57"></a>model_board <span class="op">=</span> board_folder(<span class="st">"/data/model"</span>, allow_pickle_read <span class="op">=</span> <span class="va">True</span>)</span>
-<span id="cb4-58"><a href="#cb4-58"></a>vetiver_pin_write(model_board, v)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-</div>
-<p>If these variables are in the environment, the call to <code>board_s3</code> should just work locally.</p>
-<p>We have one more step to make this work so that the model can also be written from GitHub actions. GitHub Actions needs to know how to access those environment variables too.</p>
-<p>So in the <code>Render and Publish</code> step, we’re going to declare those variables as well as environment variables.</p>
-<p>Once you’re done, that section of the <code>publish.yml</code> should look something like this.</p>
-<div class="code-with-filename">
-<div class="code-with-filename-file">
-<pre><strong>.github/workflows/publish.yml</strong></pre>
-</div>
-<div class="sourceCode" id="cb5" data-start_line="45" data-end_line="49"><pre class="sourceCode numberSource yaml number-lines code-with-copy"><code class="sourceCode yaml"><span id="cb5-1"><a href="#cb5-1"></a><span class="fu">on</span><span class="kw">:</span></span>
-<span id="cb5-2"><a href="#cb5-2"></a><span class="at">  </span><span class="fu">workflow_dispatch</span><span class="kw">:</span></span>
-<span id="cb5-3"><a href="#cb5-3"></a><span class="at">  </span><span class="fu">push</span><span class="kw">:</span></span>
-<span id="cb5-4"><a href="#cb5-4"></a><span class="at">    </span><span class="fu">branches</span><span class="kw">:</span><span class="at"> main</span></span>
-<span id="cb5-5"><a href="#cb5-5"></a></span>
-<span id="cb5-6"><a href="#cb5-6"></a><span class="fu">name</span><span class="kw">:</span><span class="at"> Quarto Publish</span></span>
-<span id="cb5-7"><a href="#cb5-7"></a></span>
-<span id="cb5-8"><a href="#cb5-8"></a><span class="fu">jobs</span><span class="kw">:</span></span>
-<span id="cb5-9"><a href="#cb5-9"></a><span class="at">  </span><span class="fu">build-deploy</span><span class="kw">:</span></span>
-<span id="cb5-10"><a href="#cb5-10"></a><span class="at">    </span><span class="fu">runs-on</span><span class="kw">:</span><span class="at"> ubuntu-latest</span></span>
-<span id="cb5-11"><a href="#cb5-11"></a><span class="at">    </span><span class="fu">permissions</span><span class="kw">:</span></span>
-<span id="cb5-12"><a href="#cb5-12"></a><span class="at">      </span><span class="fu">contents</span><span class="kw">:</span><span class="at"> write</span></span>
-<span id="cb5-13"><a href="#cb5-13"></a><span class="at">    </span><span class="fu">steps</span><span class="kw">:</span></span>
-<span id="cb5-14"><a href="#cb5-14"></a><span class="at">      </span><span class="kw">-</span><span class="at"> </span><span class="fu">name</span><span class="kw">:</span><span class="at"> Check out repository</span></span>
-<span id="cb5-15"><a href="#cb5-15"></a><span class="at">        </span><span class="fu">uses</span><span class="kw">:</span><span class="at"> actions/checkout@v2</span></span>
-<span id="cb5-16"><a href="#cb5-16"></a></span>
-<span id="cb5-17"><a href="#cb5-17"></a><span class="at">      </span><span class="kw">-</span><span class="at"> </span><span class="fu">name</span><span class="kw">:</span><span class="at"> Set up Quarto</span></span>
-<span id="cb5-18"><a href="#cb5-18"></a><span class="at">        </span><span class="fu">uses</span><span class="kw">:</span><span class="at"> quarto-dev/quarto-actions/setup@v2</span></span>
-<span id="cb5-19"><a href="#cb5-19"></a></span>
-<span id="cb5-20"><a href="#cb5-20"></a><span class="at">      </span><span class="kw">-</span><span class="at"> </span><span class="fu">name</span><span class="kw">:</span><span class="at"> Install R</span></span>
-<span id="cb5-21"><a href="#cb5-21"></a><span class="at">        </span><span class="fu">uses</span><span class="kw">:</span><span class="at"> r-lib/actions/setup-r@v2</span></span>
-<span id="cb5-22"><a href="#cb5-22"></a><span class="at">        </span><span class="fu">with</span><span class="kw">:</span></span>
-<span id="cb5-23"><a href="#cb5-23"></a><span class="at">          </span><span class="fu">r-version</span><span class="kw">:</span><span class="at"> </span><span class="st">'4.2.0'</span></span>
-<span id="cb5-24"><a href="#cb5-24"></a><span class="at">          </span><span class="fu">use-public-rspm</span><span class="kw">:</span><span class="at"> </span><span class="ch">true</span></span>
-<span id="cb5-25"><a href="#cb5-25"></a></span>
-<span id="cb5-26"><a href="#cb5-26"></a><span class="at">      </span><span class="kw">-</span><span class="at"> </span><span class="fu">name</span><span class="kw">:</span><span class="at"> Setup renv and install packages</span></span>
-<span id="cb5-27"><a href="#cb5-27"></a><span class="at">        </span><span class="fu">uses</span><span class="kw">:</span><span class="at"> r-lib/actions/setup-renv@v2</span></span>
-<span id="cb5-28"><a href="#cb5-28"></a><span class="at">        </span><span class="fu">with</span><span class="kw">:</span></span>
-<span id="cb5-29"><a href="#cb5-29"></a><span class="at">          </span><span class="fu">cache-version</span><span class="kw">:</span><span class="at"> </span><span class="dv">1</span></span>
-<span id="cb5-30"><a href="#cb5-30"></a><span class="at">        </span><span class="fu">env</span><span class="kw">:</span></span>
-<span id="cb5-31"><a href="#cb5-31"></a><span class="at">          </span><span class="fu">RENV_CONFIG_REPOS_OVERRIDE</span><span class="kw">:</span><span class="at"> https://packagemanager.rstudio.com/all/latest</span></span>
-<span id="cb5-32"><a href="#cb5-32"></a></span>
-<span id="cb5-33"><a href="#cb5-33"></a><span class="at">      </span><span class="kw">-</span><span class="at"> </span><span class="fu">name</span><span class="kw">:</span><span class="at"> Install Python and Dependencies</span></span>
-<span id="cb5-34"><a href="#cb5-34"></a><span class="at">        </span><span class="fu">uses</span><span class="kw">:</span><span class="at"> actions/setup-python@v4</span></span>
-<span id="cb5-35"><a href="#cb5-35"></a><span class="at">        </span><span class="fu">with</span><span class="kw">:</span></span>
-<span id="cb5-36"><a href="#cb5-36"></a><span class="at">          </span><span class="fu">python-version</span><span class="kw">:</span><span class="at"> </span><span class="st">'3.10'</span></span>
-<span id="cb5-37"><a href="#cb5-37"></a><span class="at">          </span><span class="fu">cache</span><span class="kw">:</span><span class="at"> </span><span class="st">'pip'</span></span>
-<span id="cb5-38"><a href="#cb5-38"></a><span class="at">      </span><span class="kw">-</span><span class="at"> </span><span class="fu">run</span><span class="kw">:</span><span class="at"> pip install jupyter</span></span>
-<span id="cb5-39"><a href="#cb5-39"></a><span class="at">      </span><span class="kw">-</span><span class="at"> </span><span class="fu">run</span><span class="kw">:</span><span class="at"> pip install -r requirements.txt</span></span>
-<span id="cb5-40"><a href="#cb5-40"></a></span>
-<span id="cb5-41"><a href="#cb5-41"></a><span class="at">      </span><span class="kw">-</span><span class="at"> </span><span class="fu">name</span><span class="kw">:</span><span class="at"> Render and Publish</span></span>
-<span id="cb5-42"><a href="#cb5-42"></a><span class="at">        </span><span class="fu">uses</span><span class="kw">:</span><span class="at"> quarto-dev/quarto-actions/publish@v2</span></span>
-<span id="cb5-43"><a href="#cb5-43"></a><span class="at">        </span><span class="fu">with</span><span class="kw">:</span></span>
-<span id="cb5-44"><a href="#cb5-44"></a><span class="at">          </span><span class="fu">target</span><span class="kw">:</span><span class="at"> gh-pages</span></span>
-<span id="cb5-45"><a href="#cb5-45"></a><span class="at">        </span><span class="fu">env</span><span class="kw">:</span></span>
-<span id="cb5-46"><a href="#cb5-46"></a><span class="at">          </span><span class="fu">GITHUB_TOKEN</span><span class="kw">:</span><span class="at"> ${{ secrets.GITHUB_TOKEN }}</span></span>
-<span id="cb5-47"><a href="#cb5-47"></a><span class="at">          </span><span class="fu">AWS_ACCESS_KEY_ID</span><span class="kw">:</span><span class="at"> ${{ secrets.AWS_ACCESS_KEY_ID }}</span></span>
-<span id="cb5-48"><a href="#cb5-48"></a><span class="at">          </span><span class="fu">AWS_SECRET_ACCESS_KEY</span><span class="kw">:</span><span class="at"> ${{ secrets.AWS_SECRET_ACCESS_KEY }}</span></span>
-<span id="cb5-49"><a href="#cb5-49"></a><span class="at">          </span><span class="fu">AWS_REGION</span><span class="kw">:</span><span class="at"> us-east-1</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-</div>
-<p>Now, unlike the <code>GITHUB_TOKEN</code> secret, which GitHub Actions automatically provides to itself, we’ll have to provide these secrets to the GitHub interface.As of this writing, you can provide them under the repository settings, secrets and variables, actions.</p>
-<p>The other thing you’ll need to do is to update the API to use the S3 pin. Luckily, this is very easy. Just update the script you used to build your <code>Dockerfile</code> so it pulls from the pin in the S3 bucket rather than the local folder.</p>
-<p>Now, the script to build the <code>Dockerfile</code> looks like this:</p>
-<div class="sourceCode" id="cb6" data-start_line="11" data-end_line="19"><pre class="sourceCode numberSource python number-lines code-with-copy"><code class="sourceCode python"><span id="cb6-1"><a href="#cb6-1"></a><span class="op">---</span></span>
-<span id="cb6-2"><a href="#cb6-2"></a>title: <span class="st">"Prepare Dockerfile"</span></span>
-<span id="cb6-3"><a href="#cb6-3"></a><span class="bu">format</span>:</span>
-<span id="cb6-4"><a href="#cb6-4"></a>  html:</span>
-<span id="cb6-5"><a href="#cb6-5"></a>    code<span class="op">-</span>fold: true</span>
-<span id="cb6-6"><a href="#cb6-6"></a><span class="op">---</span></span>
-<span id="cb6-7"><a href="#cb6-7"></a></span>
-<span id="cb6-8"><a href="#cb6-8"></a><span class="co">## Load Environment</span></span>
-<span id="cb6-9"><a href="#cb6-9"></a></span>
-<span id="cb6-10"><a href="#cb6-10"></a>```{python}</span>
-<span id="cb6-11"><a href="#cb6-11"></a><span class="im">from</span> dotenv <span class="im">import</span> load_dotenv</span>
-<span id="cb6-12"><a href="#cb6-12"></a></span>
-<span id="cb6-13"><a href="#cb6-13"></a>load_dotenv()</span>
-<span id="cb6-14"><a href="#cb6-14"></a></span>
-<span id="cb6-15"><a href="#cb6-15"></a><span class="im">from</span> pins <span class="im">import</span> board_s3</span>
-<span id="cb6-16"><a href="#cb6-16"></a><span class="im">from</span> vetiver <span class="im">import</span> vetiver_prepare_docker</span>
-<span id="cb6-17"><a href="#cb6-17"></a></span>
-<span id="cb6-18"><a href="#cb6-18"></a>board <span class="op">=</span> board_s3(<span class="st">"do4ds-lab"</span>, allow_pickle_read<span class="op">=</span><span class="va">True</span>)</span>
-<span id="cb6-19"><a href="#cb6-19"></a>vetiver_prepare_docker(board, <span class="st">"penguin_model"</span>)</span>
-<span id="cb6-20"><a href="#cb6-20"></a>```</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-<p>There are a variety of ways to put the data into S3 as well. I would recommend doing this if you are going to be working with data that will update. In fact, DuckDB allows you to directly interface with parquet files on S3.</p>
-
-
-</section>
-</section>
-<section id="footnotes" class="footnotes footnotes-end-of-document" role="doc-endnotes">
-<hr>
-<ol>
-<li id="fn1"><p>https://www.visualcapitalist.com/aws-powering-the-internet-and-amazons-profits/<a href="#fnref1" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
-<li id="fn2"><p>https://a16z.com/2021/05/27/cost-of-cloud-paradox-market-cap-cloud-lifecycle-scale-growth-repatriation-optimization/<a href="#fnref2" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
-<li id="fn3"><p>By temporary workloads, I mean for example the need for a very large server to run a particular machine learning model. This is <em>not</em> the autoscaling failure case, because you’re not expecting this server to turn itself on and off. Instead, you’d stand it up – run it for a few hours, days, or weeks while you’re using it, and then manually turn it off. This is super easy with a cloud server and very difficult in an on-prem world.<a href="#fnref3" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
-<li id="fn4"><p>There are also some wild services that do specific things, like let you rent you satellite ground station infrastructure or do Internet of Things (IoT) workloads. Those services are really cool, but so far outside the scope of this book that I’m fine with talking like they don’t exist.<a href="#fnref4" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
-<li id="fn5"><p>There are many others. These are just the most popular I’ve seen for data science use cases.<a href="#fnref5" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
-<li id="fn6"><p>Not my real access key or secret access key. Never share them.<a href="#fnref6" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
-</ol>
-</section>
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diff --git a/chapters/sec4/4-1-os-ds-in-ent.html b/chapters/sec3/3-1-os-ds-in-ent.html
similarity index 91%
rename from chapters/sec4/4-1-os-ds-in-ent.html
rename to chapters/sec3/3-1-os-ds-in-ent.html
index 010b51349..397215b45 100644
--- a/chapters/sec4/4-1-os-ds-in-ent.html
+++ b/chapters/sec3/3-1-os-ds-in-ent.html
@@ -7,7 +7,7 @@
 <meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes">
 
 
-<title>DevOps for Data Science - 16&nbsp; Open Source Data Science in the Enterprise</title>
+<title>DevOps for Data Science - 15&nbsp; Open Source Data Science in the Enterprise</title>
 <style>
 code{white-space: pre-wrap;}
 span.smallcaps{font-variant: small-caps;}
@@ -30,8 +30,8 @@
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+<link href="../../chapters/sec3/3-2-ent-networks.html" rel="next">
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+      <nav class="quarto-page-breadcrumbs" aria-label="breadcrumb"><ol class="breadcrumb"><li class="breadcrumb-item"><a href="../../chapters/sec3/3-0-sec-intro.html">Making it Enterprise-Grade</a></li><li class="breadcrumb-item"><a href="../../chapters/sec3/3-1-os-ds-in-ent.html"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></a></li></ol></nav>
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- <span class="menu-text"><span class="chapter-number">6</span>&nbsp; <span class="chapter-title">Opening the Command Line</span></span></a>
+  <a href="../../chapters/sec2/2-1-cloud.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">7</span>&nbsp; <span class="chapter-title">The Cloud</span></span></a>
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- <span class="menu-text"><span class="chapter-number">7</span>&nbsp; <span class="chapter-title">Using the Command Line</span></span></a>
+  <a href="../../chapters/sec2/2-2-cmd-line.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">8</span>&nbsp; <span class="chapter-title">Customizing the command line</span></span></a>
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- <span class="menu-text"><span class="chapter-number">8</span>&nbsp; <span class="chapter-title">Secure server connections with SSH</span></span></a>
+  <a href="../../chapters/sec2/2-3-linux.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">9</span>&nbsp; <span class="chapter-title">Intro to Linux Administration</span></span></a>
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- <span class="menu-text"><span class="chapter-number">9</span>&nbsp; <span class="chapter-title">Demystifying Docker</span></span></a>
+  <a href="../../chapters/sec2/2-4-app-admin.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Application administration</span></span></a>
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- <span class="menu-text">IT/Admin for Data Science</span></a>
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- <span class="menu-text"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Getting Started with the Cloud</span></span></a>
+  <a href="../../chapters/sec2/2-5-scale.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Server Resources and Scaling</span></span></a>
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-  </div>
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-  <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-3-networking.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-6-networking.html" class="sidebar-item-text sidebar-link">
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-  <a href="../../chapters/sec3/3-4-dns.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-7-dns.html" class="sidebar-item-text sidebar-link">
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-  <a href="../../chapters/sec3/3-5-ssl.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-8-ssl.html" class="sidebar-item-text sidebar-link">
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- <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Choosing the right server for you</span></span></a>
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+            <a href="../../chapters/sec3/3-0-sec-intro.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text">Making it Enterprise-Grade</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true" aria-label="Toggle section">
+          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-3" aria-expanded="true" aria-label="Toggle section">
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-      <ul id="quarto-sidebar-section-4" class="collapse list-unstyled sidebar-section depth1 show">  
+      <ul id="quarto-sidebar-section-3" class="collapse list-unstyled sidebar-section depth1 show">  
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-  <a href="../../chapters/sec4/4-1-os-ds-in-ent.html" class="sidebar-item-text sidebar-link active">
- <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></a>
+  <a href="../../chapters/sec3/3-1-os-ds-in-ent.html" class="sidebar-item-text sidebar-link active">
+ <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></a>
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- <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></a>
+  <a href="../../chapters/sec3/3-2-ent-networks.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></a>
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- <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></a>
+  <a href="../../chapters/sec3/3-3-auth.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></a>
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- <span class="menu-text"><span class="chapter-number">19</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></a>
+  <a href="../../chapters/sec3/3-4-ent-servers.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></a>
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-            <a class="sidebar-item-text sidebar-link text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-5" aria-expanded="true">
+            <a class="sidebar-item-text sidebar-link text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true">
  <span class="menu-text">Appendices</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-5" aria-expanded="true" aria-label="Toggle section">
+          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true" aria-label="Toggle section">
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-      <ul id="quarto-sidebar-section-5" class="collapse list-unstyled sidebar-section depth1 show">  
+      <ul id="quarto-sidebar-section-4" class="collapse list-unstyled sidebar-section depth1 show">  
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  <span class="menu-text"><span class="chapter-number">B</span>&nbsp; <span class="chapter-title">Lab Map</span></span></a>
   </div>
+</li>
+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/append/cheatsheets.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">C</span>&nbsp; <span class="chapter-title">Cheatsheets</span></span></a>
+  </div>
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@@ -330,23 +319,23 @@
     <h2 id="toc-title">Table of contents</h2>
    
   <ul>
-  <li><a href="#data-science-sandboxes" id="toc-data-science-sandboxes" class="nav-link active" data-scroll-target="#data-science-sandboxes"><span class="header-section-number">16.1</span> Data Science Sandboxes</a></li>
-  <li><a href="#devtestprod-for-admins" id="toc-devtestprod-for-admins" class="nav-link" data-scroll-target="#devtestprod-for-admins"><span class="header-section-number">16.2</span> Dev/Test/Prod for Admins</a></li>
-  <li><a href="#package-management-in-the-enterprise" id="toc-package-management-in-the-enterprise" class="nav-link" data-scroll-target="#package-management-in-the-enterprise"><span class="header-section-number">16.3</span> Package Management in the Enterprise</a>
+  <li><a href="#data-science-sandboxes" id="toc-data-science-sandboxes" class="nav-link active" data-scroll-target="#data-science-sandboxes"><span class="header-section-number">15.1</span> Data Science Sandboxes</a></li>
+  <li><a href="#devtestprod-for-admins" id="toc-devtestprod-for-admins" class="nav-link" data-scroll-target="#devtestprod-for-admins"><span class="header-section-number">15.2</span> Dev/Test/Prod for Admins</a></li>
+  <li><a href="#package-management-in-the-enterprise" id="toc-package-management-in-the-enterprise" class="nav-link" data-scroll-target="#package-management-in-the-enterprise"><span class="header-section-number">15.3</span> Package Management in the Enterprise</a>
   <ul class="collapse">
-  <li><a href="#open-source-in-enterprise" id="toc-open-source-in-enterprise" class="nav-link" data-scroll-target="#open-source-in-enterprise"><span class="header-section-number">16.3.1</span> Open Source in Enterprise</a></li>
-  <li><a href="#dealing-with-package-restrictions" id="toc-dealing-with-package-restrictions" class="nav-link" data-scroll-target="#dealing-with-package-restrictions"><span class="header-section-number">16.3.2</span> Dealing with Package Restrictions</a></li>
+  <li><a href="#open-source-in-enterprise" id="toc-open-source-in-enterprise" class="nav-link" data-scroll-target="#open-source-in-enterprise"><span class="header-section-number">15.3.1</span> Open Source in Enterprise</a></li>
+  <li><a href="#dealing-with-package-restrictions" id="toc-dealing-with-package-restrictions" class="nav-link" data-scroll-target="#dealing-with-package-restrictions"><span class="header-section-number">15.3.2</span> Dealing with Package Restrictions</a></li>
   </ul></li>
-  <li><a href="#comprehension-questions" id="toc-comprehension-questions" class="nav-link" data-scroll-target="#comprehension-questions"><span class="header-section-number">16.4</span> Comprehension Questions</a></li>
+  <li><a href="#comprehension-questions" id="toc-comprehension-questions" class="nav-link" data-scroll-target="#comprehension-questions"><span class="header-section-number">15.4</span> Comprehension Questions</a></li>
   </ul>
-<div class="toc-actions"><div><i class="bi bi-github"></i></div><div class="action-links"><p><a href="https://github.com/akgold/do4ds/edit/main/chapters/sec4/4-1-os-ds-in-ent.qmd" class="toc-action">Edit this page</a></p></div></div></nav>
+<div class="toc-actions"><div><i class="bi bi-github"></i></div><div class="action-links"><p><a href="https://github.com/akgold/do4ds/edit/main/chapters/sec3/3-1-os-ds-in-ent.qmd" class="toc-action">Edit this page</a></p></div></div></nav>
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 <!-- main -->
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 <div class="quarto-title">
-<h1 class="title"><span id="sec-osds-ent" class="quarto-section-identifier"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></h1>
+<h1 class="title"><span id="sec-osds-ent" class="quarto-section-identifier"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></h1>
 </div>
 
 
@@ -363,8 +352,8 @@ <h1 class="title"><span id="sec-osds-ent" class="quarto-section-identifier"><spa
 
 <p>If you’re working in an enterprise, there is almost certainly an experienced IT/Admin organization nearby. They probably know a lot about auth, scaling, storage, networking, and more. But they most likely know very little about open source, and they likely know even less about the work of a data scientist.</p>
 <p>This chapter explains a few of the most common things IT/Admins usually don’t understand about how data scientists work. By the end of this chapter, you will understand what IT/Admins need to understand about these topics to be able to better support you as a user of the environment they maintain.</p>
-<section id="data-science-sandboxes" class="level2" data-number="16.1">
-<h2 data-number="16.1" class="anchored" data-anchor-id="data-science-sandboxes"><span class="header-section-number">16.1</span> Data Science Sandboxes</h2>
+<section id="data-science-sandboxes" class="level2" data-number="15.1">
+<h2 data-number="15.1" class="anchored" data-anchor-id="data-science-sandboxes"><span class="header-section-number">15.1</span> Data Science Sandboxes</h2>
 <p>In <a href="../sec1/1-5-deployments.html">Chapter&nbsp;<span>5</span></a> on code promotion, we talked about wanting to create separate dev/test/prod environments for your data science assets. In many organizations, your good intentions to do dev/test/prod work for your data science assets are insufficient.</p>
 <p>In the enterprise, it’s often the case that IT/Admins are required to ensure that your dev work can’t wreak havoc on actual production systems. If you can work with your organization’s IT/Admins to get a place to work, this is a good thing! It’s nice to have a sandbox where you can do whatever you want with no concern of breaking anything real.</p>
 <p>There are three components to a data science sandbox:</p>
@@ -374,32 +363,32 @@ <h2 data-number="16.1" class="anchored" data-anchor-id="data-science-sandboxes">
 <li>A process to promote data science projects into production</li>
 </ol>
 <p>Many IT/Admins are familiar with building workbenches for other sorts of software development tasks, so they may believe they understand what you need.</p>
-<section id="read-only-data-access" class="level4" data-number="16.1.0.1">
-<h4 data-number="16.1.0.1" class="anchored" data-anchor-id="read-only-data-access"><span class="header-section-number">16.1.0.1</span> Read-Only Data Access</h4>
+<section id="read-only-data-access" class="level4" data-number="15.1.0.1">
+<h4 data-number="15.1.0.1" class="anchored" data-anchor-id="read-only-data-access"><span class="header-section-number">15.1.0.1</span> Read-Only Data Access</h4>
 <p>In software engineering, the shape of the data in the system matters a lot, but the content doesn’t matter much. If you’re building software to do inventory tracking, you’re perfectly fine testing on data that isn’t of a real inventory as long as it’s formatted the same as real inventory data. That means that a software engineering dev environment doesn’t require access to any real data.</p>
 <p>IT/Admins may believe that providing a standalone or isolated environment for you to work in is sufficient. You’re probably wincing reading this knowing that it’s not the case.</p>
 <p>As you know, data science isn’t like that. In data science, what you’re doing in dev environments – exploring relationships between variables, visualizing, training models, looks much more different from test and prod than for software engineering. You need a place where you can work with real data, explore relationships in the data, and try out ways of modeling and visualizing the data to see what works.</p>
 <p>In many cases, creating a data science sandbox with <em>read-only</em> access to data is a great solution. If you’re creating a tool that also writes data, you can write the data only within the dev environment.</p>
 <p>If you’re able to do this, you can explore the data to your heart’s content without the IT/Admin team having to worry you’re going to mess up production data.</p>
-<p>Depending on your organization, they may also be worried about data exfiltration – people intentionally or accidentally removing data from the sandbox environment. In that case, you may want to run your sandbox without the ability to connect to the internet, sometimes called <em>airgapped</em> or <em>offline</em>. More on how to work in an airgapped environment is in <a href="4-2-ent-networks.html">Chapter&nbsp;<span>17</span></a>.</p>
+<p>Depending on your organization, they may also be worried about data exfiltration – people intentionally or accidentally removing data from the sandbox environment. In that case, you may want to run your sandbox without the ability to connect to the internet, sometimes called <em>airgapped</em> or <em>offline</em>. More on how to work in an airgapped environment is in <a href="3-2-ent-networks.html">Chapter&nbsp;<span>16</span></a>.</p>
 </section>
-<section id="package-availability" class="level4" data-number="16.1.0.2">
-<h4 data-number="16.1.0.2" class="anchored" data-anchor-id="package-availability"><span class="header-section-number">16.1.0.2</span> Package Availability</h4>
+<section id="package-availability" class="level4" data-number="15.1.0.2">
+<h4 data-number="15.1.0.2" class="anchored" data-anchor-id="package-availability"><span class="header-section-number">15.1.0.2</span> Package Availability</h4>
 <p>Your organization may not have any restrictions on the packages you can install and use in your environment. If so, that’s great! You should still use environment as code tooling as we explored in <a href="../sec1/1-1-env-as-code.html">Chapter&nbsp;<span>1</span></a>.</p>
 <p>But other organizations don’t allow free-and-open access to packages inside their environments for security or other reasons. They may have restrictive networking rules that don’t allow you to reach our to CRAN, BioConductor, PyPI, or GitHub to install packages publicly.</p>
 <p>There may also be rules about having to validate packages – for security and/or correctness – before they can be used in a production context.</p>
 <p>This is difficult, since the exploratory dev process often involves trying out new packages – is it best to use this modeling package or that, best to use one type of visualization or another. If you can convince your IT/Admins to give you freer access to packages in dev, that’s ideal.</p>
 <p>You can work with them to figure out what the promotion process will look like. It’s easy to generate a list of the packages you’ll need to promote apps or reports into production with tools like <code>renv</code> or <code>venv</code>. Great collaborations with IT/Admin are possible if you can develop a procedure where you give them package manifests that they can compare to allow-lists and then make those packages available.</p>
 </section>
-<section id="a-promotion-process" class="level4" data-number="16.1.0.3">
-<h4 data-number="16.1.0.3" class="anchored" data-anchor-id="a-promotion-process"><span class="header-section-number">16.1.0.3</span> A Promotion Process</h4>
+<section id="a-promotion-process" class="level4" data-number="15.1.0.3">
+<h4 data-number="15.1.0.3" class="anchored" data-anchor-id="a-promotion-process"><span class="header-section-number">15.1.0.3</span> A Promotion Process</h4>
 <p>The last thing you’ll need is a process to promote content out of the dev environment into test or prod. The parameters of this process will vary a lot depending on your organization.</p>
 <p>In many organizations, data scientists won’t have permissions to deploy into the prod environment – only a small group of admins will have the ability to verify changes and submit them to the prod environment.</p>
 <p>In this case, a code promotion strategy (see <a href="../sec1/1-5-deployments.html">Chapter&nbsp;<span>5</span></a>) co-designed with your IT/Admins is the way to go. You want to hand off a fully-baked production asset so all they need to do is put it into the right place, preferably with CI/CD tooling.</p>
 </section>
 </section>
-<section id="devtestprod-for-admins" class="level2" data-number="16.2">
-<h2 data-number="16.2" class="anchored" data-anchor-id="devtestprod-for-admins"><span class="header-section-number">16.2</span> Dev/Test/Prod for Admins</h2>
+<section id="devtestprod-for-admins" class="level2" data-number="15.2">
+<h2 data-number="15.2" class="anchored" data-anchor-id="devtestprod-for-admins"><span class="header-section-number">15.2</span> Dev/Test/Prod for Admins</h2>
 <p>In the chapter on environment as code tooling, we discussed how you want to create a version of your package environment in a safe place and then use code to share it with others and promote it into production.</p>
 <p>The IT/Admin group at your organization probably is thinking about something similar, but at a more basic level. They want to make sure that they’re providing a great experience to you – the users of the platform.</p>
 <p>So they probably want to make sure they can upgrade the servers you’re using, change to a newer operating system, or upgrade to a newer version of R or Python without interrupting your use of the servers.</p>
@@ -416,12 +405,12 @@ <h2 data-number="16.2" class="anchored" data-anchor-id="devtestprod-for-admins">
 <p>It’s also worth noting that IaC may or may not be deployed using CI/CD. It’s generally a good practice to do so, but you can have IaC tooling that’s deployed manually.</p>
 <p>Basically none of these tools will save you from your own bad habits, but they can give you alternatives.</p>
 </section>
-<section id="package-management-in-the-enterprise" class="level2" data-number="16.3">
-<h2 data-number="16.3" class="anchored" data-anchor-id="package-management-in-the-enterprise"><span class="header-section-number">16.3</span> Package Management in the Enterprise</h2>
+<section id="package-management-in-the-enterprise" class="level2" data-number="15.3">
+<h2 data-number="15.3" class="anchored" data-anchor-id="package-management-in-the-enterprise"><span class="header-section-number">15.3</span> Package Management in the Enterprise</h2>
 <p>In the chapter on environments as code, we went in depth on how to manage a per-project package environment that moves around with that project. This is a best practice and you should do it.</p>
 <p>But in some Enterprise environments, there may be further requirements around how packages get into the environment, which packages are allowed, and how to validate those packages.</p>
-<section id="open-source-in-enterprise" class="level3" data-number="16.3.1">
-<h3 data-number="16.3.1" class="anchored" data-anchor-id="open-source-in-enterprise"><span class="header-section-number">16.3.1</span> Open Source in Enterprise</h3>
+<section id="open-source-in-enterprise" class="level3" data-number="15.3.1">
+<h3 data-number="15.3.1" class="anchored" data-anchor-id="open-source-in-enterprise"><span class="header-section-number">15.3.1</span> Open Source in Enterprise</h3>
 <p>Open Souce software is the water code-first data science swims in. R and Python are open source. Any package you’ll access on CRAN, BioConductor, or PyPI is open source.</p>
 <p>Even if you don’t know the details, you’re probably already a big believer in the power of Free and Open Source Software (FOSS) to help people get stuff done.</p>
 <p>In the enterprise, it is sometimes the case that people are more acquainted with the risks of open source than the benefits.</p>
@@ -443,8 +432,8 @@ <h3 data-number="16.3.1" class="anchored" data-anchor-id="open-source-in-enterpr
 <p>Say I create an app or plot in R and then share that plot with the public – is that app or plot bound by the license as well? Do I now have to release my source code to the public? Many would argue no – it uses R, but doesn’t derive from R in any way. Others have concerns that stricter interpretations of copyleft might hold up in court if it were to come to that.</p>
 <p>There are disagreements on this among lawyers, and you should be sure to talk to a lawyer at your organization if you have concerns.</p>
 </section>
-<section id="dealing-with-package-restrictions" class="level3" data-number="16.3.2">
-<h3 data-number="16.3.2" class="anchored" data-anchor-id="dealing-with-package-restrictions"><span class="header-section-number">16.3.2</span> Dealing with Package Restrictions</h3>
+<section id="dealing-with-package-restrictions" class="level3" data-number="15.3.2">
+<h3 data-number="15.3.2" class="anchored" data-anchor-id="dealing-with-package-restrictions"><span class="header-section-number">15.3.2</span> Dealing with Package Restrictions</h3>
 <p><a href="../sec1/1-1-env-as-code.html">Chapter&nbsp;<span>1</span></a> on environments as code dealt with how to create a reproducible version of your package library for any given piece of content. But in some enterprises, you won’t be able to freely create a library. Instead, your organization may have restrictions on package installation and will need to gate the packages that are allowed into your environment.</p>
 <p>In order to enact these restrictions, IT/Admins have to do two things - make sure that public repositories are not available to users of their data science platforms, and use one of these repository tools to manage the set of packages that are available inside their environment. It often takes a bit of convincing, but a good division of labor here is generally that the IT/Admins manage the repository server and what’s allowed into the environment and the individual teams manage their own project libraries.</p>
 <div class="callout callout-style-default callout-note callout-titled">
@@ -474,8 +463,8 @@ <h3 data-number="16.3.2" class="anchored" data-anchor-id="dealing-with-package-r
 <p>The second thing your organization may care about is the licenses software is released under. They may want to disallow certain licenses – especially aggressive copyleft licenses – from being present in their codebases.</p>
 </section>
 </section>
-<section id="comprehension-questions" class="level2" data-number="16.4">
-<h2 data-number="16.4" class="anchored" data-anchor-id="comprehension-questions"><span class="header-section-number">16.4</span> Comprehension Questions</h2>
+<section id="comprehension-questions" class="level2" data-number="15.4">
+<h2 data-number="15.4" class="anchored" data-anchor-id="comprehension-questions"><span class="header-section-number">15.4</span> Comprehension Questions</h2>
 <ol type="1">
 <li>What is the purpose of creating a data science sandbox? Who benefits most from the creation of a sandbox?</li>
 <li>Why is using infrastructure as code an important prerequisite for doing Dev/Test/Prod?</li>
@@ -722,13 +711,13 @@ <h2 data-number="16.4" class="anchored" data-anchor-id="comprehension-questions"
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diff --git a/chapters/sec4/4-2-ent-networks.html b/chapters/sec3/3-2-ent-networks.html
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+ <span class="menu-text"><span class="chapter-number">6</span>&nbsp; <span class="chapter-title">Demystifying Docker</span></span></a>
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+ <span class="menu-text">IT/Admin for Data Science</span></a>
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+  <a href="../../chapters/sec2/2-1-cloud.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">7</span>&nbsp; <span class="chapter-title">The Cloud</span></span></a>
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- <span class="menu-text"><span class="chapter-number">7</span>&nbsp; <span class="chapter-title">Using the Command Line</span></span></a>
+  <a href="../../chapters/sec2/2-2-cmd-line.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">8</span>&nbsp; <span class="chapter-title">Customizing the command line</span></span></a>
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+  <a href="../../chapters/sec2/2-3-linux.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">9</span>&nbsp; <span class="chapter-title">Intro to Linux Administration</span></span></a>
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+  <a href="../../chapters/sec2/2-4-app-admin.html" class="sidebar-item-text sidebar-link">
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+  <a href="../../chapters/sec2/2-5-scale.html" class="sidebar-item-text sidebar-link">
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+  <a href="../../chapters/sec2/2-6-networking.html" class="sidebar-item-text sidebar-link">
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+  <a href="../../chapters/sec3/3-1-os-ds-in-ent.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></a>
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+  <a href="../../chapters/sec3/3-3-auth.html" class="sidebar-item-text sidebar-link">
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+  <a href="../../chapters/sec3/3-4-ent-servers.html" class="sidebar-item-text sidebar-link">
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+  </div>
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@@ -330,25 +319,25 @@
     <h2 id="toc-title">Table of contents</h2>
    
   <ul>
-  <li><a href="#enterprise-networking-terminology" id="toc-enterprise-networking-terminology" class="nav-link active" data-scroll-target="#enterprise-networking-terminology"><span class="header-section-number">17.1</span> Enterprise Networking Terminology</a>
+  <li><a href="#enterprise-networking-terminology" id="toc-enterprise-networking-terminology" class="nav-link active" data-scroll-target="#enterprise-networking-terminology"><span class="header-section-number">16.1</span> Enterprise Networking Terminology</a>
   <ul class="collapse">
-  <li><a href="#what-proxies-do" id="toc-what-proxies-do" class="nav-link" data-scroll-target="#what-proxies-do"><span class="header-section-number">17.1.1</span> What proxies do</a></li>
+  <li><a href="#what-proxies-do" id="toc-what-proxies-do" class="nav-link" data-scroll-target="#what-proxies-do"><span class="header-section-number">16.1.1</span> What proxies do</a></li>
   </ul></li>
-  <li><a href="#what-data-science-needs-from-the-network" id="toc-what-data-science-needs-from-the-network" class="nav-link" data-scroll-target="#what-data-science-needs-from-the-network"><span class="header-section-number">17.2</span> What data science needs from the network</a>
+  <li><a href="#what-data-science-needs-from-the-network" id="toc-what-data-science-needs-from-the-network" class="nav-link" data-scroll-target="#what-data-science-needs-from-the-network"><span class="header-section-number">16.2</span> What data science needs from the network</a>
   <ul class="collapse">
-  <li><a href="#issues-with-inbound-proxies" id="toc-issues-with-inbound-proxies" class="nav-link" data-scroll-target="#issues-with-inbound-proxies"><span class="header-section-number">17.2.1</span> Issues with inbound proxies</a></li>
-  <li><a href="#issues-with-forwardoutbound-proxies" id="toc-issues-with-forwardoutbound-proxies" class="nav-link" data-scroll-target="#issues-with-forwardoutbound-proxies"><span class="header-section-number">17.2.2</span> Issues with forward/outbound proxies</a></li>
+  <li><a href="#issues-with-inbound-proxies" id="toc-issues-with-inbound-proxies" class="nav-link" data-scroll-target="#issues-with-inbound-proxies"><span class="header-section-number">16.2.1</span> Issues with inbound proxies</a></li>
+  <li><a href="#issues-with-forwardoutbound-proxies" id="toc-issues-with-forwardoutbound-proxies" class="nav-link" data-scroll-target="#issues-with-forwardoutbound-proxies"><span class="header-section-number">16.2.2</span> Issues with forward/outbound proxies</a></li>
   </ul></li>
-  <li><a href="#comprehension-questions" id="toc-comprehension-questions" class="nav-link" data-scroll-target="#comprehension-questions"><span class="header-section-number">17.3</span> Comprehension Questions</a></li>
+  <li><a href="#comprehension-questions" id="toc-comprehension-questions" class="nav-link" data-scroll-target="#comprehension-questions"><span class="header-section-number">16.3</span> Comprehension Questions</a></li>
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 <div class="quarto-title">
-<h1 class="title"><span id="sec-ent-networks" class="quarto-section-identifier"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></h1>
+<h1 class="title"><span id="sec-ent-networks" class="quarto-section-identifier"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></h1>
 </div>
 
 
@@ -363,21 +352,34 @@ <h1 class="title"><span id="sec-ent-networks" class="quarto-section-identifier">
 
 </header>
 
-<p>In <a href="../sec3/3-3-networking.html">Chapter&nbsp;<span>12</span></a> we went over a general introduction to networking, including an introduction to DNS, how to get and use a real URL, and making sure your servers are secure with SSL/HTTPS.</p>
+<p>In <a href="../sec2/2-6-networking.html">Chapter&nbsp;<span>12</span></a> we went over a general introduction to networking, including an introduction to DNS, how to get and use a real URL, and making sure your servers are secure with SSL/HTTPS.</p>
 <p>These are requirements for <em>any</em> server configuration, so it’s great that you understand them now. If you’re in an environment where you’re configuring your own server, this is probably enough. But if you’re working with an enterprise IT/Admin team – or a standalone networking team – they’ve got a much more complicated setup in mind. This chapter aims to equip you with an understanding of the kind of networking setup they’re going to configure for you and how to talk to them about it.</p>
-<p>In <a href="../sec3/3-3-networking.html">Chapter&nbsp;<span>12</span></a>, we talked about the analogy of a server as an apartment building. That’s a great analogy to your server – the front door sits on a public street and people can knock on the door as they please. You have to check in with the front desk guard to get in, so there’s a good amount of security. But there isn’t security in layers. If someone were to overwhelm or fool the front door guard, or find a side door left open, they can run amok inside the building.</p>
+<p>In <a href="../sec2/2-6-networking.html">Chapter&nbsp;<span>12</span></a>, we talked about the analogy of a server as an apartment building. That’s a great analogy to your server – the front door sits on a public street and people can knock on the door as they please. You have to check in with the front desk guard to get in, so there’s a good amount of security. But there isn’t security in layers. If someone were to overwhelm or fool the front door guard, or find a side door left open, they can run amok inside the building.</p>
 <p>In enterprises, this isn’t acceptable. Instead, the setup of an enterprise network looks like a castle keep behind a drawbridge and a front gate.</p>
+<p>However, in many cases, that <em>public IP Address</em> isn’t the IP Address of an actual server. Instead, it’s some sort of network device that sends traffic into a <em>private network</em>, where</p>
+<p>Many are housed in private networks. A private network is one where the hosts aren’t directly accessible to the public. You can think of a host in a private network like a building inside a gated community. You may still be able to get there from the public, but you can’t just walk up to the building from the street. Instead you need to come in through the specific gates that have been permitted and approach only on the roads that are allowed.</p>
+<p>TODO: Image of public IPs like street address, private like cul-de-sac</p>
+<p>There are many different kinds of private networks. Some are small and enforced by connection to a physical endpoint, like the private network your WiFi router controls that houses your laptop, phone, TV, Xbox, and anything else you allow to connect to your router. In other cases, the network is a software network. Many organizations have virtual private networks (VPNs). In this case, you connect to the network via software. There may be resources you can only connect to inside your VPN and there also might be limitations about what you can go out and get.</p>
+<p>There are a few different reasons for this public/private network split. The first is security. If you’ve got a public IP Address, anyone on the internet can come knock on your virtual front door. That’s actually not so bad. What’s more problematic is that they can go all the way around the building looking for an unlocked side door. Putting your host inside a private network is a way to ensure that people can only approach the host through on the pathways you intend.</p>
+<p>The second reason is convenience.</p>
+<p>Private networks provide a nice layer of abstraction for network addresses.</p>
+<p>You probably have a variety of network-enabled devices in your home, from your laptop and phone to your TV, Xbox, washing machine, and smart locks. But from the outside, your house has only one public IP Address – the address of the router in your home. That means that your router has to keep track of all the devices you’ve got, but they don’t need to register with any sort of public service just to be able to use the internet.</p>
+<p>As we’ll get into in <a href="../sec2/2-7-dns.html">Chapter&nbsp;<span>13</span></a>, keeping track of IP Addresses is best left to machines. If you’re managing a complex private network, it’s really nice to give <em>hostnames</em> to individual hosts. A nice feature of a private hostname compared to a public address is that you don’t have to worry if the hostname is unique across the entire internet – it just has to be unique inside your private network.</p>
 <p>TODO: image of apartment building vs castle</p>
 <p>Relative to a front door that’s on the internet, a drawbridge provides two big advantages.</p>
 <p>First, the drawbridge reduces the attack surface for malicious attacks. Assuming it’s set up right, now there’s only one way in or out. You still want to make sure every side door to your castle keep is closed, but if you were to accidentally mess up, you’ve got an extra layer of security. Additionally, if you are doing work on your server, it’s easy to temporarily close the drawbridge and know everything is secure while work is in progress.</p>
 <p>Because all of the traffic is funneled through this one point of entry, it gives you an obvious place to monitor incoming traffic and check if it’s malicious. If it is, closing the drawbridge is much easier than trying to run around double check that every entrance to the building is closed. Additionally, if the drawbridge were to get damaged by something malicious, it’s way easier to replace compared to the actual building inside.</p>
 <p>For example, let’s say you are targeted by a distributed denial of service (DDOS) attack. This is a type of attack where someone uses a fleet of bots to send a flood of traffic to your servers for the sole purpose of overwhelming them – usually for ransom. It’s not great for your actual data science server to go down as a result of being overwhelmed.</p>
 <p>You probably don’t have monitoring directly on the landing page of RStudio Server about how many people are trying to login – so you wouldn’t know that something bad had happened until they succeeded in overwhelming the server. On the other hand, it’s really easy to put a traffic load monitor on a proxy to alert if something seems out-of-0whack.</p>
-<section id="enterprise-networking-terminology" class="level2" data-number="17.1">
-<h2 data-number="17.1" class="anchored" data-anchor-id="enterprise-networking-terminology"><span class="header-section-number">17.1</span> Enterprise Networking Terminology</h2>
+<section id="enterprise-networking-terminology" class="level2" data-number="16.1">
+<h2 data-number="16.1" class="anchored" data-anchor-id="enterprise-networking-terminology"><span class="header-section-number">16.1</span> Enterprise Networking Terminology</h2>
+<p>REORGED FROM 2.6</p>
+<p>In order to be accessible to traffic from the internet, a host must have a <em>public IP Address</em>, which is unique across the entire internet.</p>
+<p>But many, many more hosts don’t have apublic IP Address. Instead, they live only on a private network and have only a <em>private IP Address</em>. For example, your phone, personal computer, and smart fridge don’t (or shouldn’t) have a public IP Address. Instead, these devices register with your home router and the router assigns and keeps track of their private IP Addresses. Only your router has a public IP Address, so return mail has somewhere to go.</p>
+<p>This system drastically simplifies the topology of the web. Instead of thinking of the web as an enormous set of public streets, it’s more like a series of gated communities and the public IP Address servers only need to keep track of those front gates.</p>
 <p>Hopefully the analogy of a basic server as an apartment building and an enterprise server as a castle keep behind a drawbridge makes basic sense. But let’s get into the way you’ll actually talk about this with the IT/Admins at your organization – I promise they won’t talk about castles and apartments.</p>
 <p>When you stand up a server in the cloud, it’s inside a <em>private network</em>. In AWS, the private network that houses the servers is called a <em>virtual private cloud (VPC)</em>, which you probably saw somewhere in the AWS console.</p>
-<p>For our workbench server, we took that private network and made it public so every server (there was just one) inside our private network also has a public IP address so it was accessible from the internet.</p>
+<p>For our workbench server, we took that private network and made it public so every server (there was just one) inside our private network also has a public IP Address so it was accessible from the internet.</p>
 <p>In an enterprise configuration you won’t do that. Instead, you’ll take your private network and divide it into <em>subnets</em> – most often two of them.</p>
 <p>Now you’ll take the subnets and put all the stuff you actually care about in a private subnet. Private networks generally host all of the servers that actually <em>do things</em>. Your data science workbench server, your databases, server for hosting shiny apps – all these things should live inside the private network. Nothing in the private subnet will be directly accessible from the public internet.</p>
 <div class="callout callout-style-default callout-note callout-titled">
@@ -400,10 +402,10 @@ <h2 data-number="17.1" class="anchored" data-anchor-id="enterprise-networking-te
 <p>This means that the traffic actually coming to your workbench comes only <em>from other servers you control</em>. It’s easy to see why this is more secure.</p>
 <p>[TODO: image of private networks + proxies]</p>
 <p>In most cases, you’ll have minimum two servers in the DMZ. You’ll usually have one or more proxies to handle the incoming HTTPS traffic that comes in from the outside world. You’ll also usually have a proxy that is just for passing SSH traffic along to hosts in the private network, often called a <em>bastion host</em> or <em>jump box</em>.</p>
-<p>The other benefit of using a private network for the things you actually care about is that you can manage the IP addresses and hostnames of those servers without having to worry about getting public addresses. If you want to name one of the servers in your private subnet <em>google.com</em>, you can do that (I wouldn’t recommend it), because the only time that name will be used is when traffic is coming past your proxy servers and into the private network.</p>
-<p>There’s a device sitting on the boundary of all networks that provide translations between private IP addresses and public ones. For your private subnet, you’ll only have an outbound one available. In AWS, it’s called a Network Address Translation (NAT) Gateway. For your private network as a whole, there’ll be another gateway that provides both inbound and outbout support, it’s called an Internet Gateway by AWS.</p>
-<section id="what-proxies-do" class="level3" data-number="17.1.1">
-<h3 data-number="17.1.1" class="anchored" data-anchor-id="what-proxies-do"><span class="header-section-number">17.1.1</span> What proxies do</h3>
+<p>The other benefit of using a private network for the things you actually care about is that you can manage the IP Addresses and hostnames of those servers without having to worry about getting public addresses. If you want to name one of the servers in your private subnet <em>google.com</em>, you can do that (I wouldn’t recommend it), because the only time that name will be used is when traffic is coming past your proxy servers and into the private network.</p>
+<p>There’s a device sitting on the boundary of all networks that provide translations between private IP Addresses and public ones. For your private subnet, you’ll only have an outbound one available. In AWS, it’s called a Network Address Translation (NAT) Gateway. For your private network as a whole, there’ll be another gateway that provides both inbound and outbout support, it’s called an Internet Gateway by AWS.</p>
+<section id="what-proxies-do" class="level3" data-number="16.1.1">
+<h3 data-number="16.1.1" class="anchored" data-anchor-id="what-proxies-do"><span class="header-section-number">16.1.1</span> What proxies do</h3>
 <p>As a data scientist, this may be the first time you’re encountering the term proxy, but for IT/Admins – especially ones who specialize in networking – configuring proxies is an everyday activity.</p>
 <p>Proxies can be either in software or hardware. For example, in our workbench server, we installed the <em>nginx</em> software proxy on the same server as our workbench to allow people to go to any of the different services we installed on that server. In enterprise use cases, proxies are most often on standalone pieces of hardware. They may run <em>nginx</em> or <em>Apache</em> – the other popular open source option. Popular paid enterprise options include <em>F5, Citrix</em>, <em>Fortinet</em>, and <em>Cloudflare</em>.</p>
 <p>Proxies can deal with traffic coming into the private network, called an <em>inbound</em> proxy or they can deal with traffic going out from the private network, called an <em>outbound</em> proxy.</p>
@@ -445,11 +447,11 @@ <h3 data-number="17.1.1" class="anchored" data-anchor-id="what-proxies-do"><span
 <p>Occasionally proxies also do <em>authentication</em>. In most cases, proxies pass along any traffic that comes in to where it’s supposed to go. If there’s authentication, it’s often at the server itself.</p>
 <p>Sometimes the proxy is actually where authentication happens, so you have to provide the credentials at the edge of the network. Once those credentials have been supplied, the proxy will let you through. Depending on the configuration, the proxy may also add some sort of token or header to your incoming traffic to let the servers inside know that your authentication is good and to pass along identification for authorization purposes.</p>
 <p>TODO: image of auth at proxy</p>
-<p>Lastly, there’s a special kind of reverse proxy called a load-balancer. A load-balancer is used to scale a service across a pool of servers on the back end. We’ll get more into how this works in <a href="4-4-ent-servers.html">Chapter&nbsp;<span>19</span></a>.</p>
+<p>Lastly, there’s a special kind of reverse proxy called a load-balancer. A load-balancer is used to scale a service across a pool of servers on the back end. We’ll get more into how this works in <a href="3-4-ent-servers.html">Chapter&nbsp;<span>18</span></a>.</p>
 </section>
 </section>
-<section id="what-data-science-needs-from-the-network" class="level2" data-number="17.2">
-<h2 data-number="17.2" class="anchored" data-anchor-id="what-data-science-needs-from-the-network"><span class="header-section-number">17.2</span> What data science needs from the network</h2>
+<section id="what-data-science-needs-from-the-network" class="level2" data-number="16.2">
+<h2 data-number="16.2" class="anchored" data-anchor-id="what-data-science-needs-from-the-network"><span class="header-section-number">16.2</span> What data science needs from the network</h2>
 <p>As you’ve probably grasped, enterprise networking can be complex. And your IT/Admin group knows a lot about it. What they don’t know a lot about is the interaction of networking and data science, so it’s helpful for you to be able to clearly state what you need.</p>
 <div class="callout callout-style-default callout-note callout-titled">
 <div class="callout-header d-flex align-content-center">
@@ -467,18 +469,18 @@ <h2 data-number="17.2" class="anchored" data-anchor-id="what-data-science-needs-
 </div>
 <p>One of the most common issues with data science environments in an enterprise is proxy behavior. If you’re experiencing weird behavior in your data science environment – files failing to upload or download, sessions getting cutoff strangely, or data not transferring right – asking your IT/Admin about whether there are proxies and their behavior should be suspect number one.</p>
 <p>When you’re talking to your IT/Admin about the proxies, it’s really helpful to have a good mental model of what traffic might be hitting an inbound proxy and what traffic might be hitting an outbound one.</p>
-<p>As we went over in <a href="../sec3/3-3-networking.html">Chapter&nbsp;<span>12</span></a>, network traffic <em>always</em> operates on a call and response model. So whether your traffic is inbound or outbound is dependent on <em>who makes the call</em>. Inbound means that the call is coming from a computer <em>outside</em> the private network directed to a server <em>inside</em> the private network, and outbound is the opposite.</p>
+<p>As we went over in <a href="../sec2/2-6-networking.html">Chapter&nbsp;<span>12</span></a>, network traffic <em>always</em> operates on a call and response model. So whether your traffic is inbound or outbound is dependent on <em>who makes the call</em>. Inbound means that the call is coming from a computer <em>outside</em> the private network directed to a server <em>inside</em> the private network, and outbound is the opposite.</p>
 <p>TODO: image inbound vs outbound connection</p>
 <p>So basically, anything that originates on your laptop – including the actual session into the server is an inbound connection, while anything that originates on the server – including <em>everything</em> in code that runs on the server is an outbound connection.</p>
-<section id="issues-with-inbound-proxies" class="level3" data-number="17.2.1">
-<h3 data-number="17.2.1" class="anchored" data-anchor-id="issues-with-inbound-proxies"><span class="header-section-number">17.2.1</span> Issues with inbound proxies</h3>
+<section id="issues-with-inbound-proxies" class="level3" data-number="16.2.1">
+<h3 data-number="16.2.1" class="anchored" data-anchor-id="issues-with-inbound-proxies"><span class="header-section-number">16.2.1</span> Issues with inbound proxies</h3>
 <p>Inbound proxies affect the connection you’re making from your personal computer to the server. There are two ways this might affect your experience doing data science on a server.</p>
 <p>It’s reasonably common for organizations to have settings that limit file sizes for uploads and downloads or implementing timeouts on file uploads, downloads, and sessions. In data science contexts, files tend to be big and session lengths long.</p>
 <p>If you’re trying to work in a data science context and weird things are happening with file uploads or downloads or sessions ending unexpectedly, checking on inbound proxy settings is a good first step.</p>
 <p>Some data science app frameworks (including Shiny and Streamlit) use a technology called <em>Websockets</em> for maintaining the connection between the user and the app session. Most modern proxies (including those you’ll get from a cloud provider) support Websockets, but some older on-prem proxies don’t and you may have to figure out a workaround if you can’t get Websockets enabled on your proxy.</p>
 </section>
-<section id="issues-with-forwardoutbound-proxies" class="level3" data-number="17.2.2">
-<h3 data-number="17.2.2" class="anchored" data-anchor-id="issues-with-forwardoutbound-proxies"><span class="header-section-number">17.2.2</span> Issues with forward/outbound proxies</h3>
+<section id="issues-with-forwardoutbound-proxies" class="level3" data-number="16.2.2">
+<h3 data-number="16.2.2" class="anchored" data-anchor-id="issues-with-forwardoutbound-proxies"><span class="header-section-number">16.2.2</span> Issues with forward/outbound proxies</h3>
 <p>Almost all enterprise networks have inbound proxies. Outbound ones are somewhat rarer. That’s because outbound proxies limit connections made from inside the network to the outside. It’s obvious why you’d need to protect your data science environment from the entire outside world.</p>
 <p>Many organizations don’t feel the need to limit what external resources people can interact with from inside their firewall, but limitations on outbound access have long been common in highly regulated industries with strong requirements around data security and governance and are becoming increasingly common in many different industries. Many organizations have these proxies to reduce the risk of someone getting in and then being able to exfiltrate valuable resource.</p>
 <p>Organizations who limit outbound access from their data science environment usually refer to the environment as offline or airgapped. The term airgapped indicates that there is a physical gap – air – between the internet and the environment. It is very rare for this to be the case. In most cases, airgapping is accomplished by putting in an outbound proxy that disallows (nearly) all connections.</p>
@@ -500,8 +502,8 @@ <h3 data-number="17.2.2" class="anchored" data-anchor-id="issues-with-forwardout
 <p>This can take a lot of convincing. Good luck.</p>
 </section>
 </section>
-<section id="comprehension-questions" class="level2" data-number="17.3">
-<h2 data-number="17.3" class="anchored" data-anchor-id="comprehension-questions"><span class="header-section-number">17.3</span> Comprehension Questions</h2>
+<section id="comprehension-questions" class="level2" data-number="16.3">
+<h2 data-number="16.3" class="anchored" data-anchor-id="comprehension-questions"><span class="header-section-number">16.3</span> Comprehension Questions</h2>
 <ol type="1">
 <li>What is the advantage of adopting a more complex networking setup than a server just deployed directly on the internet? Are there advantages other than security?</li>
 <li>Draw a mental map with the following entities: inbound traffic, outbound traffic, proxy, DMZ, private subnet, public subnet, VPC</li>
@@ -757,13 +759,13 @@ <h2 data-number="17.3" class="anchored" data-anchor-id="comprehension-questions"
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+      <a href="../../chapters/sec3/3-1-os-ds-in-ent.html" class="pagination-link">
+        <i class="bi bi-arrow-left-short"></i> <span class="nav-page-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span>
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+      <a href="../../chapters/sec3/3-3-auth.html" class="pagination-link">
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-  <li><a href="#linux-is-an-operating-system-with-a-long-history" id="toc-linux-is-an-operating-system-with-a-long-history" class="nav-link active" data-scroll-target="#linux-is-an-operating-system-with-a-long-history"><span class="header-section-number">11.1</span> Linux is an operating system with a long history</a></li>
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-  <li><a href="#managing-who-can-do-what" id="toc-managing-who-can-do-what" class="nav-link" data-scroll-target="#managing-who-can-do-what"><span class="header-section-number">11.5</span> Managing who can do what</a>
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-  <li><a href="#file-permissions" id="toc-file-permissions" class="nav-link" data-scroll-target="#file-permissions"><span class="header-section-number">11.5.1</span> File Permissions</a></li>
-  </ul></li>
-  <li><a href="#installing-stuff" id="toc-installing-stuff" class="nav-link" data-scroll-target="#installing-stuff"><span class="header-section-number">11.6</span> Installing Stuff</a>
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-  <li><a href="#managing-r-and-python" id="toc-managing-r-and-python" class="nav-link" data-scroll-target="#managing-r-and-python"><span class="header-section-number">11.6.1</span> Managing R and Python</a></li>
-  </ul></li>
-  <li><a href="#debugging-and-troubleshooting" id="toc-debugging-and-troubleshooting" class="nav-link" data-scroll-target="#debugging-and-troubleshooting"><span class="header-section-number">11.7</span> Debugging and troubleshooting</a>
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-  <li><a href="#storage" id="toc-storage" class="nav-link" data-scroll-target="#storage"><span class="header-section-number">11.7.1</span> Storage</a></li>
-  <li><a href="#monitoring-processes" id="toc-monitoring-processes" class="nav-link" data-scroll-target="#monitoring-processes"><span class="header-section-number">11.7.2</span> Monitoring processes</a></li>
-  <li><a href="#managing-networking" id="toc-managing-networking" class="nav-link" data-scroll-target="#managing-networking"><span class="header-section-number">11.7.3</span> Managing networking</a></li>
-  <li><a href="#understanding-paths" id="toc-understanding-paths" class="nav-link" data-scroll-target="#understanding-paths"><span class="header-section-number">11.7.4</span> Understanding PATHs</a></li>
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-  <li><a href="#comprehension-questions" id="toc-comprehension-questions" class="nav-link" data-scroll-target="#comprehension-questions"><span class="header-section-number">11.8</span> Comprehension Questions</a></li>
-  <li><a href="#lab-a-working-data-science-workbench" id="toc-lab-a-working-data-science-workbench" class="nav-link" data-scroll-target="#lab-a-working-data-science-workbench"><span class="header-section-number">11.9</span> Lab: A working Data Science Workbench</a>
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-  <li><a href="#step-2-create-a-non-root-user" id="toc-step-2-create-a-non-root-user" class="nav-link" data-scroll-target="#step-2-create-a-non-root-user"><span class="header-section-number">11.9.1</span> Step 2: Create a non-root user</a></li>
-  <li><a href="#step-3-add-an-ssh-key-for-your-user" id="toc-step-3-add-an-ssh-key-for-your-user" class="nav-link" data-scroll-target="#step-3-add-an-ssh-key-for-your-user"><span class="header-section-number">11.9.2</span> Step 3: Add an SSH Key for your user</a></li>
-  <li><a href="#step-4-install-r" id="toc-step-4-install-r" class="nav-link" data-scroll-target="#step-4-install-r"><span class="header-section-number">11.9.3</span> Step 4: Install R</a></li>
-  <li><a href="#step-5-install-python" id="toc-step-5-install-python" class="nav-link" data-scroll-target="#step-5-install-python"><span class="header-section-number">11.9.4</span> Step 5: Install Python</a></li>
-  <li><a href="#step-5-installing-rstudio-server" id="toc-step-5-installing-rstudio-server" class="nav-link" data-scroll-target="#step-5-installing-rstudio-server"><span class="header-section-number">11.9.5</span> Step 5: Installing RStudio Server</a></li>
-  <li><a href="#step-6-installing-jupyerhub-jupyterlab" id="toc-step-6-installing-jupyerhub-jupyterlab" class="nav-link" data-scroll-target="#step-6-installing-jupyerhub-jupyterlab"><span class="header-section-number">11.9.6</span> Step 6: Installing JupyerHub + JupyterLab</a></li>
-  <li><a href="#step-7-running-a-plumber-api-in-a-container" id="toc-step-7-running-a-plumber-api-in-a-container" class="nav-link" data-scroll-target="#step-7-running-a-plumber-api-in-a-container"><span class="header-section-number">11.9.7</span> Step 7: Running a Plumber API in a Container</a></li>
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-<p>Administering a personal computer is something you’re probably already used to. You know how to access files and folders on your computer and install software.</p>
-<p>There are three additional wrinkles that come up when you’re administering a server. First, you don’t have a graphical interface. Unlike the administration on your personal computer, where you work through pointing-and-clicking, a server has no such interface.</p>
-<p>Second, a server is almost always a multi-user environment. This means from the ground up, the server needs to be designed to serve the needs of several people at once.</p>
-<p>You should already know some basics of how to use the Command line from <a href="../sec2/2-1-cmd-line.html">Chapter&nbsp;<span>6</span></a>. In this chapter, we’ll get into what to do to make your server run smoothly.</p>
-<p>It’s worth saying that you can make a whole career out of Linux System Administration, so this chapter is going to be really focused on the things you need to know to successfully run a data science environment (and fun asides I feel like sharing).</p>
-<p>In the lab for this chapter, we’re going to finally get started with something that is recognizably about data science – we’re going to configure R and Python on our EC2 instance and configure both RStudio Server and JupyterHub. By the end of the chapter you’ll have a running – though still inaccessible – data science workbench.</p>
-<section id="linux-is-an-operating-system-with-a-long-history" class="level2" data-number="11.1">
-<h2 data-number="11.1" class="anchored" data-anchor-id="linux-is-an-operating-system-with-a-long-history"><span class="header-section-number">11.1</span> Linux is an operating system with a long history</h2>
-<p>A computer’s operating system (OS) defines how applications – like Microsoft Word, RStudio, and Minecraft – interact with the underlying hardware to actually do computation. OSes define how files are stored and accessed, how applications are installed and can connect to networks, and more.</p>
-<p>These days, basically all computers run on one of a few different operating systems – Windows, MacOS, or Linux for laptops and desktops; Windows or Linux for servers, Android (a flavor of Linux) or iOS for phones and tablets, and Linux for other kinds of embedded systems (like ATMs and the chips in your car).</p>
-<p>When you stand up a server, you’re going to be choosing from one of a few versions of Linux. If you’re unfamiliar with Linux, the number of choices can seem overwhelming, so here’s a quick primer on the history of operating systems. Hopefully it’ll help it all make sense.</p>
-<p>Before the early 1970s, the market for computer hardware and software looked nothing like it does now. Computers released in that era had extremely tight linking between hardware and software. There were no standard interfaces between hardware and software, so each hardware manufacturer also had to release the software to use with their machine.</p>
-<p>In the early 1970s, Bell Labs released Unix – the first operating system.</p>
-<p>Once there was an operating system, the computer market started looking a lot more familiar to 2020s eyes. Hardware manufacturers would build machines that ran Unix and software companies could write applications that ran on Unix. The fact that those applications would run on <em>any</em> Unix machine was a game-changer.</p>
-<p>In the 1980s, programmers wanted to be able to work with Unix themselves, but didn’t necessarily want to pay Bell Labs for Unix, so they started writing <em>Unix-like</em> operating systems. Unix-like OSes or Unix clones behaved just like Unix, but didn’t actually include any code from Unix itself.<a href="#fn1" class="footnote-ref" id="fnref1" role="doc-noteref"><sup>1</sup></a></p>
-<p>In 1991, Linus Torvalds – then a 21 year-old Finnish grad student – released Linux, an open source Unix clone via a amusingly nonchalant newsgroup posting.<a href="#fn2" class="footnote-ref" id="fnref2" role="doc-noteref"><sup>2</sup></a></p>
-<p>Since then, Linux has seen tremendous adoption. A large majority of the world’s servers run on Linux.<a href="#fn3" class="footnote-ref" id="fnref3" role="doc-noteref"><sup>3</sup></a> Along with most of the world’s servers, almost all of the world’s embedded computers – in ATMs, cars and planes, TVs, and most other gadgets and gizmos – run on Linux. If you have an Android phone or a Chromebook – that’s Linux. Basically all of the world’s supercomputers use Linux.</p>
-<p>As you might imagine, running Linux in so many different places has necessitated the creation of many different kinds of Linux. For example, a full-featured Linux server is going to require a very different operating system than the barebones operating system running on an ATM with extremely modest computational power.</p>
-<p>These different versions are called distributions (<em>distros</em> for short) of Linux. They have a variety of technical attributes and also different licensing models.</p>
-<p>Some versions of Linux, like Ubuntu, are completely open source. Others, like Red Hat Enterprise Linux (RHEL), are paid. Most paid Linux OSes have closely-related free and open source versions – like CentOS and Fedora for RHEL.<a href="#fn4" class="footnote-ref" id="fnref4" role="doc-noteref"><sup>4</sup></a></p>
-<p>Many organizations have a standard Linux distro they use – most often RHEL/CentOS or Ubuntu. Increasingly, organizations deploying in AWS are using Amazon Linux, which is independently maintained by Amazon but was originally a RHEL derivative. There are also some organizations that use SUSE (<a href="https://www.youtube.com/watch?v=nLdexZlVkAY">pronunced soo-suh</a>), which has both open source and enterprise versions.</p>
-</section>
-<section id="a-tiny-intro-to-linux-administration" class="level2" data-number="11.2">
-<h2 data-number="11.2" class="anchored" data-anchor-id="a-tiny-intro-to-linux-administration"><span class="header-section-number">11.2</span> A tiny intro to Linux administration</h2>
-<p>We’ll get into <em>how</em> to administer a Linux server just below, but before we get there, let’s introduce <em>what</em> you’ll be doing as a Linux server admin. There are three main things you’ll manage as a Linux server admin:</p>
-<ul>
-<li><p><strong>System resources</strong> Each server has a certain amount of resources available. In particular, you’ve got CPU, RAM, and storage. Keeping track of how much you’ve got of these things and how they’re being used – and making sure no one is gobbling up all the resources – is an important part of system administration.</p></li>
-<li><p><strong>Networking</strong> Your server is only valuable if you and others can connect to it, so managing how your server can connect to the environment around it is an important part of Linux administration.</p></li>
-<li><p><strong>Permissions</strong> Servers generally exist to allow a number of people to access the same machine. Creating users and groups – and managing what they’re allowed to do – is a huge part of server administration.</p></li>
-<li><p><strong>Applications</strong> Generally you want to <em>do</em> something with your server, so being able to interact with applications that are running, debug issues, and fix things that aren’t going well is an essential Linux admin skill.</p></li>
-</ul>
-<p>When you log into a Linux server, you’ll be interacting exclusively via the command line, so all of the commands in this chapter are going to be terminal commands. If you haven’t yet figured out how to open the terminal on your laptop (and gotten it themed and customized so it’s perfect), I’d advise going back to <a href="../sec2/2-1-cmd-line.html">Chapter&nbsp;<span>6</span></a> to get it all configured.<a href="#fn5" class="footnote-ref" id="fnref5" role="doc-noteref"><sup>5</sup></a></p>
-<div class="callout callout-style-default callout-note callout-titled">
-<div class="callout-header d-flex align-content-center">
-<div class="callout-icon-container">
-<i class="callout-icon"></i>
-</div>
-<div class="callout-title-container flex-fill">
-Windows, Mac, and Linux
-</div>
-</div>
-<div class="callout-body-container callout-body">
-<p>MacOS is based on BSD, a Unix clone, so any terminal commands you’ve used before on Mac will be very similar to Linux commands.</p>
-<p>Windows, on the other hand, is basically the only popular operating system that <em>isn’t</em> a Unix clone. Over time, the Windows command line has gotten more Unix-like, so the differences aren’t as big as they used to be, but there will be some differences in the exact commands that work on Windows vs Linux.</p>
-<p>The most obvious difference is the types of slashes used in file paths. Unix-like systems use forward slashes <code>/</code> to denote file hierarchies, while Windows historically uses back slashes <code>\</code>. These days Windows deals just fine with either.</p>
-</div>
-</div>
-</section>
-<section id="the-filesystem" class="level2" data-number="11.3">
-<h2 data-number="11.3" class="anchored" data-anchor-id="the-filesystem"><span class="header-section-number">11.3</span> The filesystem</h2>
-<p>All of the information available to a computer is indexed by its <em>filesystem</em>. The filesystem is made up of <em>directories</em> or <em>folders</em>, which are containers for other directories and files.</p>
-<p>On your laptop, you’re probably used to browsing the filesystem with your mouse. On your phone, the filesystem is completely obscured by apps, but it’s there.</p>
-<p>When using the command line, the only way to traverse the filesystem is with written commands. Having a good mental model for what the filesystem looks like is, therefore, really important.</p>
-<p>On Mac or Linux, the entire filesystem is a tree (or perhaps an upside-down tree). Every directory is contained in by a <em>parent directory</em>, and may contain one or more <em>children</em> or <em>sub-directories</em>. The <em>root directory, <code>/</code></em> is the base of the tree and is its own parent. A <code>/</code> in between two directories means that it’s a sub-directory.</p>
-<p><img src="../sec2/images/directories.png" class="img-fluid" alt="A tree of directories. / is the root, /home is a sub directory, /home/alex is a sub-sub-directory, and /etc is another sub-directory." width="450"></p>
-<p>Every directory is a sub-directory of <code>/</code> or a sub-directory of a sub-directory of <code>/</code> or…you get the picture. So the <code>/home/alex</code> <em>file path</em> defines a particular location, which is the <code>alex</code> sub-directory of <code>/home</code>, which is a sub-directory of the root directory, <code>/</code>.</p>
-</section>
-<section id="windows-folders-and-files" class="level2" data-number="11.4">
-<h2 data-number="11.4" class="anchored" data-anchor-id="windows-folders-and-files"><span class="header-section-number">11.4</span> Windows folders and files</h2>
-<p>Each Linux computer has exactly one filesystem. On Windows you can have multiple filesystems on the same machine, one for each physical or logical disk. You’re probably familiar with <code>C:</code> as your main filesystem. Your machine may also have a <code>D:</code> drive.</p>
-<p>In Linux, network shares are mounted somewhere on the filesystem, often at <code>/mnt</code>, but the fact that they’re on separate drives is obscured from the user. On Windows, network share drives are mounted as a separate filesystem, often at <code>M:</code> or <code>N:</code> or <code>P:</code>.</p>
-<p>One other difference is that Windows uses <code>\</code> to separate file path elements rather than <code>/</code>. This used to be a big deal, but newer versions of Windows accept file paths using <code>/</code>.</p>
-</section>
-<section id="managing-who-can-do-what" class="level2" data-number="11.5">
-<h2 data-number="11.5" class="anchored" data-anchor-id="managing-who-can-do-what"><span class="header-section-number">11.5</span> Managing who can do what</h2>
-<p>Whenever you’re doing something in Linux, you’re doing that thing <em>as</em> a particular user.</p>
-<p>On any Unix-like system, you can check your active user at any time with the <code>whoami</code> command. For example, here’s what it looks like on my MacBook.</p>
-<div class="sourceCode" id="cb1"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb1-1"><a href="#cb1-1"></a><span class="ex">❯</span> whoami                                                       </span>
-<span id="cb1-2"><a href="#cb1-2"></a><span class="ex">alexkgold</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-<p><code>whoami</code> returns the <em>username</em> of my user.</p>
-<p>Usernames have to be unique on the system – but they’re not the true identifier for a Linux user. A user is uniquely (and permanently) identified by their <em>user id (<code>uid</code>)</em>. All other attributes (including username, password, home directory, groups, and more) are malleable, but <code>uid</code> is forever.</p>
-<p>Many of the users on a Linux server correspond to actual humans, but there are more users than that. Most programs that run on a Linux server run as a <em>service account</em> that represent the set of permissions allowed to that program.</p>
-<p>For example, installing RStudio Server will create a user with username <code>rstudio-server</code>. Then, when <code>rstudio-server</code> goes to do something – start an <code>R</code> session for example – it will do so <em>as</em> <code>rstudio-server</code>.</p>
-<div class="callout callout-style-default callout-note callout-titled">
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-<div class="callout-icon-container">
-<i class="callout-icon"></i>
-</div>
-<div class="callout-title-container flex-fill">
-A few details on UIDs
-</div>
-</div>
-<div class="callout-body-container callout-body">
-<p><code>uid</code>s are just numbers from 0 to over 2,000,000,000. <code>uid</code>s are assigned by the system at the time the user is created. You should probably keep <code>uid</code>s below 2,000,000 or so if you are ever assigning <code>uid</code>s manually – some programs can’t deal with <code>uid</code>s any bigger.</p>
-<p>10,000 is the the lowest <code>uid</code> that’s available for use by a user account. Everything below that is reserved for predefined system accounts or application accounts.</p>
-</div>
-</div>
-<p>In addition to users, Linux has a notion of groups. A group is a collection of users. Each user has exactly one <em>primary</em> group and can be a member of secondary groups.<a href="#fn6" class="footnote-ref" id="fnref6" role="doc-noteref"><sup>6</sup></a> By default, each user’s primary group is the same as their username.</p>
-<p>Like a user has a <code>uid</code> a group has a <code>gid</code>. User <code>gid</code>s start at 100.</p>
-<p>You can see a user’s username, <code>uid</code>, groups, and <code>gid</code> with the <code>id</code> command.</p>
-<div class="sourceCode" id="cb2"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb2-1"><a href="#cb2-1"></a> <span class="ex">❯</span> id                                                                </span>
-<span id="cb2-2"><a href="#cb2-2"></a><span class="va">uid</span><span class="op">=</span>501<span class="kw">(</span><span class="ex">alexkgold</span><span class="kw">)</span> <span class="va">gid</span><span class="op">=</span>20<span class="kw">(</span><span class="ex">staff</span><span class="kw">)</span> <span class="va">groups</span><span class="op">=</span>20<span class="kw">(</span><span class="ex">staff</span><span class="kw">)</span><span class="ex">,12</span><span class="er">(</span><span class="ex">everyone</span><span class="kw">)</span><span class="ex">,61</span><span class="er">(</span><span class="ex">localaccounts</span><span class="kw">)</span><span class="ex">,79</span><span class="er">(</span><span class="ex">_appserverusr</span><span class="kw">)</span><span class="ex">,80</span><span class="er">(</span><span class="ex">admin</span><span class="kw">)</span><span class="ex">,81</span><span class="er">(</span><span class="ex">_appserveradm</span><span class="kw">)</span><span class="ex">,98</span><span class="er">(</span><span class="ex">_lpadmin</span><span class="kw">)</span><span class="ex">,701</span><span class="er">(</span><span class="ex">com.apple.sharepoint.group.1</span><span class="kw">)</span><span class="ex">,33</span><span class="er">(</span><span class="ex">_appstore</span><span class="kw">)</span><span class="ex">,100</span><span class="er">(</span><span class="ex">_lpoperator</span><span class="kw">)</span><span class="ex">,204</span><span class="er">(</span><span class="ex">_developer</span><span class="kw">)</span><span class="ex">,250</span><span class="er">(</span><span class="ex">_analyticsusers</span><span class="kw">)</span><span class="ex">,395</span><span class="er">(</span><span class="ex">com.apple.access_ftp</span><span class="kw">)</span><span class="ex">,398</span><span class="er">(</span><span class="ex">com.apple.access_screensharing</span><span class="kw">)</span><span class="ex">,400</span><span class="er">(</span><span class="ex">com.apple.access_remote_ae</span><span class="kw">)</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-<p>On my laptop, I’m a member of a number of different groups.</p>
-<p>There’s one extra special user – called the admin, root, sudo, or super user. They get the ultra-cool <code>uid</code> 0. That user has permission to do <em>anything</em> on the system. You almost never want to actually log in as the <code>root</code> user. Instead, you make users and add them to the <code>admin</code> or <code>sudo</code> group so that they have the ability to temporarily assume those admin powers.</p>
-<p>The easiest way to make users is with the <code>useradd</code> command. Once you have a user, you may need to change the password, which you can do at any time with the <code>passwd</code> command. Both <code>useradd</code> and <code>passwd</code> start interactive prompts, so you don’t need to do much more than run those commands.</p>
-<table class="table">
-<colgroup>
-<col style="width: 23%">
-<col style="width: 62%">
-</colgroup>
-<thead>
-<tr class="header">
-<th>Command</th>
-<th>What it does</th>
-</tr>
-</thead>
-<tbody>
-<tr class="odd">
-<td><code>su &lt;username&gt;</code></td>
-<td>Change to be a different user.</td>
-</tr>
-<tr class="even">
-<td><code>whoami</code></td>
-<td>Get username of current user.</td>
-</tr>
-<tr class="odd">
-<td><code>id</code></td>
-<td>Get full user + group info on current user.</td>
-</tr>
-<tr class="even">
-<td><code>passwd</code></td>
-<td>Change password.</td>
-</tr>
-<tr class="odd">
-<td><code>useradd</code></td>
-<td>Add a new user.</td>
-</tr>
-</tbody>
-</table>
-<section id="file-permissions" class="level3" data-number="11.5.1">
-<h3 data-number="11.5.1" class="anchored" data-anchor-id="file-permissions"><span class="header-section-number">11.5.1</span> File Permissions</h3>
-<p>Every object in Linux is just a file. Every log – file. Every picture – file. Every program – file. Every system setting – file.</p>
-<p>So determining whether a user can take a particular action is really a question of whether they have the right permissions on a particular file.</p>
-<div class="callout callout-style-default callout-note callout-titled">
-<div class="callout-header d-flex align-content-center">
-<div class="callout-icon-container">
-<i class="callout-icon"></i>
-</div>
-<div class="callout-title-container flex-fill">
-Note
-</div>
-</div>
-<div class="callout-body-container callout-body">
-<p>The question of who’s allowed to do what – authorization – is an extremely deep one. There’s a chapter all about authorization, how it differs from authentication, and the different ways your IT/Admins might want to manage it <a href="sec4/4-3auth">later in the book</a>.</p>
-<p>This is just going to be a high-level overview of basic Linux authorization.</p>
-</div>
-</div>
-<p>There are three permissions you can have: read, write, and execute. Read means you’re allowed to see the contents of a file, write means you can save a changed version of a file, and execute means you’re allowed to run the file as a program.</p>
-<p>The execute permission really only makes sense for some kinds of files - what would it mean to execute a csv file? But Linux doesn’t care – you can assign any combination of these three permissions for any file.</p>
-<p>How are these permissions assigned? Every file has an owner and an owning group.</p>
-<p>So you can think of permissions in Linux as being assigned in a 3x3 grid. The owner, the owning group, and everyone else can have permissions to read, write, or execute the file.</p>
-<p>TODO: change to graphic</p>
-<table class="table">
-<thead>
-<tr class="header">
-<th></th>
-<th>Owner</th>
-<th>Group</th>
-<th>Everyone Else</th>
-</tr>
-</thead>
-<tbody>
-<tr class="odd">
-<td><strong>Read</strong></td>
-<td>✅/❌</td>
-<td>✅/❌</td>
-<td>✅/❌</td>
-</tr>
-<tr class="even">
-<td><strong>Write</strong></td>
-<td>✅/❌</td>
-<td>✅/❌</td>
-<td>✅/❌</td>
-</tr>
-<tr class="odd">
-<td><strong>Execute</strong></td>
-<td>✅/❌</td>
-<td>✅/❌</td>
-<td>✅/❌</td>
-</tr>
-</tbody>
-</table>
-<p>To understand better, let’s look at the permissions on an actual file.</p>
-<p>Running <code>ls -l</code> on a directory gives you the list of files in that directory, along with their permissions. The first few columns of the list give you the full set of file permissions – though they can be a little tricky to read.</p>
-<p>So, for example, here’s a few lines of the output of running <code>ls -l</code> on a python project I have.</p>
-<div class="sourceCode" id="cb3"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb3-1"><a href="#cb3-1"></a><span class="ex">❯</span> ls <span class="at">-l</span>                                                           </span>
-<span id="cb3-2"><a href="#cb3-2"></a><span class="ex">-rw-r--r--</span>  1 alexkgold  staff     28 Oct 30 11:05 config.py</span>
-<span id="cb3-3"><a href="#cb3-3"></a><span class="ex">-rw-r--r--</span>  1 alexkgold  staff   2330 May  8  2017 credentials.json</span>
-<span id="cb3-4"><a href="#cb3-4"></a><span class="ex">-rw-r--r--</span>  1 alexkgold  staff   1083 May  8  2017 main.py</span>
-<span id="cb3-5"><a href="#cb3-5"></a><span class="ex">drwxr-xr-x</span> 33 alexkgold  staff   1056 May 24 13:08 tests</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-<p>This readout has the file permissions (a series of ten characters), followed by a number<a href="#fn7" class="footnote-ref" id="fnref7" role="doc-noteref"><sup>7</sup></a>, then the file’s owner, and the file’s group. Let’s learn how to read these.</p>
-<p>The file’s owner and group are the easiest to understand. In this case, I <code>alexkgold</code> own all the files, and the group of all the files is <code>staff</code>.</p>
-<p>The ten-character file permissions are relative to that user and group.</p>
-<p>The first character indicates the type of file: <code>-</code> for normal and <code>d</code> for a directory.</p>
-<p>The next nine characters are indicators for the three permissions – <code>r</code> for read, <code>w</code> for write, and <code>x</code> for execute (or <code>-</code> for in place of any of those for not) – first for the user, then for the group, then for any other user on the system.</p>
-<p>So, for example, my <code>config.py</code> file with permissions of <code>rw-r-r--</code> indicates the user (<code>alexkgold</code>) can read and write the file, and everyone else – including in the file’s group <code>staff</code> – has read-only permission.</p>
-<p>In the course of administering a server, you will probably need to change a file’s permissions. You can do so using the <code>chmod</code> command.</p>
-<p>For <code>chmod</code>, permissions are indicated with only three numbers – one for the user, one for the group, and one for everyone else. The way this works is pretty clever – you just sum up the permissions as follows: 4 for read, 2 for write, and 1 for execute. You can check for yourself, but any set of permissions can be uniquely identified by a number between 1 and 7.<a href="#fn8" class="footnote-ref" id="fnref8" role="doc-noteref"><sup>8</sup></a></p>
-<p>So <code>chmod 765 &lt;filename&gt;</code> would give the user full permissions (4 + 2 + 1), read and write (4 + 2) to the group, and read and execute (4 + 1) to everyone else. This would be a strange set of permissions to give a file, but it’s a perfectly valid <code>chmod</code> command.</p>
-<div class="callout callout-style-default callout-note callout-titled">
-<div class="callout-header d-flex align-content-center">
-<div class="callout-icon-container">
-<i class="callout-icon"></i>
-</div>
-<div class="callout-title-container flex-fill">
-Note
-</div>
-</div>
-<div class="callout-body-container callout-body">
-<p>If you spend any time administering a Linux server, you almost certainly will at some point find yourself running into a problem and applying <code>chmod 777</code> out of frustration to rule out a permissions issue.</p>
-<p>I can’t in good faith tell you not to do this – we’ve all been there. But if it’s something important, be sure you change it back once you’re finished figuring out what’s going on.</p>
-</div>
-</div>
-<p>In some cases you might actually want to <strong>ch</strong>ange the <strong>own</strong>er or group of a file. You can change users or groups with either names or ids. You can do so using the <code>chown</code> command. If you’re changing the group, the group name gets prefixed with a colon.</p>
-<p>In some cases, you might not be the correct user to take a particular action. You might not want to change the file permissions, but instead to change who <em>you</em> are. In that case, you can <strong>s</strong>witch <strong>u</strong>sers with the <code>su</code> command.</p>
-<p>Some actions are also reserved for the admin user. For example, let’s take a look at this configuration file:</p>
-<div class="sourceCode" id="cb4"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb4-1"><a href="#cb4-1"></a> <span class="ex">❯</span> ls <span class="at">-l</span> /etc/config/my-config                      </span>
-<span id="cb4-2"><a href="#cb4-2"></a><span class="ex">-rw-r--r--</span>  1 root  system  4954 Dec  2 06:37 config.conf</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-<p>As you can see, all users can read this file to check the configuration settings. But this file is owned by <code>root</code>, and only the owner has <code>write</code> permissions. So I could run <code>cat config.conf</code> to see it. Or I could go into it with <code>vim config.conf</code>, but I’d find myself stuck if I wanted to make changes.</p>
-<p>So if I want to change this configuration file, I’d need to temporarily assume my root powers to make changes. Instead of switching to be the root user, I would run <code>sudo vim config.conf</code> and open the file for editing with root permissions.</p>
-<table class="table">
-<colgroup>
-<col style="width: 30%">
-<col style="width: 23%">
-<col style="width: 23%">
-</colgroup>
-<thead>
-<tr class="header">
-<th>Command</th>
-<th>What it does</th>
-<th>Helpful options + notes</th>
-</tr>
-</thead>
-<tbody>
-<tr class="odd">
-<td><code>c h m o d &lt; p ermissions&gt; &lt;file&gt;</code></td>
-<td>Modifies permissions on a file.</td>
-<td>Number indicates permissions for user, group, others: add 4 for read, 2 for write, 1 for execute, 0 for nothing.</td>
-</tr>
-<tr class="even">
-<td><code>c h o w n &lt; user/group&gt; &lt;file&gt;</code></td>
-<td>Change the owner of a file.</td>
-<td>Can be used for user or group, e.g. <code>:my-group</code>.</td>
-</tr>
-<tr class="odd">
-<td><code>su &lt;username&gt;</code></td>
-<td>Change active user.</td>
-<td></td>
-</tr>
-<tr class="even">
-<td><code>sudo &lt;command&gt;</code></td>
-<td>Adopt super user permissions for the following command.</td>
-<td></td>
-</tr>
-</tbody>
-</table>
-</section>
-</section>
-<section id="installing-stuff" class="level2" data-number="11.6">
-<h2 data-number="11.6" class="anchored" data-anchor-id="installing-stuff"><span class="header-section-number">11.6</span> Installing Stuff</h2>
-<p>There are several different ways to install programs for Linux, and you’ll see a few of them throughout this book.</p>
-<p>Just as CRAN and PyPI are repositories for R and Python packages, Linux distros also have their own repositories. For Ubuntu, the <code>apt</code> command is used for accessing and installing <code>.deb</code> files from the Ubuntu repositories. For CentOS and RedHat, the <code>yum</code> command is used for installing <code>.rpm</code> files.</p>
-<div class="callout callout-style-default callout-note callout-titled">
-<div class="callout-header d-flex align-content-center">
-<div class="callout-icon-container">
-<i class="callout-icon"></i>
-</div>
-<div class="callout-title-container flex-fill">
-Note
-</div>
-</div>
-<div class="callout-body-container callout-body">
-<p>The examples below are all for Ubuntu, since that’s what we use in the lab for this book. Conceptually, using <code>yum</code> is very similar, though the exact commands differ somewhat.</p>
-</div>
-</div>
-<p>When you’re installing packages in Ubuntu, you’ll often see commands prefixed with <code>apt-get update &amp;&amp; apt-get upgrade y</code>. This command makes your machine update the list of available packages it knows about on the server and upgrade everything to the latest version.</p>
-<p>Packages are installed with <code>apt-get install &lt;package&gt;</code>. Depending on which user you are, you may need to prefix the command with <code>sudo</code>.</p>
-<p>You can also install packages that aren’t from the central package repository. Doing that will generally involve downloading a file directly from a URL – usually with <code>wget</code> and then installing it from the file you’ve downloaded – often with the <code>gdebi</code> command.</p>
-<table class="table">
-<colgroup>
-<col style="width: 44%">
-<col style="width: 23%">
-</colgroup>
-<thead>
-<tr class="header">
-<th>Command</th>
-<th>What it does</th>
-</tr>
-</thead>
-<tbody>
-<tr class="odd">
-<td><code>a p t - g e t update  &amp;&amp; apt-get upgrade y</code></td>
-<td>Fetch and install upgrades to system packages</td>
-</tr>
-<tr class="even">
-<td><code>apt-get install &lt;package&gt;</code></td>
-<td>Install a system package.</td>
-</tr>
-<tr class="odd">
-<td><code>wget</code></td>
-<td>Download a file from a URL.</td>
-</tr>
-<tr class="even">
-<td><code>gdebi</code></td>
-<td>Install local <code>.deb</code> file.</td>
-</tr>
-</tbody>
-</table>
-<section id="managing-r-and-python" class="level3" data-number="11.6.1">
-<h3 data-number="11.6.1" class="anchored" data-anchor-id="managing-r-and-python"><span class="header-section-number">11.6.1</span> Managing R and Python</h3>
-<p>As the admin of a data science server, managing R and Python installations is a central task you’ll have to do, as well as installing software on top of that like RStudio Server, JupyterHub, and/or Shiny Server. While R and Python are both open source data science languages, the way you’ll have to administer them are pretty different.</p>
-<p>People pretty much only ever install R to do data science. In contrast, Python is one of the world’s most popular programming languages for general purpose computing. Contrary to what you might think, this actually makes configuring Python <em>harder</em> than configuring R.</p>
-<p>The reason is that your system comes with a version of Python installed, but we don’t want to use that version. Given the centrality of that version to normal server operations, we want to leave it alone. It turns out that installing one or more other versions of Python and then ignoring the system version of Python isn’t totally trivial to do. Then we’re going to want to create a standalone virtual environment that’s just for running JupyterHub so it doesn’t get messed up later.</p>
-<p>RStudio and R are system libraries. So when RStudio runs, it calls and owns the R process that you’ll use inside RStudio Server. In contrast, JupyterHub and JupyterLab <em>are</em> Python programs, so we install them inside a Python installation.</p>
-<p>TODO: diagram of relationships of system python, DS python, Jupyter Python.</p>
-</section>
-</section>
-<section id="debugging-and-troubleshooting" class="level2" data-number="11.7">
-<h2 data-number="11.7" class="anchored" data-anchor-id="debugging-and-troubleshooting"><span class="header-section-number">11.7</span> Debugging and troubleshooting</h2>
-<p>There are three main resources you’ll need to manage as the server admin – CPU, RAM, and storage space. There’s more on all three of these and how to make sure you’ve got enough in <a href="3-6-servers.html">Chapter&nbsp;<span>15</span></a>.</p>
-<p>For now, we’re just going to go over how to check how much you’ve got, how much you’re using, and getting rid of stuff that’s misbehaving.</p>
-<section id="storage" class="level3" data-number="11.7.1">
-<h3 data-number="11.7.1" class="anchored" data-anchor-id="storage"><span class="header-section-number">11.7.1</span> Storage</h3>
-<p>A common culprit for weird server behavior is running out of storage space. There are two handy commands for monitoring the amount of storage you’ve got – <code>du</code> and <code>df</code>. These commands are almost always used with the <code>-h</code> flag to put file sizes in human-readable formats.</p>
-<p><code>du</code>, short for <strong>d</strong>isk <strong>u</strong>sage, gives you the size of individual files inside a directory. This can be helpful for finding your largest files or directories if you think you might need to clean up things. It’s particularly useful in combination with the <code>sort</code> command.</p>
-<p>For example, here’s the result of running <code>du</code> on the <code>chapters</code> directory where the text files for this book live.</p>
-<div class="sourceCode" id="cb5"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb5-1"><a href="#cb5-1"></a> <span class="ex">❯</span> du <span class="at">-h</span> chapters <span class="kw">|</span> <span class="fu">sort</span> <span class="at">-h</span>                                      </span>
-<span id="cb5-2"><a href="#cb5-2"></a> <span class="ex">44K</span>    chapters/sec2/images-servers</span>
-<span id="cb5-3"><a href="#cb5-3"></a><span class="ex">124K</span>    chapters/sec3/images-scaling</span>
-<span id="cb5-4"><a href="#cb5-4"></a><span class="ex">156K</span>    chapters/sec2/images</span>
-<span id="cb5-5"><a href="#cb5-5"></a><span class="ex">428K</span>    chapters/sec2/images-traffic</span>
-<span id="cb5-6"><a href="#cb5-6"></a><span class="ex">656K</span>    chapters/sec1/images-code-promotion</span>
-<span id="cb5-7"><a href="#cb5-7"></a><span class="ex">664K</span>    chapters/sec1/images-docker</span>
-<span id="cb5-8"><a href="#cb5-8"></a><span class="ex">1.9M</span>    chapters/sec1/images-repro</span>
-<span id="cb5-9"><a href="#cb5-9"></a><span class="ex">3.4M</span>    chapters/sec1</span>
-<span id="cb5-10"><a href="#cb5-10"></a><span class="ex">3.9M</span>    chapters/sec3/images-auth</span>
-<span id="cb5-11"><a href="#cb5-11"></a><span class="ex">4.1M</span>    chapters/sec3</span>
-<span id="cb5-12"><a href="#cb5-12"></a><span class="ex">4.5M</span>    chapters/sec2/images-networking</span>
-<span id="cb5-13"><a href="#cb5-13"></a><span class="ex">5.3M</span>    chapters/sec2</span>
-<span id="cb5-14"><a href="#cb5-14"></a> <span class="ex">13M</span>    chapters</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-<p>So if I were thinking about cleaning up this directory, I could see that my <code>images-networking</code> directory in <code>sec2</code> is the biggest single bottom-level directory. If you find yourself needing to find big files on your Linux server, it’s worth spending some time with the help pages for <code>du</code>. There are lots of really useful options.</p>
-<p><code>du</code> is useful for identifying large files and directories on a server. <code>df</code>, for <strong>d</strong>isk <strong>f</strong>ree, is useful for diagnosing issues that might be a problem for a directory. If you’re struggling to write into a directory – perhaps getting out of space errors, <code>df</code> can help you diagnose.</p>
-<p><code>df</code> answers the question – given a file or directory, what device is it mounted on and how full is that device?</p>
-<p>So here’s the result of running the <code>df</code> command on that same <code>chapters</code> directory.</p>
-<div class="sourceCode" id="cb6"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb6-1"><a href="#cb6-1"></a> <span class="ex">❯</span> df <span class="at">-h</span> chapters                                                    </span>
-<span id="cb6-2"><a href="#cb6-2"></a><span class="ex">Filesystem</span>     Size   Used  Avail Capacity iused      ifree %iused  Mounted on</span>
-<span id="cb6-3"><a href="#cb6-3"></a><span class="ex">/dev/disk3s5</span>  926Gi  163Gi  750Gi    18% 1205880 7863468480    0%   /System/Volumes/Data</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-<p>So you can see that the chapters folder lives on a disk called <code>/dev/disk3s5</code> that’s a little less than 1Tb and is 18% full – no problem. On a server this can be really useful to know, because it’s quite easy to switch a disk out for a bigger one in the same spot.</p>
-<table class="table">
-<colgroup>
-<col style="width: 11%">
-<col style="width: 11%">
-<col style="width: 11%">
-</colgroup>
-<thead>
-<tr class="header">
-<th>C o mmand</th>
-<th>What it does</th>
-<th>H e lpful o p tions</th>
-</tr>
-</thead>
-<tbody>
-<tr class="odd">
-<td><code>du</code></td>
-<td>Check size of f iles.</td>
-<td><p>Most l ikely to be used <code>d  u  - h &lt;d  i r &gt;  | s o r t -h</code> [^3 -2-l in u x - a d m i n-9]</p>
-<p>Also u seful to c o mbine with <code>h ead</code>.</p></td>
-</tr>
-<tr class="even">
-<td><code>df</code></td>
-<td>Check s t orage space on d e vice.</td>
-<td><code>-h</code></td>
-</tr>
-</tbody>
-</table>
-</section>
-<section id="monitoring-processes" class="level3" data-number="11.7.2">
-<h3 data-number="11.7.2" class="anchored" data-anchor-id="monitoring-processes"><span class="header-section-number">11.7.2</span> Monitoring processes</h3>
-<p>Every program your computer runs is a process. For example, when you type <code>python</code> on the command line to open a REPL, that’s a process. Running more complicated programs usually involves more than one process.</p>
-<p>For example, running RStudio involves (at minimum) one process for the IDE itself and one for the R session that it uses in the background. The relationships between these different processes is mostly hidden from you – the end user.</p>
-<p>As a server admin, finding runaway processes, killing them, and figuring out how to prevent the them from happening again is a pretty common task. Runaway processes usually misbehave by using up the entire CPU, filling up the entire machine’s RAM.</p>
-<p>Like users and groups have ids, each process has a numeric <strong>p</strong>rocess <strong>id</strong> (<code>pid</code>). Each process also has an owner – this can be either a service account or a real user. If you’ve got a rogue process, the pattern is to try to find the process and make note of its <code>pid</code>. Then you can immediately end the process by <code>pid</code> with the <code>kill</code> command.</p>
-<p>So, how do you find a troublesome process?</p>
-<p>The <code>top</code> command is a good first stop. <code>top</code> shows the top CPU-consuming processes in real time. Here’s the <code>top</code> output from my machine as I write this sentence.</p>
-<div class="sourceCode" id="cb7"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb7-1"><a href="#cb7-1"></a><span class="ex">PID</span>    COMMAND      %CPU TIME     <span class="co">#TH    #WQ  #PORT MEM    PURG   CMPRS PGRP</span></span>
-<span id="cb7-2"><a href="#cb7-2"></a><span class="ex">0</span>      kernel_task  16.1 03:56:53 530/10 0    0     2272K  0B     0B    0</span>
-<span id="cb7-3"><a href="#cb7-3"></a><span class="ex">16329</span>  WindowServer 16.0 01:53:20 23     6    3717  941M-  16M+   124M  16329</span>
-<span id="cb7-4"><a href="#cb7-4"></a><span class="ex">24484</span>  iTerm2       11.3 00:38.20 5      2    266-  71M-   128K   18M-  24484</span>
-<span id="cb7-5"><a href="#cb7-5"></a><span class="ex">29519</span>  top          9.7  00:04.30 1/1    0    36    9729K  0B     0B    29519</span>
-<span id="cb7-6"><a href="#cb7-6"></a><span class="ex">16795</span>  Magnet       3.1  00:39.16 3      1    206   82M    0B     39M   16795</span>
-<span id="cb7-7"><a href="#cb7-7"></a><span class="ex">16934</span>  Arc          1.8  18:18.49 45     6    938   310M   144K   61M   16934</span>
-<span id="cb7-8"><a href="#cb7-8"></a><span class="ex">16456</span>  Messages     1.7  06:58.27 4      1    603   138M   2752K  63M   16456</span>
-<span id="cb7-9"><a href="#cb7-9"></a><span class="ex">1</span>      launchd      1.7  13:41.03 4/1    3/1  3394+ 29M    0B     6080K 1</span>
-<span id="cb7-10"><a href="#cb7-10"></a><span class="ex">573</span>    diagnosticd  1.4  04:31.97 3      2    49    2417K  0B     816K  573</span>
-<span id="cb7-11"><a href="#cb7-11"></a><span class="ex">16459</span>  zoom.us      1.3  66:38.37 30     3    2148  214M   384K   125M  16459</span>
-<span id="cb7-12"><a href="#cb7-12"></a><span class="ex">16575</span>  UniversalCon 1.3  01:15.89 2      1    131   12M    0B     2704K 16575</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-<p>In most instances, the first three columns are the most useful. You’ve got the name of the command and how much CPU they’re using. Right now, nothing is using very much CPU. If I were to find something concerning – perhaps an R process that is using 500% of CPU – I would want to take notice of its <code>pid</code> to kill it with <code>kill</code>.</p>
-<div class="callout callout-style-default callout-note callout-titled">
-<div class="callout-header d-flex align-content-center">
-<div class="callout-icon-container">
-<i class="callout-icon"></i>
-</div>
-<div class="callout-title-container flex-fill">
-So much CPU?
-</div>
-</div>
-<div class="callout-body-container callout-body">
-<p>For <code>top</code> (and most other commands), CPU is expressed as a percent of <em>single core</em> availability. So, on a modern machine (with multiple cores), it’s very common to see CPU totals well over 100%. Seeing a single process using over 100% of CPU is rarer.</p>
-</div>
-</div>
-<p>The <code>top</code> command takes over your whole terminal. You can exit with <code>Ctrl + c</code>.</p>
-<p>Another useful command for finding runaway processes is <code>ps aux</code>.<a href="#fn9" class="footnote-ref" id="fnref9" role="doc-noteref"><sup>9</sup></a> It lists all processes currently running on the system, along with how much CPU and RAM they’re using. You can sort the output with the <code>--sort</code> flag and specify sorting by cpu with <code>--sort -%cpu</code> or by memory with <code>--sort -%mem</code>.</p>
-<p>Because <code>ps aux</code> returns <em>every</em> running process on the system, you’ll probably want to pipe the output into <code>head</code>.</p>
-<p>Another useful way to use <code>ps aux</code> is in combination with <code>grep</code>. If you pretty much know what the problem is – often this might be a runaway R or Python process – <code>ps aux | grep &lt;name&gt;</code> can be super useful to get the <code>pid</code>.</p>
-<p>For example, here are the RStudio processes currently running on my system.</p>
-<div class="sourceCode" id="cb8"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb8-1"><a href="#cb8-1"></a> <span class="op">&gt;</span> ps <span class="ex">aux</span> <span class="kw">|</span> <span class="fu">grep</span> <span class="st">"RStudio\|USER"</span>                                                                                      <span class="pp">[</span><span class="ss">10:21:18</span><span class="pp">]</span></span>
-<span id="cb8-2"><a href="#cb8-2"></a><span class="ex">USER</span>               PID  %CPU %MEM      VSZ    RSS   TT  STAT STARTED      TIME COMMAND</span>
-<span id="cb8-3"><a href="#cb8-3"></a><span class="ex">alexkgold</span>        23583   0.9  1.7 37513368 564880   <span class="pp">??</span>  S    Sat09AM  17:15.27 /Applications/RStudio.app/Contents/MacOS/RStudio</span>
-<span id="cb8-4"><a href="#cb8-4"></a><span class="ex">alexkgold</span>        23605   0.5  0.4 36134976 150828   <span class="pp">??</span>  S    Sat09AM   1:58.16 /Applications/RStudio.app/Contents/MacOS/rsession <span class="at">--config-file</span> none <span class="at">--program-mode</span> desktop </span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-<div class="callout callout-style-default callout-tip callout-titled">
-<div class="callout-header d-flex align-content-center">
-<div class="callout-icon-container">
-<i class="callout-icon"></i>
-</div>
-<div class="callout-title-container flex-fill">
-Tip
-</div>
-</div>
-<div class="callout-body-container callout-body">
-<p>The <code>grep</code> command above looks a little weird because I used a little trick. I wanted to keep the header in the output, so the regex I used matches both the header line (<code>USER</code>) and the thing I actually care about (<code>RStudio</code>).</p>
-</div>
-</div>
-<table class="table">
-<colgroup>
-<col style="width: 23%">
-<col style="width: 23%">
-<col style="width: 23%">
-</colgroup>
-<thead>
-<tr class="header">
-<th>Command</th>
-<th>What it does</th>
-<th>Helpful options</th>
-</tr>
-</thead>
-<tbody>
-<tr class="odd">
-<td><code>top</code></td>
-<td>See what’s running on the system.</td>
-<td></td>
-</tr>
-<tr class="even">
-<td><code>ps aux</code></td>
-<td>See all system processes.</td>
-<td>Consider using <code>--sort</code> and pipe into <code>head</code> or <code>grep</code></td>
-</tr>
-<tr class="odd">
-<td><code>kill</code></td>
-<td>Kill a system process.</td>
-<td><code>-9</code> to force kill immediately</td>
-</tr>
-</tbody>
-</table>
-</section>
-<section id="managing-networking" class="level3" data-number="11.7.3">
-<h3 data-number="11.7.3" class="anchored" data-anchor-id="managing-networking"><span class="header-section-number">11.7.3</span> Managing networking</h3>
-<p>Networking is a complicated topic, which we’ll approach with great detail in <a href="3-3-networking.html">Chapter&nbsp;<span>12</span></a>. For now, it’s important to be able to see what’s running on your server that is accessible from the outside world on a particular port.</p>
-<p>The main command to help you see what ports are being used and by what services is the <code>netstat</code> command. <code>netstat</code> returns the services that are running and their associated ports. <code>netstat</code> is generally most useful with the <code>-tlp</code> flags to show programs that are listening and the programs associated.</p>
-<p>TODO: get netstat example</p>
-<table class="table">
-<colgroup>
-<col style="width: 20%">
-<col style="width: 20%">
-<col style="width: 20%">
-</colgroup>
-<thead>
-<tr class="header">
-<th>Command</th>
-<th>What it does</th>
-<th>Helpful options</th>
-</tr>
-</thead>
-<tbody>
-<tr class="odd">
-<td><code>netstat</code></td>
-<td>See ports and services using them.</td>
-<td>Usually used with <code>-tlp</code></td>
-</tr>
-</tbody>
-</table>
-<p>Sometimes you <em>know</em> you’ve got a service running on your machine, but you just can’t seem to get the networking working. It can be useful to access the service directly without having to deal with networking. You can do this with port forwarding, also called tunneling.</p>
-<p>SSH port forwarding allows you to take the output of a port on a remote server, route it through SSH, and display it <em>as if</em> it were on a local port. For example, let’s say I’ve got RStudio Server running on my server. Maybe I don’t have networking set up yet, or I just can’t get it working. If I’ve got SSH to my server working properly, I can double check that the service is working as I expect and the issue really is somewhere in the network.</p>
-<p>I find that the syntax for port forwarding completely defies my memory and I have to google it every time I use it. For the kind of port forwarding you’ll use most often in debugging, you’ll use the <code>-L</code> flag.</p>
-<p><code>ssh -L &lt;local port&gt;:&lt;remote ip&gt;:&lt;remote port&gt; &lt;ssh hostname&gt;</code></p>
-<p>When you’re doing ssh forwarding, <code>local</code> is the place you’re ssh-ed into (aka your server) and the <code>remote</code> is another location – usually your laptop.</p>
-<p>Since the “remote” is my laptop, I almost always want to use <code>localhost</code> as the remote IP, and I usually want to use the same port remotely and locally – unless the local service is on a reserved port.</p>
-<p>So let’s say I’ve got RStudio Server running on my server at my-ds-workbench.com on port <code>3939</code>. Then I could run <code>ssh -L 3939:localhost:3939 my-user@my-ds-workbench.com</code>. With this command, I can bypass networking and just access whatever is at port 3939 on my server (hopefully RStudio Workbench!) by just going to <code>localhost:3939</code> in my laptop’s browser.</p>
-</section>
-<section id="understanding-paths" class="level3" data-number="11.7.4">
-<h3 data-number="11.7.4" class="anchored" data-anchor-id="understanding-paths"><span class="header-section-number">11.7.4</span> Understanding PATHs</h3>
-<p>TODO: add note on symlinks</p>
-<p>Let’s say you want to open R on your command line. Once you’ve got everything properly configured, you can just type <code>R</code> and have it open right up.</p>
-<div class="sourceCode" id="cb9"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb9-1"><a href="#cb9-1"></a> <span class="ex">❯</span> R                                                       </span>
-<span id="cb9-2"><a href="#cb9-2"></a></span>
-<span id="cb9-3"><a href="#cb9-3"></a><span class="ex">R</span> version 4.2.0 <span class="er">(</span><span class="ex">2022-04-22</span><span class="kw">)</span> <span class="ex">--</span> <span class="st">"Vigorous Calisthenics"</span></span>
-<span id="cb9-4"><a href="#cb9-4"></a><span class="ex">Copyright</span> <span class="er">(</span><span class="ex">C</span><span class="kw">)</span> <span class="ex">2022</span> The R Foundation for Statistical Computing</span>
-<span id="cb9-5"><a href="#cb9-5"></a><span class="ex">Platform:</span> x86_64-apple-darwin17.0 <span class="er">(</span><span class="ex">64-bit</span><span class="kw">)</span></span>
-<span id="cb9-6"><a href="#cb9-6"></a></span>
-<span id="cb9-7"><a href="#cb9-7"></a><span class="ex">R</span> is free software and comes with ABSOLUTELY NO WARRANTY.</span>
-<span id="cb9-8"><a href="#cb9-8"></a><span class="ex">You</span> are welcome to redistribute it under certain conditions.</span>
-<span id="cb9-9"><a href="#cb9-9"></a><span class="ex">Type</span> <span class="st">'license()'</span> or <span class="st">'licence()'</span> for distribution details.</span>
-<span id="cb9-10"><a href="#cb9-10"></a></span>
-<span id="cb9-11"><a href="#cb9-11"></a>  <span class="ex">Natural</span> language support but running in an English locale</span>
-<span id="cb9-12"><a href="#cb9-12"></a></span>
-<span id="cb9-13"><a href="#cb9-13"></a><span class="ex">R</span> is a collaborative project with many contributors.</span>
-<span id="cb9-14"><a href="#cb9-14"></a><span class="ex">Type</span> <span class="st">'contributors()'</span> for more information and</span>
-<span id="cb9-15"><a href="#cb9-15"></a><span class="st">'citation()'</span> on how to cite R or R packages in publications.</span>
-<span id="cb9-16"><a href="#cb9-16"></a></span>
-<span id="cb9-17"><a href="#cb9-17"></a><span class="ex">Type</span> <span class="st">'demo()'</span> for some demos, <span class="st">'help()'</span> for on-line help, or</span>
-<span id="cb9-18"><a href="#cb9-18"></a><span class="st">'help.start()'</span> for an HTML browser interface to help.</span>
-<span id="cb9-19"><a href="#cb9-19"></a><span class="ex">Type</span> <span class="st">'q()'</span> to quit R.</span>
-<span id="cb9-20"><a href="#cb9-20"></a></span>
-<span id="cb9-21"><a href="#cb9-21"></a><span class="op">&gt;</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-<p>But how does the operating system know what you mean when you type <code>R</code>? If you’ve been reading carefully, you’ve realized that running the command means opening a particular runnable file, and <code>R</code> isn’t a file path on my system.</p>
-<p>You can actually just type the complete filename of a runnable binary into your command line. For example, on my MacBook, my version of R is at <code>/usr/bin/local/R</code>, so I could open an R session by typing that full path. Sometimes it can be handy to be precise about exactly which executable you’re opening (I’m looking at you, multiple versions of Python), so you may want to use full paths to executables.</p>
-<p>If you ever want to check which actual executable is being used by a command, you can use the <code>which</code> command. For example, on my system this is the result of <code>which R</code>.</p>
-<div class="sourceCode" id="cb10"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb10-1"><a href="#cb10-1"></a> <span class="ex">❯</span> which R                                                    </span>
-<span id="cb10-2"><a href="#cb10-2"></a><span class="ex">/usr/local/bin/R</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-<p>Most of the time you don’t want to have to bother with full paths for executables. You want to just type <code>R</code> on the command line and have R open. Moreover, there are cases where functionality relies on another executable being able to find R and run it – think of running RStudio Server, which starts a version of R under the hood.</p>
-<p>The operating system knows how to find the actual runnable programs on your system via something called the <em>path</em>. When you type <code>R</code> into the command line, it searches along the path to find a version of R it can run.</p>
-<p>You can check your path at any time by echoing the <code>PATH</code> environment variable with <code>echo $PATH</code>. On my MacBook, this is what the path looks like.</p>
-<div class="sourceCode" id="cb11"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb11-1"><a href="#cb11-1"></a> <span class="ex">❯</span> echo <span class="va">$PATH</span>                                                      </span>
-<span id="cb11-2"><a href="#cb11-2"></a><span class="ex">/opt/homebrew/bin:/opt/homebrew/sbin:/usr/local/bin:/System/Cryptexes/App/usr/bin:/usr/bin:/bin:/usr/sbin:/sbin</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-<p>Later, when we get into running versions of programs that aren’t the system versions, we may have to append locations to the path so that we can run them easily.</p>
-</section>
-</section>
-<section id="comprehension-questions" class="level2" data-number="11.8">
-<h2 data-number="11.8" class="anchored" data-anchor-id="comprehension-questions"><span class="header-section-number">11.8</span> Comprehension Questions</h2>
-<ol type="1">
-<li>Create a mind map of the following terms: Operating System, Windows, MacOS, Unix, Linux, Distro, Ubuntu</li>
-<li>When you initially SSH-ed into your server using <code>ubuntu@$SERVER_ADDRESS</code>, what user were you and what directory did you enter? What about when you used <code>test_user@$SERVER_ADDRESS</code>?</li>
-<li>What are the 3x3 options for Linux file permissions? How are they indicated in an <code>ls -l</code> command?</li>
-<li>How would you do the following?
-<ol type="1">
-<li><p>Find and kill the process IDs for all running <code>rstudio-server</code> processes.</p></li>
-<li><p>Figure out which port <code>JupyterHub</code> is running on.</p></li>
-<li><p>Create a file called <code>secrets.txt</code>, open it with vim, write something in, close and save it, and make it so that only you can read it.</p></li>
-</ol></li>
-</ol>
-</section>
-<section id="lab-a-working-data-science-workbench" class="level2" data-number="11.9">
-<h2 data-number="11.9" class="anchored" data-anchor-id="lab-a-working-data-science-workbench"><span class="header-section-number">11.9</span> Lab: A working Data Science Workbench</h2>
-<p>In the last chapter’s lab, we set up a bare Ubuntu server in AWS. In this chapter, we’re going to make that server into a data science workbench. By the end of this chapter, you’ll have a functional data science workbench - though it won’t yet be accessible to the outside world.</p>
-<section id="step-1-log-on-with-the-.pem-key" class="level4" data-number="11.9.0.1">
-<h4 data-number="11.9.0.1" class="anchored" data-anchor-id="step-1-log-on-with-the-.pem-key"><span class="header-section-number">11.9.0.1</span> Step 1: Log on with the <code>.pem</code> key</h4>
-<p>The <code>.pem</code> key you downloaded when you set up the server is the skeleton key – it will automatically let you in with complete admin privileges. We’re going to use the <code>.pem</code> key to get started on the server, but be extremely careful with the power of the <code>.pem</code> key.</p>
-<p>Because the keypair is so powerful, AWS requires that you restrict the access pretty severely. If you try to use the keypair without first changing the permissions, you’ll be unable to, and you’ll get a warning that looks something like this:</p>
-<div class="sourceCode" id="cb12"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb12-1"><a href="#cb12-1"></a></span>
-<span id="cb12-2"><a href="#cb12-2"></a><span class="ex">\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@</span></span>
-<span id="cb12-3"><a href="#cb12-3"></a></span>
-<span id="cb12-4"><a href="#cb12-4"></a><span class="ex">\@</span> WARNING: UNPROTECTED PRIVATE KEY FILE! <span class="dt">\@</span></span>
-<span id="cb12-5"><a href="#cb12-5"></a></span>
-<span id="cb12-6"><a href="#cb12-6"></a><span class="ex">\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@\@</span></span>
-<span id="cb12-7"><a href="#cb12-7"></a></span>
-<span id="cb12-8"><a href="#cb12-8"></a><span class="ex">Permissions</span> 0644 for <span class="st">'do4ds-lab-key.pem'</span> are too open.</span>
-<span id="cb12-9"><a href="#cb12-9"></a></span>
-<span id="cb12-10"><a href="#cb12-10"></a><span class="ex">It</span> is required that your private key files are NOT accessible by others.</span>
-<span id="cb12-11"><a href="#cb12-11"></a></span>
-<span id="cb12-12"><a href="#cb12-12"></a><span class="ex">This</span> private key will be ignored.</span>
-<span id="cb12-13"><a href="#cb12-13"></a></span>
-<span id="cb12-14"><a href="#cb12-14"></a><span class="ex">Load</span> key <span class="st">"do4ds-lab-key.pem"</span>: bad permissions</span>
-<span id="cb12-15"><a href="#cb12-15"></a></span>
-<span id="cb12-16"><a href="#cb12-16"></a><span class="ex">ubuntu\@ec2-54-159-134-39.compute-1.amazonaws.com:</span> Permission denied <span class="er">(</span><span class="ex">publickey</span><span class="kw">)</span><span class="bu">.</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-<p>Before we can use it to open the server, we’ll need to change the permissions so that only the user can use it. We’re going to give the key <code>600</code> permissions. If you recall from above, that means that the user can read and write the file and no one else can access.</p>
-<p>On my machine, changing the key goes like this:</p>
-<div class="code-with-filename">
-<div class="code-with-filename-file">
-<pre><strong>Terminal</strong></pre>
-</div>
-<div class="sourceCode" id="cb13"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb13-1"><a href="#cb13-1"></a><span class="bu">cd</span> ~/Documents/do4ds-lab</span>
-<span id="cb13-2"><a href="#cb13-2"></a><span class="fu">chmod</span> 600 do4ds-lab-key.pem</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-</div>
-<p>In your terminal type the following</p>
-<div class="code-with-filename">
-<div class="code-with-filename-file">
-<pre><strong>Terminal</strong></pre>
-</div>
-<div class="sourceCode" id="cb14"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb14-1"><a href="#cb14-1"></a><span class="fu">ssh</span> <span class="at">-i</span> do4ds-lab-key.pem <span class="dt">\</span></span>
-<span id="cb14-2"><a href="#cb14-2"></a>  ubuntu@<span class="va">$SERVER_ADDRESS</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-</div>
-<p>Type <code>yes</code> when prompted, and you’re now logged in to your server!</p>
-<div class="callout callout-style-default callout-note callout-titled">
-<div class="callout-header d-flex align-content-center">
-<div class="callout-icon-container">
-<i class="callout-icon"></i>
-</div>
-<div class="callout-title-container flex-fill">
-SSH on Windows
-</div>
-</div>
-<div class="callout-body-container callout-body">
-<p>For a long time, Windows didn’t come with a built in SSH client, so you had to use PuTTY to do SSH from a Windows machine. Microsoft brought a native SSH client to Windows 10 in 2015, and it has been enabled by default since 2018.</p>
-<p>If you run into any trouble using SSH commands on Windows, double check that you’ve enabled the <code>OpenSSH Client</code>.</p>
-</div>
-</div>
-</section>
-<section id="step-2-create-a-non-root-user" class="level3" data-number="11.9.1">
-<h3 data-number="11.9.1" class="anchored" data-anchor-id="step-2-create-a-non-root-user"><span class="header-section-number">11.9.1</span> Step 2: Create a non-root user</h3>
-<p>The first thing we’re going to do is create a user so that you can login without running as root all the time. In general, if you’ve got a multitenant server, you’re going to want users for each actual human who’s accessing the system.</p>
-<p>I’m going to use the username <code>test-user</code>. If you want to be able to copy/paste commands from the online book, I’d advise doing the same. If you were creating users based on real humans, I’d advise using their names.</p>
-<p>Let’s create a user using the <code>adduser</code> command. This will walk us through a set of prompts to create a new user with a home directory and a password. Feel free to add any information you want – or to leave it blank – when prompted.</p>
-<div class="code-with-filename">
-<div class="code-with-filename-file">
-<pre><strong>Terminal</strong></pre>
-</div>
-<div class="sourceCode" id="cb15"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb15-1"><a href="#cb15-1"></a><span class="fu">sudo</span> adduser test-user</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-</div>
-<p>We want this new user to be able to adopt root privileges. Remember that the way that is determined is whether the user is part of the <code>sudo</code> group. Here’s the command you’ll need to make it so.</p>
-<div class="code-with-filename">
-<div class="code-with-filename-file">
-<pre><strong>Terminal</strong></pre>
-</div>
-<div class="sourceCode" id="cb16"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb16-1"><a href="#cb16-1"></a><span class="fu">sudo</span> usermod <span class="at">-aG</span> sudo test-user</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-</div>
-</section>
-<section id="step-3-add-an-ssh-key-for-your-user" class="level3" data-number="11.9.2">
-<h3 data-number="11.9.2" class="anchored" data-anchor-id="step-3-add-an-ssh-key-for-your-user"><span class="header-section-number">11.9.2</span> Step 3: Add an SSH Key for your user</h3>
-<p>The first thing you should do is check if you have an SSH key on your laptop. You’ll need to open a different terminal window or tab than the one that’s SSH-ed into your server and try <code>ls ~/.ssh</code>.</p>
-<p>If you’ve got one already, I’d recommend just using that key so you don’t have to mess around with multiple keys. If you don’t have one, google how to create an SSH key and do it on your laptop. If you’re not really sure what an SSH key is, I’d recommend re-reading <a href="../sec2/2-3-ssh.html">Chapter&nbsp;<span>8</span></a>.</p>
-<p>Once you’ve got an SSH key, we’re going to add it to the <code>authorized_users</code> for our user on the server.</p>
-<p>First, you need to get your public key to the server. I recommend using <code>scp</code>.<a href="#fn10" class="footnote-ref" id="fnref10" role="doc-noteref"><sup>10</sup></a></p>
-<p>You’ll need to check that your <code>SERVER_ADDRESS</code> variable is still set using <code>echo $SERVER_ADDRESS</code>. If it’s not set, you’ll have to re-set it to be the public IPv4 from your server.</p>
-<p>For me, the command looks like this</p>
-<div class="code-with-filename">
-<div class="code-with-filename-file">
-<pre><strong>Terminal</strong></pre>
-</div>
-<div class="sourceCode" id="cb17"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb17-1"><a href="#cb17-1"></a><span class="fu">scp</span> <span class="at">-i</span> ~/Documents/do4ds-lab/do4ds-lab-key.pem ~/.ssh/id_ed25519.pub ubuntu@<span class="va">$SERVER_ADDRESS</span>:/home/ubuntu </span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-</div>
-<p>You may need to change the file paths to either your server’s <code>pem</code> key or your SSH key if they’re not in the same locations as mine.</p>
-<p>Now our public key is on the server, but it’s in the <code>ubuntu</code> user’s home directory. We’re going to add it as an authorized key for the <code>test-user</code> so that we can SSH in as that user.</p>
-<p>Let’s go back to the tab that’s open to the SSH connection to our server.</p>
-<p>Here are the commands to do so:</p>
-<div class="code-with-filename">
-<div class="code-with-filename-file">
-<pre><strong>Terminal</strong></pre>
-</div>
-<div class="sourceCode" id="cb18"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb18-1"><a href="#cb18-1"></a><span class="fu">su</span> test-user <span class="co">#change user</span></span>
-<span id="cb18-2"><a href="#cb18-2"></a><span class="bu">cd</span> ~ <span class="co"># move to home directory</span></span>
-<span id="cb18-3"><a href="#cb18-3"></a><span class="fu">mkdir</span> <span class="at">-p</span> .ssh <span class="co"># create .ssh directory</span></span>
-<span id="cb18-4"><a href="#cb18-4"></a><span class="fu">sudo</span> mv /home/ubuntu/id_ed25519.pub ./.ssh <span class="co"># move key into .ssh </span></span>
-<span id="cb18-5"><a href="#cb18-5"></a><span class="fu">sudo</span> chown test-user:test-user ~/.ssh/id_ed25519.pub <span class="co"># take ownership of key</span></span>
-<span id="cb18-6"><a href="#cb18-6"></a><span class="fu">chmod</span> 700 .ssh <span class="co"># Lock directory from other users</span></span>
-<span id="cb18-7"><a href="#cb18-7"></a><span class="fu">cat</span> .ssh/id_ed25519.pub <span class="op">&gt;</span> .ssh/authorized_keys <span class="co">#add public key to end of authorized_keys file</span></span>
-<span id="cb18-8"><a href="#cb18-8"></a><span class="fu">chmod</span> 600 .ssh/authorized_keys <span class="co">#set permissions</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-</div>
-<p>Now we’re all set up with SSH, and you can log in as a normal user from your laptop just using <code>ssh test-user@$SERVER_ADDRESS</code>.</p>
-<p>If you want to set up an SSH config for this server, I’d advise waiting until we’ve got a permanent URL for it in the next chapter.</p>
-<p>Now that we’re all set up, you should store the <code>pem</code> key somewhere safe and never use it to log in again.</p>
-<p>When you ever want to exit SSH and get back to your machine, you can just type <code>exit</code>.</p>
-<div class="callout callout-style-default callout-tip callout-titled">
-<div class="callout-header d-flex align-content-center">
-<div class="callout-icon-container">
-<i class="callout-icon"></i>
-</div>
-<div class="callout-title-container flex-fill">
-Tip
-</div>
-</div>
-<div class="callout-body-container callout-body">
-<p>If you run into trouble assuming <code>sudo</code> with your new user, try exiting SSH and coming back. Sometimes these changes aren’t picked up until you restart the shell.</p>
-</div>
-</div>
-</section>
-<section id="step-4-install-r" class="level3" data-number="11.9.3">
-<h3 data-number="11.9.3" class="anchored" data-anchor-id="step-4-install-r"><span class="header-section-number">11.9.3</span> Step 4: Install R</h3>
-<p>Everything until now has been generic server administration. Now let’s get into some data-science-specific work – setting up R and Python.</p>
-<p>There are a number of ways to install R on your server including installing it from source, from the system repository, or using R-specific tooling.</p>
-<p>You can use the system repository version of R, but then you just get whatever version of R happens to be current when you run <code>sudo apt-get install R</code>. My preferred option is to use <code>rig</code>, which is an R-specific installation manager.</p>
-<div class="callout callout-style-default callout-note callout-titled">
-<div class="callout-header d-flex align-content-center">
-<div class="callout-icon-container">
-<i class="callout-icon"></i>
-</div>
-<div class="callout-title-container flex-fill">
-Note
-</div>
-</div>
-<div class="callout-body-container callout-body">
-<p>As of this writing, <code>rig</code> only supports Ubuntu. If you want to install on a different Linux distro, you will have to install R a different way.</p>
-</div>
-</div>
-<p>There are good instructions on downloading <code>rig</code> and using it to install R on the <a href="https://github.com/r-lib/rig"><code>rlib/rig</code> GitHub repo</a>. Use those instructions to install the current R release on your AWS server.</p>
-<p>Once you’ve installed R on your server, you can check that it’s running by just typing <code>R</code> into the command line. If that works, you’re good to move on to the next step.</p>
-</section>
-<section id="step-5-install-python" class="level3" data-number="11.9.4">
-<h3 data-number="11.9.4" class="anchored" data-anchor-id="step-5-install-python"><span class="header-section-number">11.9.4</span> Step 5: Install Python</h3>
-<p>It’s very likely that the version of Python on your system is old. Generally we’re going to want to install a newer Python for doing data science work, so let’s start there. As of this writing, Python 3.10 is a relatively new version of Python, so we’ll install that one.</p>
-<p>Let’s start by actually installing Python 3.10 on our system. We can do that with apt.</p>
-<div class="code-with-filename">
-<div class="code-with-filename-file">
-<pre><strong>Terminal</strong></pre>
-</div>
-<div class="sourceCode" id="cb19"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb19-1"><a href="#cb19-1"></a><span class="fu">sudo</span> apt-get install python3.10-venv</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-</div>
-<p>Once you’ve installed Python, you can check that you’ve got the right version by running</p>
-<div class="code-with-filename">
-<div class="code-with-filename-file">
-<pre><strong>Terminal</strong></pre>
-</div>
-<div class="sourceCode" id="cb20"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb20-1"><a href="#cb20-1"></a><span class="ex">python3</span> <span class="at">--version</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-</div>
-</section>
-<section id="step-5-installing-rstudio-server" class="level3" data-number="11.9.5">
-<h3 data-number="11.9.5" class="anchored" data-anchor-id="step-5-installing-rstudio-server"><span class="header-section-number">11.9.5</span> Step 5: Installing RStudio Server</h3>
-<p>Once R is installed, let’s download and install RStudio Server.</p>
-<p>I’m not going to reproduce the commands here because the RStudio Server version numbers change frequently and you probably want the most recent one.</p>
-<p>You can find the exact commands on the <a href="https://posit.co/download/rstudio-server/">Posit website</a>. Make sure to pick the version that matches your operating system. Since you’ve already installed R, you can skip down to the “Install RStudio Server” step.</p>
-<p>Once you’ve installed, you can check the status with <code>sudo systemctl status rstudio-server</code>. If there’s a line that says <code>Active: active (running)</code>, you’re good to go!</p>
-</section>
-<section id="step-6-installing-jupyerhub-jupyterlab" class="level3" data-number="11.9.6">
-<h3 data-number="11.9.6" class="anchored" data-anchor-id="step-6-installing-jupyerhub-jupyterlab"><span class="header-section-number">11.9.6</span> Step 6: Installing JupyerHub + JupyterLab</h3>
-<p>Because python is so crucial to the operation of your system <em>are</em> python programs, we’re going to want to create a standalone virtual environment for running JupyterHub.</p>
-<p>Here are the commands to create and activate a <code>jupyterhub</code> virtual environment</p>
-<div class="code-with-filename">
-<div class="code-with-filename-file">
-<pre><strong>Terminal</strong></pre>
-</div>
-<div class="sourceCode" id="cb21"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb21-1"><a href="#cb21-1"></a><span class="fu">sudo</span> python3 <span class="at">-m</span> venv /opt/jupyterhub</span>
-<span id="cb21-2"><a href="#cb21-2"></a><span class="bu">source</span> /opt/jupyterhub/bin/activate</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-</div>
-<p>Now we’re going to actually get JupyterHub up and running inside the virtual environment we just created. JupyterHub produces <a href="https://jupyterhub.readthedocs.io/en/stable/quickstart.html">docs that you can use</a> to get up and running very quickly. If you have to stop for any reason, make sure to come back, assume sudo, and start the JupyterHub virtual environment we created.</p>
-<p>Here were the installation steps that worked for me:</p>
-<div class="code-with-filename">
-<div class="code-with-filename-file">
-<pre><strong>Terminal</strong></pre>
-</div>
-<div class="sourceCode" id="cb22"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb22-1"><a href="#cb22-1"></a><span class="fu">sudo</span> su</span>
-<span id="cb22-2"><a href="#cb22-2"></a><span class="ex">apt</span> install npm nodejs</span>
-<span id="cb22-3"><a href="#cb22-3"></a><span class="ex">npm</span> install <span class="at">-g</span> configurable-http-proxy</span>
-<span id="cb22-4"><a href="#cb22-4"></a><span class="ex">python3</span> <span class="at">-m</span> pip install jupyterhub jupyterlab notebook</span>
-<span id="cb22-5"><a href="#cb22-5"></a></span>
-<span id="cb22-6"><a href="#cb22-6"></a><span class="fu">ln</span> <span class="at">-s</span> /opt/jupyterhub/bin/jupyterhub-singleuser /usr/local/bin/jupyterhub-singleuser <span class="co"># symlink in singleuser server, necessary because we're using virtual environment</span></span>
-<span id="cb22-7"><a href="#cb22-7"></a></span>
-<span id="cb22-8"><a href="#cb22-8"></a><span class="ex">jupyterhub</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-</div>
-<p>If all went well, you’ll now have JupyterHub up and running on port <code>8000</code>!</p>
-<section id="running-jupyterhub-as-a-service" class="level4" data-number="11.9.6.1">
-<h4 data-number="11.9.6.1" class="anchored" data-anchor-id="running-jupyterhub-as-a-service"><span class="header-section-number">11.9.6.1</span> Running JupyterHub as a service</h4>
-<p>As I mentioned above, JupyterHub is a Python process, not a system process. This is ok, but it means that we’ve got to remember the command to start it if we have to restart it, and that it won’t auto restart if it were to fail for any reason.</p>
-<p>A program that runs in the background on a machine, starting automatically, and controlled by <code>systemctl</code> is called a <em>daemon</em>. Since we want JupyterHub to be a daemon, we’re got to add it as a system daemon, which isn’t hard.</p>
-<p>We don’t need it right now, but it’ll be easier to manage JupyterHub later on from a config file that’s in <code>/etc/jupyterhub</code>.</p>
-<p>Let’s create a default config file and move it into the right place using</p>
-<div class="code-with-filename">
-<div class="code-with-filename-file">
-<pre><strong>Terminal</strong></pre>
-</div>
-<div class="sourceCode" id="cb23"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb23-1"><a href="#cb23-1"></a><span class="fu">sudo</span> su</span>
-<span id="cb23-2"><a href="#cb23-2"></a><span class="bu">source</span> /opt/jupyterhub/bin/activate</span>
-<span id="cb23-3"><a href="#cb23-3"></a><span class="ex">jupyterhub</span> <span class="at">--generate-config</span></span>
-<span id="cb23-4"><a href="#cb23-4"></a><span class="fu">mkdir</span> <span class="at">-p</span> /etc/jupyterhub</span>
-<span id="cb23-5"><a href="#cb23-5"></a><span class="fu">mv</span> jupyterhub_config.py /etc/jupyterhub</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-</div>
-<p>Now we’ve got to daemon-ize JupterHub. There are two steps – create a file describing the service for the server’s daemon, and then start the service.</p>
-<p>To start with, end the existing JupyterHub process. If you’ve still got that terminal open, you can do so with <code>ctrl</code> + <code>c</code>. If not, you can use your <code>ps aux</code> and <code>grep</code> skills to find and kill the JupyterHub processes.</p>
-<p>On Ubuntu, adding a daemon file uses a tool called <code>systemd</code> and is really straightforward.</p>
-<p>First, add the following to <code>/etc/systemd/system/jupyterhub.service</code>. If you’re reading this book in hard copy, you can go to the online version to copy/paste or get this file on the book’s Git repo at TODO.</p>
-<div class="code-with-filename">
-<div class="code-with-filename-file">
-<pre><strong>/etc/systemd/system/jupyterhub.service</strong></pre>
-</div>
-<div class="sourceCode" id="cb24"><pre class="sourceCode numberSource yaml number-lines code-with-copy"><code class="sourceCode yaml"><span id="cb24-1"><a href="#cb24-1"></a><span class="kw">[</span><span class="at">Unit</span><span class="kw">]</span></span>
-<span id="cb24-2"><a href="#cb24-2"></a><span class="at">Description=Jupyterhub</span></span>
-<span id="cb24-3"><a href="#cb24-3"></a><span class="at">After=syslog.target network.target</span></span>
-<span id="cb24-4"><a href="#cb24-4"></a></span>
-<span id="cb24-5"><a href="#cb24-5"></a><span class="kw">[</span><span class="at">Service</span><span class="kw">]</span></span>
-<span id="cb24-6"><a href="#cb24-6"></a><span class="at">User=root</span></span>
-<span id="cb24-7"><a href="#cb24-7"></a><span class="at">Environment="PATH=/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/opt/jupyterhub/bin"</span></span>
-<span id="cb24-8"><a href="#cb24-8"></a><span class="at">ExecStart=/opt/jupyterhub/bin/jupyterhub -f /etc/jupyterhub/jupyterhub_config.py</span></span>
-<span id="cb24-9"><a href="#cb24-9"></a></span>
-<span id="cb24-10"><a href="#cb24-10"></a><span class="kw">[</span><span class="at">Install</span><span class="kw">]</span></span>
-<span id="cb24-11"><a href="#cb24-11"></a><span class="at">WantedBy=multi-user.target</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-</div>
-<p>Hopefully this file is pretty easy to parse. Two things to notice – the <code>Environment</code> line adds <code>/opt/jupyterhub/bin</code> to the path – that’s where our virtual environment is.</p>
-<p>Second, the <code>ExecStart</code> line is the startup command and includes our <code>-f /etc/jupyterhub/jupyterhub_config.py</code> – this is the command to start JupyterHub with the config we created a few seconds ago.</p>
-<p>Now we just need to reload the daemon tool so it picks up the new service it has available and start JupyterHub!</p>
-<div class="code-with-filename">
-<div class="code-with-filename-file">
-<pre><strong>Terminal</strong></pre>
-</div>
-<div class="sourceCode" id="cb25"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb25-1"><a href="#cb25-1"></a><span class="ex">systemctl</span> daemon-reload</span>
-<span id="cb25-2"><a href="#cb25-2"></a><span class="ex">systemctl</span> start jupyterhub</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-</div>
-<p>You should now be able to see that JupyterHub is running using <code>systemctl status jupyterhub</code> and can see it again by tunneling to it.</p>
-<p>To set JupyterHub to automatically restart when the server restarts, run <code>systemctl enable jupyterhub</code>.</p>
-</section>
-</section>
-<section id="step-7-running-a-plumber-api-in-a-container" class="level3" data-number="11.9.7">
-<h3 data-number="11.9.7" class="anchored" data-anchor-id="step-7-running-a-plumber-api-in-a-container"><span class="header-section-number">11.9.7</span> Step 7: Running a Plumber API in a Container</h3>
-<p>In addition to running a development workbench on your server, you might want to run a data science project. If you’re running a Shiny app, Shiny Server is easy to configure along the lines of RStudio Server.</p>
-<p>However, if you put an API in a container like we did in <a href="../sec2/2-4-docker.html">Chapter&nbsp;<span>9</span></a>, you might want to deploy that somewhere on your server as a running container.</p>
-<p>The first step is to install docker on your system with <code>sudo apt-get install docker.io</code>. You can check that you can run docker with <code>docker ps</code>. You may need to adopt <code>sudo</code> privileges to do so.</p>
-<p>Once we have docker installed, getting the API running is almost trivially easy using the command we used back in <a href="../sec2/2-4-docker.html">Chapter&nbsp;<span>9</span></a> to run our container.</p>
-<div class="code-with-filename">
-<div class="code-with-filename-file">
-<pre><strong>Terminal</strong></pre>
-</div>
-<div class="sourceCode" id="cb26"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb26-1"><a href="#cb26-1"></a><span class="fu">sudo</span> docker run <span class="at">--rm</span> <span class="at">-d</span> <span class="dt">\</span></span>
-<span id="cb26-2"><a href="#cb26-2"></a>  <span class="at">-p</span> 8080:8080 <span class="dt">\</span></span>
-<span id="cb26-3"><a href="#cb26-3"></a>  <span class="at">--name</span> penguin-model <span class="dt">\</span></span>
-<span id="cb26-4"><a href="#cb26-4"></a>  alexkgold/penguin-model</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-</div>
-<p>The one change you might note is that I’ve changed the port on the server to be 8080, since we already have JupyterHub running on 8000.</p>
-<p>Once it’s up, you can check that it’s running with <code>docker ps</code>.</p>
-<p>This is why people love docker – it’s wildly easy to get something simple running. But getting Docker hardened for production takes a bit more work.</p>
-<p>The first thing to notice is that there’s no auth on our API. Anyone can hit this API as much as they want if they have the URL. Needless to say, this is not a security best practice unless you intend to host a public service.</p>
-<p>The other issue is that we haven’t daemonized the API. If we restart the server or the container dies for any reason, it won’t auto-restart.</p>
-<p>It’s not generally a best practice to daemon-ize a docker container by just putting the <code>run</code> command into <code>systemd</code>. Instead, you should use a container management system that is designed specifically to manage running containers, like Docker Compose or Kubernetes. Getting deeper into those systems is beyond the scope of this book.</p>
-</section>
-<section id="step-8-putting-up-the-shiny-app" class="level3" data-number="11.9.8">
-<h3 data-number="11.9.8" class="anchored" data-anchor-id="step-8-putting-up-the-shiny-app"><span class="header-section-number">11.9.8</span> Step 8: Putting up the Shiny app</h3>
-<p>Install Shiny Server using the instructions from the <a href="https://docs.posit.co/shiny-server/#getting-started">Admin Guide</a>. Note that you don’t need to install R, as we’ve already done that, and you don’t need to install <code>{shiny}</code>, as we’re going to use <code>{renv}</code>.</p>
-<p>TODO</p>
-<p>Edit <code>/etc/shiny-server/shiny-server.conf</code> to run the right app – may have to edit user.</p>
-<div class="code-with-filename">
-<div class="code-with-filename-file">
-<pre><strong>/etc/shiny-server/shiny-server.conf</strong></pre>
-</div>
-<div class="sourceCode" id="cb27"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb27-1"><a href="#cb27-1"></a><span class="co"># Instruct Shiny Server to run applications as the user "shiny"</span></span>
-<span id="cb27-2"><a href="#cb27-2"></a><span class="ex">run_as</span> test-user<span class="kw">;</span></span>
-<span id="cb27-3"><a href="#cb27-3"></a></span>
-<span id="cb27-4"><a href="#cb27-4"></a><span class="co"># Define a server that listens on port 3838</span></span>
-<span id="cb27-5"><a href="#cb27-5"></a><span class="ex">server</span> {</span>
-<span id="cb27-6"><a href="#cb27-6"></a>  <span class="ex">listen</span> 3838<span class="kw">;</span></span>
-<span id="cb27-7"><a href="#cb27-7"></a></span>
-<span id="cb27-8"><a href="#cb27-8"></a>  <span class="co"># Define a location at the base URL</span></span>
-<span id="cb27-9"><a href="#cb27-9"></a>  <span class="ex">location</span> / {</span>
-<span id="cb27-10"><a href="#cb27-10"></a></span>
-<span id="cb27-11"><a href="#cb27-11"></a>    <span class="co"># Host the directory of Shiny Apps stored in this directory</span></span>
-<span id="cb27-12"><a href="#cb27-12"></a>    <span class="ex">site_dir</span> /home/test-user/do4ds-lab/app<span class="kw">;</span></span>
-<span id="cb27-13"><a href="#cb27-13"></a></span>
-<span id="cb27-14"><a href="#cb27-14"></a>    <span class="co"># Log all Shiny output to files in this directory</span></span>
-<span id="cb27-15"><a href="#cb27-15"></a>    <span class="ex">log_dir</span> /var/log/shiny-server<span class="kw">;</span></span>
-<span id="cb27-16"><a href="#cb27-16"></a></span>
-<span id="cb27-17"><a href="#cb27-17"></a>    <span class="co"># When a user visits the base URL rather than a particular application,</span></span>
-<span id="cb27-18"><a href="#cb27-18"></a>    <span class="co"># an index of the applications available in this directory will be shown.</span></span>
-<span id="cb27-19"><a href="#cb27-19"></a>    <span class="ex">directory_index</span> off<span class="kw">;</span></span>
-<span id="cb27-20"><a href="#cb27-20"></a>  <span class="er">}</span></span>
-<span id="cb27-21"><a href="#cb27-21"></a><span class="er">}</span></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-</div>
-<p>Start Shiny Server</p>
-</section>
-<section id="step-8-check-it-all-out" class="level3" data-number="11.9.9">
-<h3 data-number="11.9.9" class="anchored" data-anchor-id="step-8-check-it-all-out"><span class="header-section-number">11.9.9</span> Step 8: Check it all out</h3>
-<p>Just knowing that all of our services are running isn’t nearly as fun as actually trying them out.</p>
-<p>We don’t have a stable public URL for the server yet, so we can’t just access it from our browser. This is a perfect use case for an SSH tunnel.</p>
-<p>TODO: picture of server w/ RStudio on 8787, JupyterHub on 8000, and Palmer Penguin container on 8080.</p>
-<p>If you recall, the command for an SSH tunnel from a remote server to <code>localhost</code> is to do <code>ssh -L &lt;remote port&gt;:localhost:&lt;local port&gt; &lt;user&gt;@&lt;server&gt;</code>.</p>
-<p>We’ve got three services running on our server, RStudio Server at <code>8787</code>, JupyterHub on <code>8000</code>, and our Plumber API on <code>8080</code>. You can try each of them out by subbing those in for the remote port and putting them at a local port. I’d recommend just using the same one.</p>
-<p>For example, by running <code>ssh -L 8787:localhost:8787 test-user@$SERVER_ADDRESS</code>, I can visit RStudio Server in my browser at <code>localhost:8787</code> and login with the username <code>test-user</code> and password I set on the server.</p>
-
-
-</section>
-</section>
-<section id="footnotes" class="footnotes footnotes-end-of-document" role="doc-endnotes">
-<hr>
-<ol>
-<li id="fn1"><p>Or at least they weren’t supposed to. There’s an interesting history of lawsuits around the BSD operating system including Unix code. BSD is a Unix clone that was the predecessor of MacOS.<a href="#fnref1" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
-<li id="fn2"><p>Check out the <a href="https://en.wikipedia.org/wiki/History_of_Linux">History of Linux Wikipedia article</a> for the posting.</p>
-<p>Pedants will scream that the original release of Linux was just the operating system <em>kernel</em>, not a full operating system like Unix. Duly noted, now go away.<a href="#fnref2" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
-<li id="fn3"><p>The remainder are almost entirely Windows servers. There are a few other Unix-like systems that you might encounter, like Oracle Solaris. There is no MacOS server. There is a product called <em>Mac Server</em>, but it’s just a program for managing Mac desktops and iOS devices.<a href="#fnref3" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
-<li id="fn4"><p>CentOS (short for Community ENTerprise Operating System) is an open source operating system maintained by Red Hat. The relationship between RHEL and CentOS is changing. The details are somewhat complicated, but most people expect less adoption of CentOS in enterprise settings going forward.<a href="#fnref4" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
-<li id="fn5"><p>My goal here is to be useful not precise, so I’m intermingling <code>bash</code> commands and Linux system commands because they’re useful. If you know the difference and are pedantic enough to care, this list isn’t for you anyway.<a href="#fnref5" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
-<li id="fn6"><p>Depending on your version of Linux, there <em>may</em> be a limit of 16 groups per user.<a href="#fnref6" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
-<li id="fn7"><p>You can generally ignore the number, which is the number of links to the file.<a href="#fnref7" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
-<li id="fn8"><p>Clever eyes may realize that this is just the base-10 representation of a three-digit binary number.<a href="#fnref8" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
-<li id="fn9"><p>This is another one where you’ll almost never use <code>ps</code> without <code>aux</code>.<a href="#fnref9" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
-<li id="fn10"><p>Alternatively, you could open a file of the right name and just copy/paste the contents of your public key in there. Either way works.<a href="#fnref10" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
-</ol>
-</section>
-
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diff --git a/chapters/sec4/4-3-auth.html b/chapters/sec3/3-3-auth.html
similarity index 90%
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rename to chapters/sec3/3-3-auth.html
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-<title>DevOps for Data Science - 18&nbsp; Auth in Enterprise</title>
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-<link href="../../chapters/sec4/4-2-ent-networks.html" rel="prev">
+<link href="../../chapters/sec3/3-4-ent-servers.html" rel="next">
+<link href="../../chapters/sec3/3-2-ent-networks.html" rel="prev">
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-      <nav class="quarto-page-breadcrumbs" aria-label="breadcrumb"><ol class="breadcrumb"><li class="breadcrumb-item"><a href="../../chapters/sec4/4-0-sec-intro.html">Making it Enterprise-Grade</a></li><li class="breadcrumb-item"><a href="../../chapters/sec4/4-3-auth.html"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></a></li></ol></nav>
+      <nav class="quarto-page-breadcrumbs" aria-label="breadcrumb"><ol class="breadcrumb"><li class="breadcrumb-item"><a href="../../chapters/sec3/3-0-sec-intro.html">Making it Enterprise-Grade</a></li><li class="breadcrumb-item"><a href="../../chapters/sec3/3-3-auth.html"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></a></li></ol></nav>
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@@ -177,13 +177,19 @@
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  <span class="menu-text"><span class="chapter-number">5</span>&nbsp; <span class="chapter-title">Deployments and code promotion</span></span></a>
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+</li>
+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/sec1/1-6-docker.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">6</span>&nbsp; <span class="chapter-title">Demystifying Docker</span></span></a>
+  </div>
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- <span class="menu-text">IT/Admin Tools</span></a>
+ <span class="menu-text">IT/Admin for Data Science</span></a>
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- <span class="menu-text"><span class="chapter-number">6</span>&nbsp; <span class="chapter-title">Opening the Command Line</span></span></a>
+  <a href="../../chapters/sec2/2-1-cloud.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">7</span>&nbsp; <span class="chapter-title">The Cloud</span></span></a>
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- <span class="menu-text"><span class="chapter-number">7</span>&nbsp; <span class="chapter-title">Using the Command Line</span></span></a>
+  <a href="../../chapters/sec2/2-2-cmd-line.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">8</span>&nbsp; <span class="chapter-title">Customizing the command line</span></span></a>
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-  <a href="../../chapters/sec2/2-3-ssh.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">8</span>&nbsp; <span class="chapter-title">Secure server connections with SSH</span></span></a>
+  <a href="../../chapters/sec2/2-3-linux.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">9</span>&nbsp; <span class="chapter-title">Intro to Linux Administration</span></span></a>
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-  <a href="../../chapters/sec2/2-4-docker.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">9</span>&nbsp; <span class="chapter-title">Demystifying Docker</span></span></a>
+  <a href="../../chapters/sec2/2-4-app-admin.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Application administration</span></span></a>
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-        <li class="sidebar-item sidebar-item-section">
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-            <a href="../../chapters/sec3/3-0-sec-intro.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text">IT/Admin for Data Science</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-3" aria-expanded="true" aria-label="Toggle section">
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-  <a href="../../chapters/sec3/3-1-cloud.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Getting Started with the Cloud</span></span></a>
+  <a href="../../chapters/sec2/2-5-scale.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Server Resources and Scaling</span></span></a>
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   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-2-linux-admin.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Basic Linux SysAdmin</span></span></a>
-  </div>
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-          <li class="sidebar-item">
-  <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-3-networking.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-6-networking.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">12</span>&nbsp; <span class="chapter-title">Intro to Computer Networks</span></span></a>
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           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-4-dns.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-7-dns.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">13</span>&nbsp; <span class="chapter-title">DNS allows for human-readable addresses</span></span></a>
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 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-5-ssl.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-8-ssl.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">14</span>&nbsp; <span class="chapter-title">You should use SSL/HTTPS</span></span></a>
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-  <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-6-servers.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Choosing the right server for you</span></span></a>
-  </div>
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-            <a href="../../chapters/sec4/4-0-sec-intro.html" class="sidebar-item-text sidebar-link">
+            <a href="../../chapters/sec3/3-0-sec-intro.html" class="sidebar-item-text sidebar-link">
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-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true" aria-label="Toggle section">
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-      <ul id="quarto-sidebar-section-4" class="collapse list-unstyled sidebar-section depth1 show">  
+      <ul id="quarto-sidebar-section-3" class="collapse list-unstyled sidebar-section depth1 show">  
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   <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec4/4-1-os-ds-in-ent.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></a>
+  <a href="../../chapters/sec3/3-1-os-ds-in-ent.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></a>
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-  <a href="../../chapters/sec4/4-2-ent-networks.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></a>
+  <a href="../../chapters/sec3/3-2-ent-networks.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></a>
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-  <a href="../../chapters/sec4/4-3-auth.html" class="sidebar-item-text sidebar-link active">
- <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></a>
+  <a href="../../chapters/sec3/3-3-auth.html" class="sidebar-item-text sidebar-link active">
+ <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></a>
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-  <a href="../../chapters/sec4/4-4-ent-servers.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">19</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></a>
+  <a href="../../chapters/sec3/3-4-ent-servers.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></a>
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-            <a class="sidebar-item-text sidebar-link text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-5" aria-expanded="true">
+            <a class="sidebar-item-text sidebar-link text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true">
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+          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true" aria-label="Toggle section">
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-      <ul id="quarto-sidebar-section-5" class="collapse list-unstyled sidebar-section depth1 show">  
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+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/append/cheatsheets.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">C</span>&nbsp; <span class="chapter-title">Cheatsheets</span></span></a>
+  </div>
 </li>
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@@ -330,27 +319,27 @@
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+  <li><a href="#how-itadmins-think-about-auth" id="toc-how-itadmins-think-about-auth" class="nav-link active" data-scroll-target="#how-itadmins-think-about-auth"><span class="header-section-number">17.1</span> How IT/Admins think about auth</a>
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-  <li><a href="#single-sign-on-sso" id="toc-single-sign-on-sso" class="nav-link" data-scroll-target="#single-sign-on-sso"><span class="header-section-number">18.1.2</span> Single Sign On (SSO)</a></li>
-  <li><a href="#managing-permissions" id="toc-managing-permissions" class="nav-link" data-scroll-target="#managing-permissions"><span class="header-section-number">18.1.3</span> Managing permissions</a></li>
+  <li><a href="#centralizing-user-management-with-ldapad" id="toc-centralizing-user-management-with-ldapad" class="nav-link" data-scroll-target="#centralizing-user-management-with-ldapad"><span class="header-section-number">17.1.1</span> Centralizing user management with LDAP/AD</a></li>
+  <li><a href="#single-sign-on-sso" id="toc-single-sign-on-sso" class="nav-link" data-scroll-target="#single-sign-on-sso"><span class="header-section-number">17.1.2</span> Single Sign On (SSO)</a></li>
+  <li><a href="#managing-permissions" id="toc-managing-permissions" class="nav-link" data-scroll-target="#managing-permissions"><span class="header-section-number">17.1.3</span> Managing permissions</a></li>
   </ul></li>
-  <li><a href="#data-science-auth-concerns" id="toc-data-science-auth-concerns" class="nav-link" data-scroll-target="#data-science-auth-concerns"><span class="header-section-number">18.2</span> Data Science Auth Concerns</a>
+  <li><a href="#data-science-auth-concerns" id="toc-data-science-auth-concerns" class="nav-link" data-scroll-target="#data-science-auth-concerns"><span class="header-section-number">17.2</span> Data Science Auth Concerns</a>
   <ul class="collapse">
-  <li><a href="#data-access" id="toc-data-access" class="nav-link" data-scroll-target="#data-access"><span class="header-section-number">18.2.1</span> Data Access</a></li>
-  <li><a href="#service-accounts" id="toc-service-accounts" class="nav-link" data-scroll-target="#service-accounts"><span class="header-section-number">18.2.2</span> Service Accounts</a></li>
+  <li><a href="#data-access" id="toc-data-access" class="nav-link" data-scroll-target="#data-access"><span class="header-section-number">17.2.1</span> Data Access</a></li>
+  <li><a href="#service-accounts" id="toc-service-accounts" class="nav-link" data-scroll-target="#service-accounts"><span class="header-section-number">17.2.2</span> Service Accounts</a></li>
   </ul></li>
-  <li><a href="#comprehension-questions" id="toc-comprehension-questions" class="nav-link" data-scroll-target="#comprehension-questions"><span class="header-section-number">18.3</span> Comprehension Questions</a></li>
+  <li><a href="#comprehension-questions" id="toc-comprehension-questions" class="nav-link" data-scroll-target="#comprehension-questions"><span class="header-section-number">17.3</span> Comprehension Questions</a></li>
   </ul>
-<div class="toc-actions"><div><i class="bi bi-github"></i></div><div class="action-links"><p><a href="https://github.com/akgold/do4ds/edit/main/chapters/sec4/4-3-auth.qmd" class="toc-action">Edit this page</a></p></div></div></nav>
+<div class="toc-actions"><div><i class="bi bi-github"></i></div><div class="action-links"><p><a href="https://github.com/akgold/do4ds/edit/main/chapters/sec3/3-3-auth.qmd" class="toc-action">Edit this page</a></p></div></div></nav>
     </div>
 <!-- main -->
 <main class="content" id="quarto-document-content">
 
 <header id="title-block-header" class="quarto-title-block default">
 <div class="quarto-title">
-<h1 class="title"><span id="sec-auth" class="quarto-section-identifier"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></h1>
+<h1 class="title"><span id="sec-auth" class="quarto-section-identifier"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></h1>
 </div>
 
 
@@ -384,8 +373,8 @@ <h1 class="title"><span id="sec-auth" class="quarto-section-identifier"><span cl
 <p>This chapter is mostly conceptual. There’s a lot more detail on the technical details of the different technologies used to accomplish these goals in <a href="../append/auth.html">Appendix&nbsp;<span>A</span></a>.</p>
 </div>
 </div>
-<section id="how-itadmins-think-about-auth" class="level2" data-number="18.1">
-<h2 data-number="18.1" class="anchored" data-anchor-id="how-itadmins-think-about-auth"><span class="header-section-number">18.1</span> How IT/Admins think about auth</h2>
+<section id="how-itadmins-think-about-auth" class="level2" data-number="17.1">
+<h2 data-number="17.1" class="anchored" data-anchor-id="how-itadmins-think-about-auth"><span class="header-section-number">17.1</span> How IT/Admins think about auth</h2>
 <p>Let’s start with an analogy to the real world. Imagine all the different services your company’s IT/Admin team manages as rooms in a building. Email, databases, data science workbenches, social media accounts, HR systems, and more. Each one is a room in the building.</p>
 <p>In order to comply with the principle of least privilege, people are given access only to the rooms they need. Now imagine you’re the one who has to figure out how to keep it all secure.</p>
 <p>When someone tries to enter a room, you’ll need a way to know who’s asking – to ascertain and validate their identity. This process is called <em>authentication</em>.</p>
@@ -399,8 +388,8 @@ <h2 data-number="18.1" class="anchored" data-anchor-id="how-itadmins-think-about
 <p>In the labs in section 3, this is how we configured our server. We created a standalone server with standalone credentials. And while that’s secure enough on its own, it doesn’t integrate with any central IT/Admin capabilities.</p>
 <p>Obviously, among enterprise organizations, this pattern doesn’t fly. If you’re only a team of 20 and you have 5 systems, it’s ok to metaphorically run around to each room. But a team of 2,000 or 20,000 with 50 or 500 systems can’t be managed this way.</p>
 <p>So let’s start thinking about how we could make the management of this system simpler and easier.</p>
-<section id="centralizing-user-management-with-ldapad" class="level3" data-number="18.1.1">
-<h3 data-number="18.1.1" class="anchored" data-anchor-id="centralizing-user-management-with-ldapad"><span class="header-section-number">18.1.1</span> Centralizing user management with LDAP/AD</h3>
+<section id="centralizing-user-management-with-ldapad" class="level3" data-number="17.1.1">
+<h3 data-number="17.1.1" class="anchored" data-anchor-id="centralizing-user-management-with-ldapad"><span class="header-section-number">17.1.1</span> Centralizing user management with LDAP/AD</h3>
 <p>The first thing would be to standardize on a single set of credentials. No more letting each guard issue their own. You’ll create a central security booth where you’ll manage all the credentials. Whenever someone approaches a door, the guard will radio in the credential, you’ll verify that all is well and tell the guard, “yep, that’s Heather!”</p>
 <p>This makes life easier for someone using the system since they have only one set of credentials. It’s also somewhat more secure. We know now that all of the doors are using a similar level of security and if someone loses their card or gets it stolen, we just have to do one trade.</p>
 <p>This is basically the situation that many companies have been in from the mid 1990s onwards and many still use.</p>
@@ -415,8 +404,8 @@ <h3 data-number="18.1.1" class="anchored" data-anchor-id="centralizing-user-mana
 <p>Wouldn’t it be nice if there were a way to solve all these problems? A solution would allow for centralized authorization, never sharing credentials with the guards, and authenticating only once.</p>
 <p>Enter the world of Single-Sign On (SSO).</p>
 </section>
-<section id="single-sign-on-sso" class="level3" data-number="18.1.2">
-<h3 data-number="18.1.2" class="anchored" data-anchor-id="single-sign-on-sso"><span class="header-section-number">18.1.2</span> Single Sign On (SSO)</h3>
+<section id="single-sign-on-sso" class="level3" data-number="17.1.2">
+<h3 data-number="17.1.2" class="anchored" data-anchor-id="single-sign-on-sso"><span class="header-section-number">17.1.2</span> Single Sign On (SSO)</h3>
 <p>Ok, so let’s revamp the system one more time.</p>
 <p>Now, when someone enters the building, they’ll stop at the central security office and provide their credentials. In exchange, they’ll get a building access pass that’s unique to them and they cannot share.</p>
 <p>Moreover, you’ll equip each room with a machine to swipe a building access pass. Swiping the access pass sends a request back to the central security office with the person’s name and the room number. You can check whether they’re allowed in and send back the allow signal if so and the red disallow signal if not.</p>
@@ -430,8 +419,8 @@ <h3 data-number="18.1.2" class="anchored" data-anchor-id="single-sign-on-sso"><s
 <p>These days, almost all enterprises are moving quickly towards implementing SSO using either SAML or OAuth (or both).</p>
 <p>There’s a lot more detail on the technical details of how LDAP, OAuth, SAML, and more work in <a href="../append/auth.html">Appendix&nbsp;<span>A</span></a>.</p>
 </section>
-<section id="managing-permissions" class="level3" data-number="18.1.3">
-<h3 data-number="18.1.3" class="anchored" data-anchor-id="managing-permissions"><span class="header-section-number">18.1.3</span> Managing permissions</h3>
+<section id="managing-permissions" class="level3" data-number="17.1.3">
+<h3 data-number="17.1.3" class="anchored" data-anchor-id="managing-permissions"><span class="header-section-number">17.1.3</span> Managing permissions</h3>
 <p>Irrespective of what kind of auth technology you’re using, you have to actually manage permissions somehow. It’s worth learning a little about the options.</p>
 <p>The simplest option is just to maintain a list of who’s allowed to enter each room. This is called an Access Control List (ACL).<a href="#fn5" class="footnote-ref" id="fnref5" role="doc-noteref"><sup>5</sup></a></p>
 <p>ACLs are a simple kind of permissions management that make a lot of intuitive sense.</p>
@@ -446,12 +435,12 @@ <h3 data-number="18.1.3" class="anchored" data-anchor-id="managing-permissions">
 <p>The most well-known ABAC system is the AWS Identity and Access Management (IAM) system. If you’ve ever been utterly befuddled by applying permissions to resources in AWS, you can thank the complexity of ABAC. That complexity is the tradeoff for the very high degree of flexibility ABAC provides.</p>
 </section>
 </section>
-<section id="data-science-auth-concerns" class="level2" data-number="18.2">
-<h2 data-number="18.2" class="anchored" data-anchor-id="data-science-auth-concerns"><span class="header-section-number">18.2</span> Data Science Auth Concerns</h2>
+<section id="data-science-auth-concerns" class="level2" data-number="17.2">
+<h2 data-number="17.2" class="anchored" data-anchor-id="data-science-auth-concerns"><span class="header-section-number">17.2</span> Data Science Auth Concerns</h2>
 <p>The first and simplest concern that comes up for a new data science workbench is that it needs to support whatever auth mechanism your IT/Admin group has decided your organization is going to use. Hopefully you now have some context on what those various mechanisms are.</p>
 <p>These days, most data science tools you might want to use support all of the standard SSO mechanisms – though many of them reserve that functionality for paid tiers.</p>
-<section id="data-access" class="level3" data-number="18.2.1">
-<h3 data-number="18.2.1" class="anchored" data-anchor-id="data-access"><span class="header-section-number">18.2.1</span> Data Access</h3>
+<section id="data-access" class="level3" data-number="17.2.1">
+<h3 data-number="17.2.1" class="anchored" data-anchor-id="data-access"><span class="header-section-number">17.2.1</span> Data Access</h3>
 <p>The second concern that comes up is how to get access to data. In our building metaphor, this would be like sending a note from one room asking for a resource in another room.</p>
 <p>This kind of access is actually <em>easier</em> to configure in a non-SSO configuration. If your database can be accessed with a username and password, it’s the equivalent of being able to just put your request on a piece of paper and append your credentials. The guard can verify the credentials and send back the proper information.</p>
 <p>It’s worth noting that this configuration is still quite common. Most organizations have implemented SSO for their external-facing services, but internal data sources are often available with username and password auth. This is mostly because relatively few databases have implemented SSO configurations. I expect this will change quickly in the next few years.</p>
@@ -464,8 +453,8 @@ <h3 data-number="18.2.1" class="anchored" data-anchor-id="data-access"><span cla
 <p>The last way to access a data source seamlessly is via integration with cloud IAM services. This will only work if you’re trying to access a cloud resource from another cloud resource. So you could allow access from an EC2 instance to an S3 bucket, but not from your on-prem compute cluster to an S3 bucket.</p>
 <p>The patterns for doing this vary a lot by cloud and by the data science tooling you’re using. Configuring a cloud instance to “just know” who’s making a request is possible, but requires some savvy with managing cloud services.</p>
 </section>
-<section id="service-accounts" class="level3" data-number="18.2.2">
-<h3 data-number="18.2.2" class="anchored" data-anchor-id="service-accounts"><span class="header-section-number">18.2.2</span> Service Accounts</h3>
+<section id="service-accounts" class="level3" data-number="17.2.2">
+<h3 data-number="17.2.2" class="anchored" data-anchor-id="service-accounts"><span class="header-section-number">17.2.2</span> Service Accounts</h3>
 <p>The last concern that comes up a lot is what entity is doing the access. In workbench environments, it’s common for humans to have credentials to data sources and to login as themselves. However, when those resources go to production, it’s very common to introduce <em>service accounts</em>.</p>
 <p>A service account is a non-human entity that has permissions of its own. For example, maybe you’ve got a Shiny app that users use to visualize data that’s in a database. Very often, you don’t want the app to have the same permisions as the app’s author, or to inherit the permissions of the people viewing the app.</p>
 <p>One important reason you might want this is that you want to manage the permissions of the app itself even if the author were to leave the company or change roles.</p>
@@ -473,8 +462,8 @@ <h3 data-number="18.2.2" class="anchored" data-anchor-id="service-accounts"><spa
 <p>There’s no particular magic to service accounts, but you’ll need to figure out how to make your app or report run as the right user and have the correct service account credentials.</p>
 </section>
 </section>
-<section id="comprehension-questions" class="level2" data-number="18.3">
-<h2 data-number="18.3" class="anchored" data-anchor-id="comprehension-questions"><span class="header-section-number">18.3</span> Comprehension Questions</h2>
+<section id="comprehension-questions" class="level2" data-number="17.3">
+<h2 data-number="17.3" class="anchored" data-anchor-id="comprehension-questions"><span class="header-section-number">17.3</span> Comprehension Questions</h2>
 <ol type="1">
 <li>What is the difference between authentication and authorization?</li>
 <li>What are some different ways to manage permissions? What are the advantages and drawbacks of each?</li>
@@ -491,7 +480,7 @@ <h2 data-number="18.3" class="anchored" data-anchor-id="comprehension-questions"
 <li id="fn2"><p>XML is a markup language, much like HTML. The good thing about XML is that it’s very flexible. The bad thing is that it’s relatively hard for a human to easily read.<a href="#fnref2" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
 <li id="fn3"><p>Technically, OIDC is an authentication standard and OAuth is an authorization standard. You’ll usually just hear it all referred to as OAuth.<a href="#fnref3" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
 <li id="fn4"><p>Yes, AAD is used for SAML/OAuth, not for LDAP. It’s confusing.<a href="#fnref4" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
-<li id="fn5"><p>Standard Linux permissions (POSIX permissons) that were discussed in <a href="../sec3/3-2-linux-admin.html">Chapter&nbsp;<span>11</span></a> are basically a special case of ACLs. ACLs allow setting individual-level permissions for any number of users and groups, as opposed to the one owner, one group, and everyone else permissions set for POSIX.</p>
+<li id="fn5"><p>Standard Linux permissions (POSIX permissons) that were discussed in <a href="../sec2/2-3-linux.html">Chapter&nbsp;<span>9</span></a> are basically a special case of ACLs. ACLs allow setting individual-level permissions for any number of users and groups, as opposed to the one owner, one group, and everyone else permissions set for POSIX.</p>
 <p>Linux distros now have support for ACLs on top of the standard POSIX permissions.<a href="#fnref5" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
 </ol>
 </section>
@@ -732,13 +721,13 @@ <h2 data-number="18.3" class="anchored" data-anchor-id="comprehension-questions"
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+      <a href="../../chapters/sec3/3-2-ent-networks.html" class="pagination-link">
+        <i class="bi bi-arrow-left-short"></i> <span class="nav-page-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span>
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-  <li><a href="#tcpip-and-the-mail" id="toc-tcpip-and-the-mail" class="nav-link active" data-scroll-target="#tcpip-and-the-mail"><span class="header-section-number">12.1</span> TCP/IP and the mail</a></li>
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-  <li><a href="#how-packets-are-routed" id="toc-how-packets-are-routed" class="nav-link" data-scroll-target="#how-packets-are-routed"><span class="header-section-number">12.4</span> How packets are routed</a></li>
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-  <li><a href="#reserved-ip-addresses" id="toc-reserved-ip-addresses" class="nav-link" data-scroll-target="#reserved-ip-addresses"><span class="header-section-number">12.5.1</span> Reserved IP Addresses</a></li>
-  </ul></li>
-  <li><a href="#basic-network-troubleshooting" id="toc-basic-network-troubleshooting" class="nav-link" data-scroll-target="#basic-network-troubleshooting"><span class="header-section-number">12.6</span> Basic network troubleshooting</a></li>
-  <li><a href="#comprehension-questions" id="toc-comprehension-questions" class="nav-link" data-scroll-target="#comprehension-questions"><span class="header-section-number">12.7</span> Comprehension Questions</a></li>
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-  <li><a href="#step-1-configure-nginx" id="toc-step-1-configure-nginx" class="nav-link" data-scroll-target="#step-1-configure-nginx"><span class="header-section-number">12.8.1</span> Step 1: Configure Nginx</a></li>
-  <li><a href="#step-2-open-port-80" id="toc-step-2-open-port-80" class="nav-link" data-scroll-target="#step-2-open-port-80"><span class="header-section-number">12.8.2</span> Step 2: Open port 80</a></li>
-  <li><a href="#step-3-configure-rstudio-server-and-jupyterhub-to-be-on-a-subpath" id="toc-step-3-configure-rstudio-server-and-jupyterhub-to-be-on-a-subpath" class="nav-link" data-scroll-target="#step-3-configure-rstudio-server-and-jupyterhub-to-be-on-a-subpath"><span class="header-section-number">12.8.3</span> Step 3: Configure RStudio Server and JupyterHub to be on a subpath</a></li>
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-  <li><a href="#cheat-ports" id="toc-cheat-ports" class="nav-link" data-scroll-target="#cheat-ports"><span class="header-section-number">12.8.6</span> Cheatsheet: Special Ports</a></li>
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-<p>These days using a computer is basically synonymous with using a computer network. When you visit a website, print a document, or login to your email, you are making use of a computer network.</p>
-<p>This chapter is an introduction to how computer networks work. This chapter is heavy on introducing mental models for how network traffic works. There is no lab in this chapter.</p>
-<p>The computer network we’re most familiar with is the biggest of them all: The Internet. But there are myriad other networks, like the very small private network of the devices (phones, computers, TVs, etc) connected to your home wifi router, to the somewhat larger VPN (which stands for virtual private network) you might connect to for school or work.</p>
-<p>The good news is that computer networks are basically all the same. If you understand one, you understand them all. Each step in the process is governed by a <em>protocol</em> that defines what is valid.</p>
-<p>There are two basic levels of protocols that are helpful to understand – the transport + address layer, and the application layer.</p>
-<p>Just as you and your friend could communicate in any number of human languages, computers define what a valid message is with an <em>application layer protocol</em>.</p>
-<p>There are numerous application layer protocols. Some you will see in this book include <code>SSH</code> for access to the terminal on a remote machine, <code>(S)FTP</code> for file transfers, <code>SMTP</code> for email, <code>LDAP(S)</code> for authentication and authorization, and <code>websockets</code> for persistent bi-directional communication, which is what the Shiny and Streamlit packages use.</p>
-<p>The most common application layer protocol, used for all standard web traffic, is <strong>h</strong>yper<strong>t</strong>ext <strong>t</strong>ransfer <strong>p</strong>rotocol (<em>http</em>), which we discussed in some depth in <a href="../sec1/1-2-proj-arch.html">Chapter&nbsp;<span>2</span></a> on using APIs for data science purposes.</p>
-<p>For the purposes of this chapter, we’re going to completely set aside physical network infrastructure. Yes, there are wires, cables, satellites, routers, server farms, and more that allow computer networking to work. For the purposes of this chapter, we’re going to focus entirely on the software side of networking.</p>
-<p>One cool thing about the cloud is that it allows you to abstract away all of the physical hardware and focus completely on how the software interacts.</p>
-<section id="tcpip-and-the-mail" class="level2" data-number="12.1">
-<h2 data-number="12.1" class="anchored" data-anchor-id="tcpip-and-the-mail"><span class="header-section-number">12.1</span> TCP/IP and the mail</h2>
-<p>Let’s start by imagining you have a penpal, who lives in an apartment building across the country.<a href="#fn1" class="footnote-ref" id="fnref1" role="doc-noteref"><sup>1</sup></a></p>
-<p>Let’s say you’ve got some juicy gossip to share with your penpal. Because this gossip is so juicy, you’re not going to put it on a postcard. You’d write your letter, put it inside an envelope, address the letter to the right spot, and put it in the mail.</p>
-<p>You trust the postal service to take your letter, deliver it to the correct address, and then your friend will be able to read your letter.</p>
-<p>The process of actualy getting data from one computer to another is governed by the <em>TCP/IP</em> protocol and is called <em>packet switching</em>.<a href="#fn2" class="footnote-ref" id="fnref2" role="doc-noteref"><sup>2</sup></a></p>
-<p>When a computer has data to send to another computer, it takes that information and packages it up into a bundle called a <em>packet</em>.<a href="#fn3" class="footnote-ref" id="fnref3" role="doc-noteref"><sup>3</sup></a></p>
-<p>The data in the packet is like the contents of your letter.</p>
-<p>Just as the postal service defines permissible envelope sizes and address formats, the <em>TCP/IP</em> protocol defines what a packet has to look like from the outside, including what constitutes a valid address.</p>
-<p>A uniform resource locator (URL) is the way to address a specific resource on a network.</p>
-<p>A full URL includes 4 pieces of information: <span class="math display">\[\overbrace{\text{https://}}^\text{protocol}\overbrace{\text{example.com}}^\text{address}\overbrace{\text{:443}}^\text{port}\overbrace{\text{/}}^\text{resource}\]</span></p>
-<p>The protocol starts the URL. It is separated from the rest of the URL by <code>://</code>.</p>
-<p>Each of the rest of the pieces of the URL is needed to get to a specific resource and has a real-world analog.</p>
-<p>The address is like the street address of your penpal’s building. It specifies the host where your data should go.<a href="#fn4" class="footnote-ref" id="fnref4" role="doc-noteref"><sup>4</sup></a></p>
-<p>A host is any entity on a network that can receive requests and send responses. So a server is a common type of host on a network, but so is a router, your laptop, and a printer.</p>
-<p>The port is like your friend’s apartment. It specifies which service on the server to address.</p>
-<p>Lastly, the resource dictates what resource you want on the server. It’s like the name on the address of the letter, indicating that you’re writing to your penpal, not their mom or sister.</p>
-<p>This full URL may look a little strange to you. You’re probably used to just putting a standalone domain like <span class="math inline">\(google.com\)</span> into your browser when you want to go to a website. That’s because <code>https</code>, port <code>443</code>, and <code>/</code> are all defaults, so modern browsers don’t make you specify them.</p>
-<p>But what if you make it explicit? Try going to <code>https://google.com:443/</code>. What do you get?</p>
-</section>
-<section id="ports-get-you-to-the-right-service" class="level2" data-number="12.2">
-<h2 data-number="12.2" class="anchored" data-anchor-id="ports-get-you-to-the-right-service"><span class="header-section-number">12.2</span> Ports get you to the right service</h2>
-<p>A port is a location on a server where a network connection is possible. It’s like the apartment number for the mail. Each port has a unique number 1 to just over 65,000. By default, the overwhelming majority of the ports on the server are closed for security reasons.</p>
-<p>Your computer automatically opens ports to make outgoing connections, but if you want to allow someone to make inbound connections – like to access RStudio or a Shiny app on a server – you need to manually configure and open a port.</p>
-<p>Any program that is running on a server and that you intend to be accessible from the outside is called a service. For example, we set up RStudio, JupyterHub, and a Plumber API as services in the lab in <a href="3-2-linux-admin.html">Chapter&nbsp;<span>11</span></a>. Each service lives on a unique port on the server.</p>
-<p>Since each service running on a server needs a unique port, it’s common to choose a somewhat random relatively high-numbered port. That makes sure it’s unlikely that the port will conflict with another service running on the server.</p>
-<p>For example RStudio Server runs on port <code>8787</code> by default. According to JJ Allaire, there’s no special meaning to this port. It was chosen because it was easy to remember and not <code>8888</code>, which some other popular projects had taken.</p>
-<p>There’s a <a href="#cheat-ports">cheatsheet</a> of commonly used ports at the end of the chapter.</p>
-</section>
-<section id="assigning-addresses" class="level2" data-number="12.3">
-<h2 data-number="12.3" class="anchored" data-anchor-id="assigning-addresses"><span class="header-section-number">12.3</span> Assigning addresses</h2>
-<p>The proper address of a server on a network is defined by the <em>Internet Protocol</em> (IP) and is called an <em>IP Address</em>. IP addresses are mapped to human-friendly domains like <span class="math inline">\(google.com\)</span> with the <em>Domain Name Service (DNS)</em>.</p>
-<div class="callout callout-style-default callout-note callout-titled">
-<div class="callout-header d-flex align-content-center">
-<div class="callout-icon-container">
-<i class="callout-icon"></i>
-</div>
-<div class="callout-title-container flex-fill">
-Note
-</div>
-</div>
-<div class="callout-body-container callout-body">
-<p>In this chapter, we’re going to set DNS aside and talk exclusively about IP Addresses.</p>
-<p><a href="3-4-dns.html">Chapter&nbsp;<span>13</span></a> is all about DNS.</p>
-</div>
-</div>
-<p>Every host on the internet has a public IP address.</p>
-<p>A public IP address is an IP address that is valid across the entire internet. That means that each public IP address is unique across the entire internet. You can think of a public IP address like the public street address of a building.</p>
-<p>But many hosts are not publicly accessible on the internet. Many are housed in private networks. A private network is one where the hosts aren’t directly accessible to the public. You can think of a host in a private network like a building inside a gated community. You may still be able to get there from the public, but you can’t just walk up to the building from the street. Instead you need to come in through the specific gates that have been permitted and approach only on the roads that are allowed.</p>
-<p>TODO: Image of public IPs like street address, private like cul-de-sac</p>
-<p>There are many different kinds of private networks. Some are small and enforced by connection to a physical endpoint, like the private network your WiFi router controls that houses your laptop, phone, TV, Xbox, and anything else you allow to connect to your router. In other cases, the network is a software network. Many organizations have virtual private networks (VPNs). In this case, you connect to the network via software. There may be resources you can only connect to inside your VPN and there also might be limitations about what you can go out and get.</p>
-<p>There are a few different reasons for this public/private network split. The first is security. If you’ve got a public IP address, anyone on the internet can come knock on your virtual front door. That’s actually not so bad. What’s more problematic is that they can go all the way around the building looking for an unlocked side door. Putting your host inside a private network is a way to ensure that people can only approach the host through on the pathways you intend.</p>
-<p>The second reason is convenience.</p>
-<p>Private networks provide a nice layer of abstraction for network addresses.</p>
-<p>You probably have a variety of network-enabled devices in your home, from your laptop and phone to your TV, Xbox, washing machine, and smart locks. But from the outside, your house has only one public IP address – the address of the router in your home. That means that your router has to keep track of all the devices you’ve got, but they don’t need to register with any sort of public service just to be able to use the internet.</p>
-<p>As we’ll get into in <a href="3-4-dns.html">Chapter&nbsp;<span>13</span></a>, keeping track of IP Addresses is best left to machines. If you’re managing a complex private network, it’s really nice to give <em>hostnames</em> to individual hosts. A nice feature of a private hostname compared to a public address is that you don’t have to worry if the hostname is unique across the entire internet – it just has to be unique inside your private network.</p>
-<section id="firewalls-allow-lists-and-other-security-settings" class="level3" data-number="12.3.1">
-<h3 data-number="12.3.1" class="anchored" data-anchor-id="firewalls-allow-lists-and-other-security-settings"><span class="header-section-number">12.3.1</span> Firewalls, allow-lists, and other security settings</h3>
-<p>One of the most basic ways to keep a server safe is to not allow traffic from the outside to come in. Generally that means that in addition to keeping the server ports themselves closed, you’ll also have a firewall up that defaults to all ports being closed.</p>
-<p>In AWS, the basic level of protection for your server is called the security group. If you remember, we used a default security group in launching your server. When you want to go add more services to your server, you’ll have to open additional ports both on the server and in the security group.</p>
-<p>In addition to keeping particular ports closed, you can also set your server to only allow incoming traffic from certain IP addresses. This is generally a very coarse way to do security, and rather fragile. For example, you could configure your server to only accept incoming requests from your office’s IP address, but what if someone needs to access the server from home or the office’s IP address is reassigned?</p>
-<p>One thing that is <em>not</em> a security setting is just using a port that’s hard to guess. For example, you might think, “Well, if I were to put SSH on port 2943 instead of 22, that would be safer because it’s harder to guess!” I guess so, but it’s really just an illusion of security. There are ways to make your server safer. Choosing esoteric port numbers really isn’t it.</p>
-</section>
-</section>
-<section id="how-packets-are-routed" class="level2" data-number="12.4">
-<h2 data-number="12.4" class="anchored" data-anchor-id="how-packets-are-routed"><span class="header-section-number">12.4</span> How packets are routed</h2>
-<p>The way packets travel from one computer to another is called routing. A router is a hardware or software device that route packets.</p>
-<p>You can think of routers and public networks as existing in trees. Each router knows about the IP addresses downstream of it and also the single upstream <em>default address</em>.<a href="#fn5" class="footnote-ref" id="fnref5" role="doc-noteref"><sup>5</sup></a></p>
-<p>TODO: diagram of routers in trees</p>
-<p>For example, the router in your house just keeps track of the actual devices that are attached to it. So if you were to print something from your laptop, the data would just go to your router and then to your printer.</p>
-<p>On the other hand, when you look at a picture on Instagram, that traffic has to go over the public network. The default address for your home’s router is probably one owned by your internet service provider (ISP) for your neighborhood. And that router’s default address is probably also owned by your ISP, but for a broader network.</p>
-<p>So your packet will get passed upstream to a sufficiently general network and then back downstream to the actual address you’re trying to reach.</p>
-<p>Meanwhile, your computer just waits for a response. Once the server has a response to send, it comes back using the same technique. Obviously a huge difference between sending a letter to a penpal and using a computer network is the speed. Where sending a physical letter takes a minimum of days, sending and receiving packets over a network is so fast that the delay is imperceptible when you’re playing a multiplayer video game or collaborating on a document online.</p>
-</section>
-<section id="how-to-recognize-an-ip-address" class="level2" data-number="12.5">
-<h2 data-number="12.5" class="anchored" data-anchor-id="how-to-recognize-an-ip-address"><span class="header-section-number">12.5</span> How to recognize an IP address</h2>
-<p>You’ve probably seen IPv4 addresses many times. They’re four blocks of 8-bit fields (numbers between <code>0</code> and <code>255</code>) with dots in between, so they look something like <code>65.77.154.233</code>.</p>
-<p>If you do the math, you’ll realize there are “only” about 4 billion of these. While we can stretch those 4 billion IP addresses to many more devices since most devices only have private IPs, we are indeed running out of public IPv4 addresses.</p>
-<p>The good news is that smart people started planning for this a while ago. In the last few years, adoption of the new IPv6 standard has started. IPv6 addresses are eight blocks of hexadecimal (<code>0-9</code> + <code>a-f</code>) digits separated by colons, with certain rules that allow them to be shortened, so <code>4b01:0db8:85a3:0000:0000:8a2e:0370:7334</code> or <code>3da4:66a::1</code> are both examples of valid IPv6 addresses.</p>
-<p>IPv6 will coexist with IPv4 for a few decades and we’ll eventually switch entirely to IPv6. There’s no worry about running out of IPv6 addresses any time soon, because the total quantity of IPv6 addresses is a number with 39 zeroes.</p>
-<section id="reserved-ip-addresses" class="level3" data-number="12.5.1">
-<h3 data-number="12.5.1" class="anchored" data-anchor-id="reserved-ip-addresses"><span class="header-section-number">12.5.1</span> Reserved IP Addresses</h3>
-<p>Most IPv4 addresses are freely available to be assigned, but there are a few that you’ll see in particular contexts and it’s useful to know what they are.</p>
-<p>The first IP address you’ll see a lot is <code>127.0.0.1</code>, also known as <code>localhost</code> or loopback. This is the way a machine refers to itself.</p>
-<p>For example, if you open a Shiny app in RStudio Desktop, the app will pop up in a little window along with a notice that says</p>
-<p><code>Listening on http://127.0.0.1:6311</code></p>
-<p>That <code>http://127.0.0.1</code> is indicating that your computer is serving the Shiny app to itself on the localhost address.</p>
-<p>There are also a few blocks of addresses that are reserved for use on private networks, so they’re never assigned in public.</p>
-<table class="table">
-<colgroup>
-<col style="width: 33%">
-<col style="width: 50%">
-</colgroup>
-<thead>
-<tr class="header">
-<th>Code</th>
-<th>Meaning</th>
-</tr>
-</thead>
-<tbody>
-<tr class="odd">
-<td>127.0.0.1</td>
-<td><code>localhost</code> or loopback – the machine that originated the request</td>
-</tr>
-<tr class="even">
-<td><p>192.168.x.x</p>
-<p>172.16.x.x.x</p>
-<p>10.x.x.x</p></td>
-<td>Protected address blocks used for private IP addresses.</td>
-</tr>
-</tbody>
-</table>
-<p>You don’t really need to remember these, but it’s very likely you’ve seen an address like <code>192.168.0.1</code> or <code>192.168.1.1</code> if you’ve ever tried to configure a router or modem for your home wifi.</p>
-<p>Now you know why.</p>
-</section>
-</section>
-<section id="basic-network-troubleshooting" class="level2" data-number="12.6">
-<h2 data-number="12.6" class="anchored" data-anchor-id="basic-network-troubleshooting"><span class="header-section-number">12.6</span> Basic network troubleshooting</h2>
-<p>Networking can be difficult to manage because there are so many layers where it can go awry. Let’s say you’ve configured a service on your server, but you just can’t seem to access it.</p>
-<p>The <code>ping</code> command can be useful for checking whether your server is reachable on the network. For example, here’s what happens when I <code>ping</code> the domain where this book sits.</p>
-<div class="sourceCode" id="cb1"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb1-1"><a href="#cb1-1"></a><span class="op">&gt;</span> ping <span class="ex">-o</span> do4ds.com                                                                        </span>
-<span id="cb1-2"><a href="#cb1-2"></a><span class="ex">PING</span> do4ds.com <span class="er">(</span><span class="ex">185.199.110.153</span><span class="kw">)</span><span class="bu">:</span> 56 data bytes</span>
-<span id="cb1-3"><a href="#cb1-3"></a><span class="ex">64</span> bytes from 185.199.110.153: icmp_seq=0 ttl=57 time=13.766 ms</span>
-<span id="cb1-4"><a href="#cb1-4"></a></span>
-<span id="cb1-5"><a href="#cb1-5"></a><span class="ex">---</span> do4ds.com ping statistics <span class="at">---</span></span>
-<span id="cb1-6"><a href="#cb1-6"></a><span class="ex">1</span> packets transmitted, 1 packets received, 0.0% packet loss</span>
-<span id="cb1-7"><a href="#cb1-7"></a><span class="ex">round-trip</span> min/avg/max/stddev = 13.766/13.766/13.766/0.000 ms</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-<p>This looks great – it sent 1 packet to the server and got one back. That’s exactly what I want. Seeing an unreachable host or packet loss would be an indication that my networking probably isn’t configured correctly somewhere between me and the server. I generally like to use <code>ping</code> with the <code>-o</code> option for sending just <strong>o</strong>ne packet – as opposed to continuously trying.</p>
-<p>If <code>ping</code> fails, it means that my server isn’t reachable. The things I’d want to check is that I have the URL for the server correct, that DNS is configured correctly (see <a href="3-4-dns.html">Chapter&nbsp;<span>13</span></a>), that I’ve correctly configured any firewalls to have the right ports open (Security Groups in AWS), and that any intermediate networking devices are properly configured (see more on proxies in <a href="../sec4/4-2-ent-networks.html">Chapter&nbsp;<span>17</span></a>).</p>
-<p>If <code>ping</code> succeeds but I still can’t access the server, <code>curl</code> is good to check. <code>curl</code> actually attempts to fetch the website at a particular URL. It’s often useful to use <code>curl</code> with the <code>-I</code> option so it just returns a simple status report, not the full contents of what it finds there.</p>
-<p>For example, here’s what I get when I <code>curl</code> CRAN from my machine.</p>
-<div class="sourceCode" id="cb2"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb2-1"><a href="#cb2-1"></a> <span class="op">&gt;</span> curl <span class="ex">-I</span> https://cran.r-project.org/                                                         </span>
-<span id="cb2-2"><a href="#cb2-2"></a> </span>
-<span id="cb2-3"><a href="#cb2-3"></a><span class="ex">HTTP/1.1</span> 200 OK</span>
-<span id="cb2-4"><a href="#cb2-4"></a><span class="ex">Date:</span> Sun, 15 Jan 2023 15:34:19 GMT</span>
-<span id="cb2-5"><a href="#cb2-5"></a><span class="ex">Server:</span> Apache</span>
-<span id="cb2-6"><a href="#cb2-6"></a><span class="ex">Last-Modified:</span> Mon, 14 Nov 2022 17:33:06 GMT</span>
-<span id="cb2-7"><a href="#cb2-7"></a><span class="ex">ETag:</span> <span class="st">"35a-5ed71a1e393e7"</span></span>
-<span id="cb2-8"><a href="#cb2-8"></a><span class="ex">Accept-Ranges:</span> bytes</span>
-<span id="cb2-9"><a href="#cb2-9"></a><span class="ex">Content-Length:</span> 858</span>
-<span id="cb2-10"><a href="#cb2-10"></a><span class="ex">Vary:</span> Accept-Encoding</span>
-<span id="cb2-11"><a href="#cb2-11"></a><span class="ex">Content-Type:</span> text/html</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-<p>The important thing here is that first line. The server is returning a <code>200</code> HTTP status code, which means all is well. For more on HTTP status codes and how to interpret them, see <a href="../sec1/1-2-proj-arch.html">Chapter&nbsp;<span>2</span></a>.</p>
-<p>If <code>ping</code> succeeds, but <code>curl</code> does not, it means that the server is up at the expected IP address, but the service is not accessible. At that point, you might check whether the right ports are accessible – it’s possible to (for example) have port 443 or 80 accessible on your server, but not the port you actually need for your service. You also might check on the server itself that the service is running and that it is running on the port you think it is.</p>
-<p>If you’re running inside a container, you should check that you’ve properly configured the port inside container to be forwarded to the outside.</p>
-</section>
-<section id="comprehension-questions" class="level2" data-number="12.7">
-<h2 data-number="12.7" class="anchored" data-anchor-id="comprehension-questions"><span class="header-section-number">12.7</span> Comprehension Questions</h2>
-<ol type="1">
-<li>What are the 4 components of a URL? What’s the significance of each?</li>
-<li>What are the two things a router keeps track of? How does it use each of them?</li>
-<li>Are there any inherent differences between public and private IP addresses?</li>
-<li>What is the difference between an IP address and a port?</li>
-<li>Let’s say you’ve got a server at 54.33.115.12. Draw a mind map of what happens when you try to SSH into the server. Your explanation should include the terms: IP Address, port, 22, default address, router, sever.</li>
-</ol>
-</section>
-<section id="lab-making-it-accessible-in-one-place" class="level2" data-number="12.8">
-<h2 data-number="12.8" class="anchored" data-anchor-id="lab-making-it-accessible-in-one-place"><span class="header-section-number">12.8</span> Lab: Making it accessible in one place</h2>
-<p>Right now, the only way to get to the various services on our server is only possible via an SSH tunnel. That’s fine for you as you’re working with it – but doesn’t work well if you want to share with other folks.</p>
-<p>Now, you could just open up the different ports each service is on and have people access them there – RStudio on <code>8787</code>, JupyterHub on <code>8000</code>, and the API on <code>8080</code>. But that’s not really ideal. That would mean your users would have to remember and use those ports.</p>
-<div class="callout callout-style-default callout-tip callout-titled">
-<div class="callout-header d-flex align-content-center">
-<div class="callout-icon-container">
-<i class="callout-icon"></i>
-</div>
-<div class="callout-title-container flex-fill">
-Tip
-</div>
-</div>
-<div class="callout-body-container callout-body">
-<p>If you do want to try it to prove to yourself that this “works”, go to your server’s Security Group settings and add custom TCP rules allowing access to ports <code>8787</code>, <code>8000</code>, and <code>8080</code> from anywhere. If you visit <code>$SERVER_ADDRESS:8787</code> you should get RStudio, similarly with JupyterHub at <code>$SERVER_ADDRESS:8000</code>, and the API at <code>$SERVER_ADDRESS:8080</code>.</p>
-<p>Ok, now close those ports back up so we can do this the right way.</p>
-</div>
-</div>
-<p>So instead, we want all the traffic to come in one front door and for users to use convenient subpaths to reach the services. The tool to accomplish this kind of rerouting is called a <em>proxy</em>.</p>
-<p>In our case, we’re just going to run a software proxy on our server that reroutes traffic to different ports on our server. We’re going to use Nginx – a very popular open source proxy.</p>
-<p>TODO: Image of proxy</p>
-<p>Proxies are an advanced networking topic. Most enterprise networks make extensive uses of proxies. For the data science workbench you’re configuring, you may also need to use a proxy because some open source tooling doesn’t support configuring SSL/HTTPS and don’t permit authentication.</p>
-<p>Let’s get it configured.</p>
-<section id="step-1-configure-nginx" class="level3" data-number="12.8.1">
-<h3 data-number="12.8.1" class="anchored" data-anchor-id="step-1-configure-nginx"><span class="header-section-number">12.8.1</span> Step 1: Configure Nginx</h3>
-<p>The first thing we’re going to do is to configure Nginx on our server. Configuring Nginx is pretty straightforward – you install Nginx, put the configuration file into place, and restart the service to pick up the changes. The hard part is figuring out the right configuration. I’ve tested these steps, and they should work for you the first time. But if they don’t, you’re about to learn about the pain of proxy debugging.</p>
-<p>Here are the steps to configure your proxy on your server:</p>
-<ol type="1">
-<li>SSH into your server.</li>
-<li>Install Nginx with <code>sudo apt install nginx</code>.</li>
-<li>Save a backup of the default <code>nginx.conf</code>, <code>cp /etc/nginx/nginx.conf /etc/nginx/nginx-backup.conf</code>.<a href="#fn6" class="footnote-ref" id="fnref6" role="doc-noteref"><sup>6</sup></a></li>
-<li>Edit the Nginx configuration with <code>sudo vim /etc/nginx/nginx.conf</code> and replace it with:</li>
-</ol>
-<div class="code-with-filename">
-<div class="code-with-filename-file">
-<pre><strong>/etc/nginx/nginx.conf</strong></pre>
-</div>
-<div class="sourceCode" id="cb3"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb3-1"><a href="#cb3-1"></a><span class="ex">user</span> www-data<span class="kw">;</span></span>
-<span id="cb3-2"><a href="#cb3-2"></a><span class="ex">worker_processes</span> auto<span class="kw">;</span></span>
-<span id="cb3-3"><a href="#cb3-3"></a><span class="ex">pid</span> /run/nginx.pid<span class="kw">;</span></span>
-<span id="cb3-4"><a href="#cb3-4"></a><span class="ex">include</span> /etc/nginx/modules-enabled/<span class="pp">*</span>.conf<span class="kw">;</span></span>
-<span id="cb3-5"><a href="#cb3-5"></a></span>
-<span id="cb3-6"><a href="#cb3-6"></a><span class="ex">events</span> {</span>
-<span id="cb3-7"><a href="#cb3-7"></a>	<span class="ex">worker_connections</span> 768<span class="kw">;</span></span>
-<span id="cb3-8"><a href="#cb3-8"></a>	<span class="co"># multi_accept on;</span></span>
-<span id="cb3-9"><a href="#cb3-9"></a><span class="er">}</span></span>
-<span id="cb3-10"><a href="#cb3-10"></a></span>
-<span id="cb3-11"><a href="#cb3-11"></a><span class="ex">http</span> {</span>
-<span id="cb3-12"><a href="#cb3-12"></a></span>
-<span id="cb3-13"><a href="#cb3-13"></a> <span class="ex">map</span> <span class="va">$http_upgrade</span> <span class="va">$connection_upgrade</span> {</span>
-<span id="cb3-14"><a href="#cb3-14"></a>    		<span class="ex">default</span> upgrade<span class="kw">;</span></span>
-<span id="cb3-15"><a href="#cb3-15"></a>    		<span class="st">''</span>      close<span class="kw">;</span></span>
-<span id="cb3-16"><a href="#cb3-16"></a>  <span class="er">}</span></span>
-<span id="cb3-17"><a href="#cb3-17"></a></span>
-<span id="cb3-18"><a href="#cb3-18"></a>  <span class="ex">server</span> {</span>
-<span id="cb3-19"><a href="#cb3-19"></a>    <span class="ex">listen</span> 80<span class="kw">;</span></span>
-<span id="cb3-20"><a href="#cb3-20"></a></span>
-<span id="cb3-21"><a href="#cb3-21"></a>    <span class="ex">location</span> /rstudio/ {</span>
-<span id="cb3-22"><a href="#cb3-22"></a>      <span class="co"># Needed only for a custom path prefix of /rstudio</span></span>
-<span id="cb3-23"><a href="#cb3-23"></a>      <span class="ex">rewrite</span> ^/rstudio/<span class="er">(</span><span class="bu">.</span><span class="pp">*</span><span class="kw">)</span><span class="ex">$</span> /<span class="va">$1</span> break<span class="kw">;</span></span>
-<span id="cb3-24"><a href="#cb3-24"></a></span>
-<span id="cb3-25"><a href="#cb3-25"></a>      <span class="co"># Use http here when ssl-enabled=0 is set in rserver.conf</span></span>
-<span id="cb3-26"><a href="#cb3-26"></a>      <span class="ex">proxy_pass</span> http://localhost:8787<span class="kw">;</span></span>
-<span id="cb3-27"><a href="#cb3-27"></a></span>
-<span id="cb3-28"><a href="#cb3-28"></a>      <span class="ex">proxy_http_version</span> 1.1<span class="kw">;</span></span>
-<span id="cb3-29"><a href="#cb3-29"></a>      <span class="ex">proxy_set_header</span> Upgrade <span class="va">$http_upgrade</span><span class="kw">;</span></span>
-<span id="cb3-30"><a href="#cb3-30"></a>      <span class="ex">proxy_set_header</span> Connection <span class="va">$connection_upgrade</span><span class="kw">;</span></span>
-<span id="cb3-31"><a href="#cb3-31"></a>      <span class="ex">proxy_read_timeout</span> 20d<span class="kw">;</span></span>
-<span id="cb3-32"><a href="#cb3-32"></a></span>
-<span id="cb3-33"><a href="#cb3-33"></a>      <span class="co"># Not needed if www-root-path is set in rserver.conf</span></span>
-<span id="cb3-34"><a href="#cb3-34"></a>      <span class="ex">proxy_set_header</span> X-RStudio-Root-Path /rstudio<span class="kw">;</span></span>
-<span id="cb3-35"><a href="#cb3-35"></a></span>
-<span id="cb3-36"><a href="#cb3-36"></a>      <span class="co"># Optionally, use an explicit hostname and omit the port if using 80/443</span></span>
-<span id="cb3-37"><a href="#cb3-37"></a>      <span class="ex">proxy_set_header</span> Host <span class="va">$host</span>:<span class="va">$server_port</span><span class="kw">;</span></span>
-<span id="cb3-38"><a href="#cb3-38"></a>    <span class="er">}</span></span>
-<span id="cb3-39"><a href="#cb3-39"></a></span>
-<span id="cb3-40"><a href="#cb3-40"></a>    <span class="ex">location</span> /jupyter/ {</span>
-<span id="cb3-41"><a href="#cb3-41"></a>      <span class="co"># </span><span class="al">NOTE</span><span class="co"> important to also set bind url of jupyterhub to /jupyter in its config</span></span>
-<span id="cb3-42"><a href="#cb3-42"></a>      <span class="ex">proxy_pass</span> http://127.0.0.1:8000<span class="kw">;</span></span>
-<span id="cb3-43"><a href="#cb3-43"></a></span>
-<span id="cb3-44"><a href="#cb3-44"></a>      <span class="ex">proxy_redirect</span>   off<span class="kw">;</span></span>
-<span id="cb3-45"><a href="#cb3-45"></a>      <span class="ex">proxy_set_header</span> X-Real-IP <span class="va">$remote_addr</span><span class="kw">;</span></span>
-<span id="cb3-46"><a href="#cb3-46"></a>      <span class="ex">proxy_set_header</span> Host <span class="va">$host</span><span class="kw">;</span></span>
-<span id="cb3-47"><a href="#cb3-47"></a>      <span class="ex">proxy_set_header</span> X-Forwarded-For <span class="va">$proxy_add_x_forwarded_for</span><span class="kw">;</span></span>
-<span id="cb3-48"><a href="#cb3-48"></a>      <span class="ex">proxy_set_header</span> X-Forwarded-Proto <span class="va">$scheme</span><span class="kw">;</span></span>
-<span id="cb3-49"><a href="#cb3-49"></a></span>
-<span id="cb3-50"><a href="#cb3-50"></a>      <span class="co"># websocket headers</span></span>
-<span id="cb3-51"><a href="#cb3-51"></a>      <span class="ex">proxy_set_header</span> Upgrade <span class="va">$http_upgrade</span><span class="kw">;</span></span>
-<span id="cb3-52"><a href="#cb3-52"></a>      <span class="ex">proxy_set_header</span> Connection <span class="va">$connection_upgrade</span><span class="kw">;</span></span>
-<span id="cb3-53"><a href="#cb3-53"></a>    <span class="er">}</span></span>
-<span id="cb3-54"><a href="#cb3-54"></a></span>
-<span id="cb3-55"><a href="#cb3-55"></a>    <span class="ex">location</span> /penguins/ {</span>
-<span id="cb3-56"><a href="#cb3-56"></a>      <span class="ex">proxy_pass</span> http://127.0.0.1:8555/<span class="kw">;</span></span>
-<span id="cb3-57"><a href="#cb3-57"></a>      <span class="ex">proxy_set_header</span> Host <span class="va">$host</span><span class="kw">;</span></span>
-<span id="cb3-58"><a href="#cb3-58"></a>    <span class="er">}</span></span>
-<span id="cb3-59"><a href="#cb3-59"></a>  <span class="er">}</span></span>
-<span id="cb3-60"><a href="#cb3-60"></a><span class="er">}</span></span>
-<span id="cb3-61"><a href="#cb3-61"></a></span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-</div>
-<ol start="4" type="1">
-<li>Test that your configuration is valid <code>sudo nginx -t</code>.</li>
-<li>Start Nginx with <code>sudo systemctl start nginx</code>. If you see nothing all is well.</li>
-</ol>
-<p>If you need to change anything, update the config and then restart with <code>sudo systemctl restart nginx</code>.</p>
-</section>
-<section id="step-2-open-port-80" class="level3" data-number="12.8.2">
-<h3 data-number="12.8.2" class="anchored" data-anchor-id="step-2-open-port-80"><span class="header-section-number">12.8.2</span> Step 2: Open port 80</h3>
-<p>Now, if you try to go to your server, your browser will spin for a while and nothing will happen. That’s because the AWS security group still only allows SSH access on port <code>22</code>. We need to add a rule that will allow HTTP access on port <code>80</code>.</p>
-<p>On the AWS console page for your instance, find the Security section and click into the security group for your instance. You want to add a new inbound HTTP rule that allows access on port <code>80</code> from anywhere. Make sure not to get rid of the rule that allows SSH access on <code>22</code>. You still need that one too.</p>
-<p>Once you do this, you should be able to visit your server address and get the default Nginx landing page.</p>
-</section>
-<section id="step-3-configure-rstudio-server-and-jupyterhub-to-be-on-a-subpath" class="level3" data-number="12.8.3">
-<h3 data-number="12.8.3" class="anchored" data-anchor-id="step-3-configure-rstudio-server-and-jupyterhub-to-be-on-a-subpath"><span class="header-section-number">12.8.3</span> Step 3: Configure RStudio Server and JupyterHub to be on a subpath</h3>
-<p>Complex web apps like RStudio and JupyterHub frequently reroute people back to themselves. In general, they assume that they’re on the root path <code>/</code>. That’s not true in this case, so we’ve got to let them know about the subpath where they’re actually located.</p>
-<p>Configuring RStudio Server is already done. The <code>X-RStudio-Root-Path</code> line in the Nginx configuration adds a header to each request coming through the proxy that tells RStudio Server that it’s on the <code>/rstudio</code> path.</p>
-<p>Jupyter needs an explicit update to its own configuration to let it know that it’s on a subpath. Luckily it’s a very simple change. You can edit the Jupyter configuration with</p>
-<div class="code-with-filename">
-<div class="code-with-filename-file">
-<pre><strong>Terminal</strong></pre>
-</div>
-<div class="sourceCode" id="cb4"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb4-1"><a href="#cb4-1"></a><span class="fu">sudo</span> vim /etc/jupyterhub/jupyterhub_config.py</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-</div>
-<p>Find the line that reads <code># c.JupyterHub.bind_url = 'http://:8000'</code>.</p>
-<div class="callout callout-style-default callout-tip callout-titled">
-<div class="callout-header d-flex align-content-center">
-<div class="callout-icon-container">
-<i class="callout-icon"></i>
-</div>
-<div class="callout-title-container flex-fill">
-Tip
-</div>
-</div>
-<div class="callout-body-container callout-body">
-<p>You can search in vim from normal mode with <code>/ &lt;thing you're searching for&gt;</code>. Go to the next hit with <code>n</code>.</p>
-</div>
-</div>
-<p>Delete the <code>#</code> to uncomment the line and add the subpath on the end. If you’re using the <code>/jupyter</code> subpath and the default <code>8000</code> port, that line will read <code>c.JupyterHub.bind_url = 'http://:8000/jupyter'</code>.</p>
-<p>JupyterHub should pick up the new config when it’s restarted with</p>
-<div class="code-with-filename">
-<div class="code-with-filename-file">
-<pre><strong>Terminal</strong></pre>
-</div>
-<div class="sourceCode" id="cb5"><pre class="sourceCode numberSource bash number-lines code-with-copy"><code class="sourceCode bash"><span id="cb5-1"><a href="#cb5-1"></a><span class="fu">sudo</span> systemctl restart jupyterhub</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
-</div>
-</section>
-<section id="step-4-try-it-out" class="level3" data-number="12.8.4">
-<h3 data-number="12.8.4" class="anchored" data-anchor-id="step-4-try-it-out"><span class="header-section-number">12.8.4</span> Step 4: Try it out!</h3>
-<p>Now we should have each service configured on a subpath. RStudio Server at <code>/rstudio</code>, JupyterHub at <code>/jupyter</code>, and our machine learning API at <code>/penguins</code>. For example, with my server at <code>ec2-54-159-134-39.compute-1.amazonaws.com</code>, I can get to RStudio Server at <code>http://ec2-54-159-134-39.compute-1.amazonaws.com/rstudio</code>.</p>
-<div class="callout callout-style-default callout-note callout-titled">
-<div class="callout-header d-flex align-content-center">
-<div class="callout-icon-container">
-<i class="callout-icon"></i>
-</div>
-<div class="callout-title-container flex-fill">
-Note
-</div>
-</div>
-<div class="callout-body-container callout-body">
-<p>As of this writing, the machine learning API serves itself off of <code>/__docs__/</code>, so you actually won’t be able to access anything interesting at <code>/penguins</code>. Instead, you’ll find the API at <code>/penguins/__docs__/</code>.</p>
-<p>This should be fixed before final publication of this book.</p>
-</div>
-</div>
-<p>Note that right now, this server is on HTTP, which is not a best practice. In fact, it’s such a bad practice that your browser will probably autocorrect the url to start with <code>https</code> and it won’t work. You’ll have to manually correct it to <code>http</code>. Don’t leave it like this for long – make sure to make sure to configure <code>https</code> in <a href="3-5-ssl.html">Chapter&nbsp;<span>14</span></a> before doing anything real on this server.</p>
-</section>
-<section id="lab-extensions" class="level3" data-number="12.8.5">
-<h3 data-number="12.8.5" class="anchored" data-anchor-id="lab-extensions"><span class="header-section-number">12.8.5</span> Lab Extensions</h3>
-<p>If you’ve gone to the bare URL for your server, you’ve probably noticed that it’s just the default Nginx landing page, which is not very attractive.</p>
-<p>You might want to create a landing page with links to the subpath by serving a static html page off of <code>/</code>. Or maybe you want one of the services at <code>/</code> and the others at a different subpath.</p>
-<p>If you want to change the subpaths, the <code>location</code> lines in the <code>nginx.conf</code> define the subpaths where the services will be available. By changing those locations, you can change the paths where the services live or you could add another that serves a static web page.</p>
-<p>You also could add a different service at a different path. Note that the <code>proxy_path</code> lines define the port where the service is running on the server. Depending on the service you’re configuring, there may be other configuration you’ll have to do, but that will vary on a service-by-service basis.</p>
-</section>
-<section id="cheat-ports" class="level3" data-number="12.8.6">
-<h3 data-number="12.8.6" class="anchored" data-anchor-id="cheat-ports"><span class="header-section-number">12.8.6</span> Cheatsheet: Special Ports</h3>
-<p>All ports below 1024 are reserved for common server tasks, so you can’t assign services to low-numbered ports.</p>
-<p>There are also three common ports that will come up over and over. These are handy because if you’re using the relevant service, you don’t have to indicate if it’s using the default port.</p>
-<table class="table">
-<thead>
-<tr class="header">
-<th>Protocol</th>
-<th>Default Port</th>
-</tr>
-</thead>
-<tbody>
-<tr class="odd">
-<td>HTTP</td>
-<td>80</td>
-</tr>
-<tr class="even">
-<td>HTTPS</td>
-<td>443</td>
-</tr>
-<tr class="odd">
-<td>SSH</td>
-<td>22</td>
-</tr>
-</tbody>
-</table>
-
-
-</section>
-</section>
-<section id="footnotes" class="footnotes footnotes-end-of-document" role="doc-endnotes">
-<hr>
-<ol>
-<li id="fn1"><p>For this analogy to work, everyone lives in apartment buildings rather than standalone houses.<a href="#fnref1" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
-<li id="fn2"><p>TCP and IP are actually two separate protocols at different layers of the protocol stack. But they’re so closely linked that we can talk about them as one.<a href="#fnref2" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
-<li id="fn3"><p>One of the biggest ways the mail <em>is not</em> like packet switching is that your message gets chopped up among lots of different packets, which are routed independently, and are reassembled when they get where they’re going. Works well for computers, not so well for real-world mail. It’s also pretty much an irrelevant detail, since this whole process works quite invisibly.<a href="#fnref3" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
-<li id="fn4"><p>Often it’s not a single server at the address – but it behaves like one. It could instead be a proxy in front of a cluster of servers or even more complicated routing. All that matters is that it behaves like a single server from the outside.<a href="#fnref4" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
-<li id="fn5"><p>There are actually a few different types of addresses used to do this. IP addresses are used for identifying network resources and the MAC address used for physical hardware. Your router is also responsible for assigning IP addresses to devices as they join the network via the dynamic host configuration protocol (DHCP). I’m glossing over all these details as they’re immaterial to the understanding important for this chapter.<a href="#fnref5" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
-<li id="fn6"><p>This is generally a good practice before you start messing with config files. Bad configuration is usually preferable to a service that can’t start at all because you’ve messed up the config so badly. It happens.<a href="#fnref6" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
-</ol>
-</section>
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diff --git a/chapters/sec4/4-4-ent-servers.html b/chapters/sec3/3-4-ent-servers.html
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@@ -7,7 +7,7 @@
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-<title>DevOps for Data Science - 19&nbsp; Enterprise Server Management</title>
+<title>DevOps for Data Science - 18&nbsp; Enterprise Server Management</title>
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+      <nav class="quarto-page-breadcrumbs" aria-label="breadcrumb"><ol class="breadcrumb"><li class="breadcrumb-item"><a href="../../chapters/sec3/3-0-sec-intro.html">Making it Enterprise-Grade</a></li><li class="breadcrumb-item"><a href="../../chapters/sec3/3-4-ent-servers.html"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></a></li></ol></nav>
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@@ -177,13 +177,19 @@
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  <span class="menu-text"><span class="chapter-number">5</span>&nbsp; <span class="chapter-title">Deployments and code promotion</span></span></a>
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+</li>
+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/sec1/1-6-docker.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">6</span>&nbsp; <span class="chapter-title">Demystifying Docker</span></span></a>
+  </div>
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- <span class="menu-text">IT/Admin Tools</span></a>
+ <span class="menu-text">IT/Admin for Data Science</span></a>
           <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-2" aria-expanded="true" aria-label="Toggle section">
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@@ -191,121 +197,98 @@
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- <span class="menu-text"><span class="chapter-number">6</span>&nbsp; <span class="chapter-title">Opening the Command Line</span></span></a>
+  <a href="../../chapters/sec2/2-1-cloud.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">7</span>&nbsp; <span class="chapter-title">The Cloud</span></span></a>
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-  <a href="../../chapters/sec2/2-2-cmd-line-use.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">7</span>&nbsp; <span class="chapter-title">Using the Command Line</span></span></a>
+  <a href="../../chapters/sec2/2-2-cmd-line.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">8</span>&nbsp; <span class="chapter-title">Customizing the command line</span></span></a>
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-  <a href="../../chapters/sec2/2-3-ssh.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">8</span>&nbsp; <span class="chapter-title">Secure server connections with SSH</span></span></a>
+  <a href="../../chapters/sec2/2-3-linux.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">9</span>&nbsp; <span class="chapter-title">Intro to Linux Administration</span></span></a>
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-  <a href="../../chapters/sec2/2-4-docker.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">9</span>&nbsp; <span class="chapter-title">Demystifying Docker</span></span></a>
+  <a href="../../chapters/sec2/2-4-app-admin.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Application administration</span></span></a>
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- <span class="menu-text"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Getting Started with the Cloud</span></span></a>
+  <a href="../../chapters/sec2/2-5-scale.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Server Resources and Scaling</span></span></a>
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-  <a href="../../chapters/sec3/3-2-linux-admin.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Basic Linux SysAdmin</span></span></a>
-  </div>
-</li>
-          <li class="sidebar-item">
-  <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-3-networking.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-6-networking.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">12</span>&nbsp; <span class="chapter-title">Intro to Computer Networks</span></span></a>
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-  <a href="../../chapters/sec3/3-4-dns.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-7-dns.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">13</span>&nbsp; <span class="chapter-title">DNS allows for human-readable addresses</span></span></a>
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 </li>
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-  <a href="../../chapters/sec3/3-5-ssl.html" class="sidebar-item-text sidebar-link">
+  <a href="../../chapters/sec2/2-8-ssl.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">14</span>&nbsp; <span class="chapter-title">You should use SSL/HTTPS</span></span></a>
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-  <div class="sidebar-item-container"> 
-  <a href="../../chapters/sec3/3-6-servers.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Choosing the right server for you</span></span></a>
-  </div>
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-            <a href="../../chapters/sec4/4-0-sec-intro.html" class="sidebar-item-text sidebar-link">
+            <a href="../../chapters/sec3/3-0-sec-intro.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text">Making it Enterprise-Grade</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true" aria-label="Toggle section">
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+      <ul id="quarto-sidebar-section-3" class="collapse list-unstyled sidebar-section depth1 show">  
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-  <a href="../../chapters/sec4/4-1-os-ds-in-ent.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></a>
+  <a href="../../chapters/sec3/3-1-os-ds-in-ent.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></a>
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- <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></a>
+  <a href="../../chapters/sec3/3-2-ent-networks.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></a>
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-  <a href="../../chapters/sec4/4-3-auth.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></a>
+  <a href="../../chapters/sec3/3-3-auth.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></a>
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-  <a href="../../chapters/sec4/4-4-ent-servers.html" class="sidebar-item-text sidebar-link active">
- <span class="menu-text"><span class="chapter-number">19</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></a>
+  <a href="../../chapters/sec3/3-4-ent-servers.html" class="sidebar-item-text sidebar-link active">
+ <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></a>
   </div>
 </li>
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       <div class="sidebar-item-container"> 
-            <a class="sidebar-item-text sidebar-link text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-5" aria-expanded="true">
+            <a class="sidebar-item-text sidebar-link text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true">
  <span class="menu-text">Appendices</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-5" aria-expanded="true" aria-label="Toggle section">
+          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true" aria-label="Toggle section">
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-      <ul id="quarto-sidebar-section-5" class="collapse list-unstyled sidebar-section depth1 show">  
+      <ul id="quarto-sidebar-section-4" class="collapse list-unstyled sidebar-section depth1 show">  
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@@ -317,6 +300,12 @@
   <a href="../../chapters/append/lab-map.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">B</span>&nbsp; <span class="chapter-title">Lab Map</span></span></a>
   </div>
+</li>
+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../../chapters/append/cheatsheets.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">C</span>&nbsp; <span class="chapter-title">Cheatsheets</span></span></a>
+  </div>
 </li>
       </ul>
   </li>
@@ -330,27 +319,27 @@
     <h2 id="toc-title">Table of contents</h2>
    
   <ul>
-  <li><a href="#managing-complexity-with-infrastructure-as-code" id="toc-managing-complexity-with-infrastructure-as-code" class="nav-link active" data-scroll-target="#managing-complexity-with-infrastructure-as-code"><span class="header-section-number">19.1</span> Managing complexity with Infrastructure as Code</a>
+  <li><a href="#managing-complexity-with-infrastructure-as-code" id="toc-managing-complexity-with-infrastructure-as-code" class="nav-link active" data-scroll-target="#managing-complexity-with-infrastructure-as-code"><span class="header-section-number">18.1</span> Managing complexity with Infrastructure as Code</a>
   <ul class="collapse">
-  <li><a href="#devtestprod-for-itadmins" id="toc-devtestprod-for-itadmins" class="nav-link" data-scroll-target="#devtestprod-for-itadmins"><span class="header-section-number">19.1.1</span> Dev/Test/Prod for IT/Admins</a></li>
+  <li><a href="#devtestprod-for-itadmins" id="toc-devtestprod-for-itadmins" class="nav-link" data-scroll-target="#devtestprod-for-itadmins"><span class="header-section-number">18.1.1</span> Dev/Test/Prod for IT/Admins</a></li>
   </ul></li>
-  <li><a href="#enterprise-scale-and-stability" id="toc-enterprise-scale-and-stability" class="nav-link" data-scroll-target="#enterprise-scale-and-stability"><span class="header-section-number">19.2</span> Enterprise scale and stability</a>
+  <li><a href="#enterprise-scale-and-stability" id="toc-enterprise-scale-and-stability" class="nav-link" data-scroll-target="#enterprise-scale-and-stability"><span class="header-section-number">18.2</span> Enterprise scale and stability</a>
   <ul class="collapse">
-  <li><a href="#load-balancing-requirements" id="toc-load-balancing-requirements" class="nav-link" data-scroll-target="#load-balancing-requirements"><span class="header-section-number">19.2.1</span> Load-balancing requirements</a></li>
-  <li><a href="#accommodating-different-kinds-of-workloads" id="toc-accommodating-different-kinds-of-workloads" class="nav-link" data-scroll-target="#accommodating-different-kinds-of-workloads"><span class="header-section-number">19.2.2</span> Accommodating different kinds of workloads</a></li>
-  <li><a href="#adding-autoscaling" id="toc-adding-autoscaling" class="nav-link" data-scroll-target="#adding-autoscaling"><span class="header-section-number">19.2.3</span> Adding Autoscaling</a></li>
+  <li><a href="#load-balancing-requirements" id="toc-load-balancing-requirements" class="nav-link" data-scroll-target="#load-balancing-requirements"><span class="header-section-number">18.2.1</span> Load-balancing requirements</a></li>
+  <li><a href="#accommodating-different-kinds-of-workloads" id="toc-accommodating-different-kinds-of-workloads" class="nav-link" data-scroll-target="#accommodating-different-kinds-of-workloads"><span class="header-section-number">18.2.2</span> Accommodating different kinds of workloads</a></li>
+  <li><a href="#adding-autoscaling" id="toc-adding-autoscaling" class="nav-link" data-scroll-target="#adding-autoscaling"><span class="header-section-number">18.2.3</span> Adding Autoscaling</a></li>
   </ul></li>
-  <li><a href="#dockerkubernetes-in-enterprise" id="toc-dockerkubernetes-in-enterprise" class="nav-link" data-scroll-target="#dockerkubernetes-in-enterprise"><span class="header-section-number">19.3</span> Docker/Kubernetes in Enterprise</a></li>
-  <li><a href="#comprehension-questions" id="toc-comprehension-questions" class="nav-link" data-scroll-target="#comprehension-questions"><span class="header-section-number">19.4</span> Comprehension Questions</a></li>
+  <li><a href="#dockerkubernetes-in-enterprise" id="toc-dockerkubernetes-in-enterprise" class="nav-link" data-scroll-target="#dockerkubernetes-in-enterprise"><span class="header-section-number">18.3</span> Docker/Kubernetes in Enterprise</a></li>
+  <li><a href="#comprehension-questions" id="toc-comprehension-questions" class="nav-link" data-scroll-target="#comprehension-questions"><span class="header-section-number">18.4</span> Comprehension Questions</a></li>
   </ul>
-<div class="toc-actions"><div><i class="bi bi-github"></i></div><div class="action-links"><p><a href="https://github.com/akgold/do4ds/edit/main/chapters/sec4/4-4-ent-servers.qmd" class="toc-action">Edit this page</a></p></div></div></nav>
+<div class="toc-actions"><div><i class="bi bi-github"></i></div><div class="action-links"><p><a href="https://github.com/akgold/do4ds/edit/main/chapters/sec3/3-4-ent-servers.qmd" class="toc-action">Edit this page</a></p></div></div></nav>
     </div>
 <!-- main -->
 <main class="content" id="quarto-document-content">
 
 <header id="title-block-header" class="quarto-title-block default">
 <div class="quarto-title">
-<h1 class="title"><span id="sec-ent-servers" class="quarto-section-identifier"><span class="chapter-number">19</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></h1>
+<h1 class="title"><span id="sec-ent-servers" class="quarto-section-identifier"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></h1>
 </div>
 
 
@@ -368,8 +357,8 @@ <h1 class="title"><span id="sec-ent-servers" class="quarto-section-identifier"><
 <p>When the number of servers you’re managing is small, you can handle them individually. But for an enterprise, there are dozens or hundreds of servers with complicated interactions across them. In order to keep up with these complexities, different management patterns are needed.</p>
 <p>Relative to a world of just a few servers, there are two main issues that come to the fore in an enterprise context – how to manage the complexity of that many servers and how to ensure services are available when they’re needed for enterprise-scale operations.</p>
 <p>In this chapter, we’ll get into how enterprises solve these challenges of keeping so many servers in sync and scaling services to be stable and available across an enterprise.</p>
-<section id="managing-complexity-with-infrastructure-as-code" class="level2" data-number="19.1">
-<h2 data-number="19.1" class="anchored" data-anchor-id="managing-complexity-with-infrastructure-as-code"><span class="header-section-number">19.1</span> Managing complexity with Infrastructure as Code</h2>
+<section id="managing-complexity-with-infrastructure-as-code" class="level2" data-number="18.1">
+<h2 data-number="18.1" class="anchored" data-anchor-id="managing-complexity-with-infrastructure-as-code"><span class="header-section-number">18.1</span> Managing complexity with Infrastructure as Code</h2>
 <p>Here’s where you don’t want to be an an enterprise IT/Admin. You stand up a server for the data science team in a known good state – with versions of R and Python and the applications they need. But then, over time, more stuff gets installed. Maybe they needed some more versions of R. And that package they installed required some updated system libraries.</p>
 <p>If you just <code>ssh</code> in and do these things — or let the data science team do it themselves, you’ll quickly lose track of what the current state of the server is. You can’t just tear down the server and stand it back up, because none of the changes you’ve made are documented. In DevOps language, the server has become <em>stateful</em> – and that’s a no-no.</p>
 <p>Now, when you’ve just got one server like this, it’s annoying, but not the end of the world. If you’re an IT/Admin organization with 40 or 400 servers it is much more troublesome. And moreover, if you have many servers that need to be configured identically – for example because they’re treated as one cluster – this is impossible. In many enterprises, this whole though experiment would just never fly because production servers can’t be changed. They’re validated from top to bottom for compliance or security reasons and then have to be completely re-validated if any changes are needed.</p>
@@ -406,8 +395,8 @@ <h2 data-number="19.1" class="anchored" data-anchor-id="managing-complexity-with
 </div>
 </div>
 <p>We’re not going to get into any more detail on how these IaC tools work – there are books on all of them you should feel free to read if you’re interested. But now you’ll understand what you’re hearing when the IT/Admin team says they need to write a Terraform script or a Chef recipe to be able to stand up a particular service.</p>
-<section id="devtestprod-for-itadmins" class="level3" data-number="19.1.1">
-<h3 data-number="19.1.1" class="anchored" data-anchor-id="devtestprod-for-itadmins"><span class="header-section-number">19.1.1</span> Dev/Test/Prod for IT/Admins</h3>
+<section id="devtestprod-for-itadmins" class="level3" data-number="18.1.1">
+<h3 data-number="18.1.1" class="anchored" data-anchor-id="devtestprod-for-itadmins"><span class="header-section-number">18.1.1</span> Dev/Test/Prod for IT/Admins</h3>
 <p>Like you want a Dev/Test/Prod setup for your data science projects as discussed in <a href="../sec1/1-5-deployments.html">Chapter&nbsp;<span>5</span></a>, IT/Admins usually use a Dev/Test/Prod setup for themselves. They want an environment to test changes before promoting them for testing and eventually into production. In ideal states, even changes in Dev are only attempted with IaC tools to make sure it’s easy to move forward once the changes are final.</p>
 <p>In enterprises, upgrades and migrations are major to-dos. Planning for a “lift-and-shift” to the cloud is a multi-year affair in many organizations. Even just upgrading operating systems can be a major undertaking.</p>
 <p>For enterprises, I recommend a two-dimensional Dev/Test/Prod setup where the IT/Admin group make changes to the platform in a staging environment.<a href="#fn1" class="footnote-ref" id="fnref1" role="doc-noteref"><sup>1</sup></a> Data scientists never get access to the Staging environments and do all their work in the IT/Admin prod environment.</p>
@@ -415,10 +404,10 @@ <h3 data-number="19.1.1" class="anchored" data-anchor-id="devtestprod-for-itadmi
 <p>Looking back to <a href="../sec1/1-5-deployments.html">Chapter&nbsp;<span>5</span></a>, it should be obvious that the best way to move servers and applications from staging to prod is using IaC and CI/CD to make sure that changes to code always make it into production at the right time.</p>
 </section>
 </section>
-<section id="enterprise-scale-and-stability" class="level2" data-number="19.2">
-<h2 data-number="19.2" class="anchored" data-anchor-id="enterprise-scale-and-stability"><span class="header-section-number">19.2</span> Enterprise scale and stability</h2>
+<section id="enterprise-scale-and-stability" class="level2" data-number="18.2">
+<h2 data-number="18.2" class="anchored" data-anchor-id="enterprise-scale-and-stability"><span class="header-section-number">18.2</span> Enterprise scale and stability</h2>
 <p>Needing to scale data science environments for large jobs is a common need across large and small organizations. But the enterprise need to support many data scientists often requires a different kind of approach to scaling.</p>
-<p>In <a href="../sec3/3-6-servers.html">Chapter&nbsp;<span>15</span></a>, we discussed how just making a single server bigger with vertical scaling can take you a long way. But there are limits. For example, I was recently working with a large customer of Posit’s who needed to support up to 2,000 data scientists in their environment.</p>
+<p>In <a href="../sec2/2-5-scale.html">Chapter&nbsp;<span>11</span></a>, we discussed how just making a single server bigger with vertical scaling can take you a long way. But there are limits. For example, I was recently working with a large customer of Posit’s who needed to support up to 2,000 data scientists in their environment.</p>
 <p>At that scale, there is no server that is nearly large enough. The way to accomplish this kind of scale isto spread the workload out across many servers with <em>horizontal scaling</em>.</p>
 <p>Additionally, when you’re operating at that scale, the stability of the system gets really important. When you’ve got 2,000 data scientists using your platform, each hour of lost time costs more than $100,000.<a href="#fn2" class="footnote-ref" id="fnref2" role="doc-noteref"><sup>2</sup></a></p>
 <p>For some organizations, this necessitates the creation of a <em>disaster recovery</em> plan. This may mean that there are frequent snapshots of the state of the server (often nightly) so the IT/Admins can just roll back to a previous known good state in the event of a failure. Sometimes it also means that there is actually a copy of the server waiting on standby to be activated at all times.</p>
@@ -445,8 +434,8 @@ <h2 data-number="19.2" class="anchored" data-anchor-id="enterprise-scale-and-sta
 <p>If you are a solo data scientist reading this – please do not try to run your own data science cluster. When you undertake load balancing, you’ve taken on a distributed systems problem and those are <em>inherently difficult</em>. When done for scaling reasons, it is almost always worthwhile to exhaust the part of vertical scaling where costs grow linearly with compute before undertaking horizontal scaling.</p>
 <p>If your organization has high availability requirements, it’s worth considering that just adding more nodes may not be sufficient. As the requirements for high availability get steeper, the engineering cost to make sure the service really is that resilient rise exponentially. In addition to considering what to do if a node goes offline, you also have to have backup for the load-balancer and the database/NAS, as well as any other part of the system.</p>
 <p>In fact, it’s totally possible to make your system <em>less stable</em> by just doing horizontal scaling in one spot without thinking through the implications.</p>
-<section id="load-balancing-requirements" class="level3" data-number="19.2.1">
-<h3 data-number="19.2.1" class="anchored" data-anchor-id="load-balancing-requirements"><span class="header-section-number">19.2.1</span> Load-balancing requirements</h3>
+<section id="load-balancing-requirements" class="level3" data-number="18.2.1">
+<h3 data-number="18.2.1" class="anchored" data-anchor-id="load-balancing-requirements"><span class="header-section-number">18.2.1</span> Load-balancing requirements</h3>
 <p>Load-balancers are just a special kind of proxy that routes sessions among the nodes in the cluster. A simple load-balancer just rotates sending traffic to the different nodes using a <em>round-robin</em> configuration.</p>
 <p>At a minimum, your load-balancer has to know what nodes are accepting traffic. This is accomplished by configuring a health check/heartbeat endpoint for your product. A health check is a feature of an application. The load-balancer periodically pings the health check. If it gets a response, it knows it can send traffic to that node. If no response comes back, it treats that node as unhealthy and doesn’t send traffic there.</p>
 <p>It is sometimes necessary to do more complicated load-balancing that pays attention to how loaded different nodes are. Additionally, some products feature internal load-balancers, so it really doesn’t matter what your load-balancer does.</p>
@@ -458,16 +447,16 @@ <h3 data-number="19.2.1" class="anchored" data-anchor-id="load-balancing-require
 <p>When you’re in a single-server configuration, all this can just go somewhere on the server with the application. Very often the database is just a <em>sqlite</em> file that sits in a file on the filesystem.</p>
 <p>But when you go to to a load-balanced cluster, all of the nodes need symmetric access to read and write. You need an actual database (like <em>postgres</em>) for the application to use. Additionally, anything on the filesystem now needs to move off of an individual server onto a networked system that all the nodes can access.</p>
 </section>
-<section id="accommodating-different-kinds-of-workloads" class="level3" data-number="19.2.2">
-<h3 data-number="19.2.2" class="anchored" data-anchor-id="accommodating-different-kinds-of-workloads"><span class="header-section-number">19.2.2</span> Accommodating different kinds of workloads</h3>
+<section id="accommodating-different-kinds-of-workloads" class="level3" data-number="18.2.2">
+<h3 data-number="18.2.2" class="anchored" data-anchor-id="accommodating-different-kinds-of-workloads"><span class="header-section-number">18.2.2</span> Accommodating different kinds of workloads</h3>
 <p>When you’re doing horizontal-scaling, people often want to accomodate a variety of workloads. For example, they might want to be able to incorporate several different sizes of jobs that might require a few different sized nodes. Or maybe they want to run a mixture of GPU-backed and non-GPU workloads in the cluster and want to reserve GPU nodes for the jobs that need it.</p>
 <p>In general, it’s not trivial to set up a single cluster that can support different kinds of workloads, and it’s often easier to set up, for example, a standalone GPU cluster.</p>
 <p>These days, people are often reaching for Kubernetes for clusters that need to support varies workloads. While it’s true that Kubernetes can theoretically support different kinds of nodes within one cluster, this often isn’t trivial to configure.</p>
 <p>Often, a better option for data science workloads is to use use a high-performance computing (HPC) framework. HPC is particularly appropriate when you need very large machines. In Kubernetes, it is not possible to schedule pods larger than the size of the actual nodes in the cluster. In contrast, most HPC frameworks allow you to combine an arbitrary number of nodes into what acts like a single machine with thousands or tens of thousands of nodes.</p>
 <p>For example, Slurm is an HPC framework that support multiple queues for different sets of machines. AWS has a service called ParallelCluster that allows users to easily set up a Slurm cluster – and with no additional cost relative to the cost of the underlying AWS hardware.</p>
 </section>
-<section id="adding-autoscaling" class="level3" data-number="19.2.3">
-<h3 data-number="19.2.3" class="anchored" data-anchor-id="adding-autoscaling"><span class="header-section-number">19.2.3</span> Adding Autoscaling</h3>
+<section id="adding-autoscaling" class="level3" data-number="18.2.3">
+<h3 data-number="18.2.3" class="anchored" data-anchor-id="adding-autoscaling"><span class="header-section-number">18.2.3</span> Adding Autoscaling</h3>
 <p>Sometimes people also undertake horizontal scaling to be able to do autoscaling. The idea here is that the organization could maintain a small amount of “always-on” capacity and scale out other capacity as needed to maintain costs. This is possible – but it requires nontrivial engineering work.</p>
 <p>In particular, autoscaling a data science workbench down is quite hard. The main reason for this is that many autoscaling routines assume you can easily move someone’s job from one node to another just keeping track of the long-term state. This is a bad assumption for a data science workbench and autoscaling a data science workbench downwards is a difficult challenge.</p>
 <p>Let’s think about a relatively stateless workload. For example, let’s imagine a search engine – every time you put in a search, it spins up a job, does your search, and then spins down.</p>
@@ -475,8 +464,8 @@ <h3 data-number="19.2.3" class="anchored" data-anchor-id="adding-autoscaling"><s
 <p>That’s not the case with a data science workbench. Many autoscaling frameworks these days assume that applications are mostly stateless. In a stateless applications, every interaction is standalone – there’s very little path dependence. The line between statefulness and statelessness are pretty blurry, but working inside a development environment like RStudio or a Jupyter Notebook is about as stateful as it gets. You have long-term state like the files you need and your preferences and short-term state like the recent commands you’ve typed and the packages loaded into your R and Python environment.</p>
 </section>
 </section>
-<section id="dockerkubernetes-in-enterprise" class="level2" data-number="19.3">
-<h2 data-number="19.3" class="anchored" data-anchor-id="dockerkubernetes-in-enterprise"><span class="header-section-number">19.3</span> Docker/Kubernetes in Enterprise</h2>
+<section id="dockerkubernetes-in-enterprise" class="level2" data-number="18.3">
+<h2 data-number="18.3" class="anchored" data-anchor-id="dockerkubernetes-in-enterprise"><span class="header-section-number">18.3</span> Docker/Kubernetes in Enterprise</h2>
 <p>Originally created at Google and released in 2014, Kubernetes is the way to run production services out of Docker containers.<a href="#fn3" class="footnote-ref" id="fnref3" role="doc-noteref"><sup>3</sup></a> It is an open source project. If you’re confused by the name, apparently Kubernetes is an ancient Greek word for “helmsman”.</p>
 <p>Many organizations are moving towards using Docker and Kubernetes for their server-based infrastructure. Kubernetes solves all three of the key enterprise IT/Admin challenges with running servers because you manage a single cluster, you can scale rather effortlessly, and app-level administration is extremely simple.</p>
 <p>The elegance of using Kubernetes is that it completely separates provisioning and configuration challenges. The main unit of analysis in Kubernetes is a <em>pod</em>, which is the term for a Docker container that is running in Kubernetes.</p>
@@ -501,8 +490,8 @@ <h2 data-number="19.3" class="anchored" data-anchor-id="dockerkubernetes-in-ente
 <p>Networking in Kubernetes can also be quite complicated. For anything that lives fully in Kubernetes, like your Workbench nodes and load-balancer, it’s quite simple. But getting things into and out of the Kubernetes cluster – like the filesystem you probably need to mount in and accessing databases is a real challenge.</p>
 <p>All this to say – these are solvable problems for an experienced Kubernetes admin. But they will probably need some guidance around specific requirements for a data science workbench.</p>
 </section>
-<section id="comprehension-questions" class="level2" data-number="19.4">
-<h2 data-number="19.4" class="anchored" data-anchor-id="comprehension-questions"><span class="header-section-number">19.4</span> Comprehension Questions</h2>
+<section id="comprehension-questions" class="level2" data-number="18.4">
+<h2 data-number="18.4" class="anchored" data-anchor-id="comprehension-questions"><span class="header-section-number">18.4</span> Comprehension Questions</h2>
 <ol type="1">
 <li>What is the difference between horizontal and vertical scaling? For each of the following examples, which one would be more appropriate?
 <ol type="a">
@@ -762,8 +751,8 @@ <h2 data-number="19.4" class="anchored" data-anchor-id="comprehension-questions"
 </script>
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+      <a href="../../chapters/sec3/3-3-auth.html" class="pagination-link">
+        <i class="bi bi-arrow-left-short"></i> <span class="nav-page-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span>
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-  <li><a href="#computers-are-just-addition-factories" id="toc-computers-are-just-addition-factories" class="nav-link active" data-scroll-target="#computers-are-just-addition-factories"><span class="header-section-number">15.1</span> Computers are (just) addition factories</a></li>
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-  <li><a href="#scaling-servers" id="toc-scaling-servers" class="nav-link" data-scroll-target="#scaling-servers"><span class="header-section-number">15.6</span> Scaling Servers</a></li>
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-<h1 class="title"><span id="sec-servers" class="quarto-section-identifier"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Choosing the right server for you</span></span></h1>
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-<p>Throughout this section of the book, you’ve learned a lot about how to configure a server including getting one from AWS, how to administer Linux on it, and how to safely configure it to be accessible from the internet.</p>
-<p>But let’s take a step back. How do you know you chose the right server? How do you choose a server with enough horsepower to get you and your team through the day, but without breaking the bank?</p>
-<p>In this chapter, we’ll spend some time clarifying what a computer actually does and how that relates to the size and type of server you might want. We’ll also get a little into how AWS classifies servers and how you’ll choose the one you want.</p>
-<section id="computers-are-just-addition-factories" class="level2" data-number="15.1">
-<h2 data-number="15.1" class="anchored" data-anchor-id="computers-are-just-addition-factories"><span class="header-section-number">15.1</span> Computers are (just) addition factories</h2>
-<p>You’re probably aware that everything you’ve ever seen on a computer – from this book to your work in R or Python, your favorite internet cat videos, and Minecraft – it’s just 1s and 0s.</p>
-<p>The theory of why this works is deep and fascinating.<a href="#fn1" class="footnote-ref" id="fnref1" role="doc-noteref"><sup>1</sup></a> Luckily, the amount of computational theory you need to understand to be an effective data scientist can be can be summarized in three sentences:</p>
-<blockquote class="blockquote">
-<p>Everything on a computer is represented by a (usually very large) number.</p>
-<p>At a hardware level the only thing computers do is add these numbers together.</p>
-<p>Modern computers add very quickly and very accurately.</p>
-</blockquote>
-<p>This means that for your day-to-day work, you can think of a computer as just a big factory for doing additions.</p>
-<p>Every bit of input your computer gets is turned into an addition problem, processed, and the results are reverted back into something we interpret as meaningful.</p>
-<p>The addition assembly line itself – where the work actually gets done – is referred to as <em>compute</em>. It’s where 2+2 gets turned into 4, and where 345619912 + 182347910 gets turned into 527967822.</p>
-<p>There are a number of different kinds of compute, but they all basically work the same. The total speed is determined by two factors – the number of conveyor belts (cores) and the speed at which each belt is running (clock speed).</p>
-<p>We’re going to spend some time considering the three important resources – compute, memory, and storage – you have to allocate and manage on your computer or server. We’re going to spend some time generally exploring what each one is and then get into how you should think about each specifically with regard to data science.</p>
-</section>
-<section id="recommendation-1-fewer-faster-cpu-cores" class="level2" data-number="15.2">
-<h2 data-number="15.2" class="anchored" data-anchor-id="recommendation-1-fewer-faster-cpu-cores"><span class="header-section-number">15.2</span> Recommendation 1: Fewer, faster CPU cores</h2>
-<p>All computers have a central processing unit (CPU). These days, most consumer-grade laptops have between 4 and 16 cores, and may have additional capabilities that effectively doubles that number. So most laptop CPUs can do between 4 and 32 simultaneous addition problems.</p>
-<p>Clock speeds are measured in operations per second or hertz (hz). The cores in your laptop probably run between two and five gigahertz (GHz), which means between 2 and 5 billion operations per second when running at full speed.</p>
-<p>For decades, many of the innovations in computing were coming from increases in clock speed, but raw increases in speed have fallen off a lot in the last few decades. The clock speeds of consumer-grade chips increased by approximately 10x during the 90s, by 2-3x in the 2000s, and somewhere between not at all and 1.5x in the 2010s.</p>
-<p>But computers have continued getting a lot faster even as the increase in clock speeds has slowed. The increase has mostly come from increases in the number of cores, better software usage of parallelization, and innovative chip architectures for special-purpose usage.</p>
-<p>R and Python are single-threaded. Unless you’re using special libraries for parallel processing, you’ll end up red-lining a single CPU core while the other just look on in silence.</p>
-<p>Therefore for most R and Python work, single core clock speed matters more than the number of cores, and fewer, faster cores are usually preferable to many slower</p>
-<p>You’re probably not used to thinking about this tradeoff from buying a laptop or phone. The reality is that modern CPUs are pretty darn good and you should just buy the one that fits your budget.</p>
-<p>If you’re standing up a server, you often do have an explicit choice between more slower cores and fewer faster ones. In AWS, the instance type is what dictates the tradeoff – more on this below.</p>
-<p>If you’re running a multi-user server, the number of cores you need is really hard to estimate. If you’re doing non-ML tasks like counts and dashboarding or relatively light-duty machine learning I might advise the following:</p>
-<p><span class="math display">\[
-\text{n cores} = \text{1 core per user} + 1
-\]</span></p>
-<p>The spare core is for the server to do its own operations apart from the data science usage. On the other hand, if you’re doing heavy-duty machine learning or parallelizing jobs across the CPU, you may need more cores than that.</p>
-</section>
-<section id="recommendation-2-get-as-much-ram-as-feasible" class="level2" data-number="15.3">
-<h2 data-number="15.3" class="anchored" data-anchor-id="recommendation-2-get-as-much-ram-as-feasible"><span class="header-section-number">15.3</span> Recommendation 2: Get as much RAM as feasible</h2>
-<p>Your computer’s random access memory (RAM) is its short term storage. In the computer as adding factory analogy, the RAM is like the stock that’s sitting out on the factory floor ready to go right on an assembly line.</p>
-<p>RAM is very fast to for your computer to access, so you can read and write to it very quickly. The downside is that it’s temporary. When your computer turns off, the RAM gets wiped.<a href="#fn2" class="footnote-ref" id="fnref2" role="doc-noteref"><sup>2</sup></a></p>
-<div class="callout callout-style-default callout-note callout-titled">
-<div class="callout-header d-flex align-content-center">
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-Note
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-<p>You probably know this, but memory and storage is measured in bytes prefixed by metric prefixes. Common sizes for memory these days are in gigabytes (billion bytes) and terrabytes (trillion bytes). Some enterprise data stores run on the scales of thousands of terrabytes (pettabytes) or even thousands of pettabytes (yottabytes).</p>
-</div>
-</div>
-<p>Modern consumer-grade laptops come with somewhere between 4 and 16 Gb of memory.</p>
-<p>In most cases, R and Python have to load all of your data into memory. Thus, the size of the data you can use is limited to the size of your machine’s RAM. Most other limits of your machine will just result in things being slower than you’d really want, but trying to load too much data into memory will result in a session crash, and you won’t be able to do your analysis.</p>
-<div class="callout callout-style-default callout-note callout-titled">
-<div class="callout-header d-flex align-content-center">
-<div class="callout-icon-container">
-<i class="callout-icon"></i>
-</div>
-<div class="callout-title-container flex-fill">
-Note
-</div>
-</div>
-<div class="callout-body-container callout-body">
-<p>You can get around the in-memory limitation by using a <a href="#database">database</a> or libraries that facilitate on-disk operations like <a href="https://arrow.apache.org/">Apache Arrow</a> or <a href="https://docs.dask.org/en/latest/why.html">dask</a>.</p>
-</div>
-</div>
-<p>Because you’ll often be doing some sort of transformation that results in invisible data copies and your computer can’t devote all of its memory, you’ll want to leave plenty of room over your actual data size.</p>
-<p>It’s easy to say that you’ll always want more RAM, but a rough rule of thumb for whether you’ve got enough is the following:</p>
-<p><span class="math display">\[\text{Amount of RAM} = \text{max amount of data} * 3\]</span></p>
-<p>If you’re thinking about running a multi-user server, you’ll want to think about the maximum simultaneous number of users on the server, the most data each one would want to have loaded into memory and use that for your max amount of data</p>
-</section>
-<section id="recommendation-3-get-lots-of-storage-its-cheap" class="level2" data-number="15.4">
-<h2 data-number="15.4" class="anchored" data-anchor-id="recommendation-3-get-lots-of-storage-its-cheap"><span class="header-section-number">15.4</span> Recommendation 3: Get lots of storage, it’s cheap</h2>
-<p>Relative to the RAM that’s right next to the factory floor, your computer’s storage is like the warehouse in the next building over. It’s much, much slower to get things from storage than RAM, but it’s also permanent once its stored there.</p>
-<p>Up until a few years ago, hard drives were very slow. HDD drives have a bunch of magnetic disks that spin very fast (5,400 and 7,200 RPM are common speeds). Magnetized read/write heads move among the disks and save and read your data.</p>
-<p>While 7,200 RPM is very fast, there were still physical moving parts, and reading and writing data was very slow by computational standards.</p>
-<p>In the last few years, solid-state drives (SSDs) have become more-or-less standard in laptops. SSDs, which are collections of flash memory chips with no moving parts, are up to 15x faster than HDDs. They also can take a wider variety of shapes and sizes, and are more reliable and durable because they have no moving parts. The main drawback is that they’re usually more expensive per byte, but prices are still quite reasonable.</p>
-<p>Many consumer laptops have only an SSD at this point. Some desktops and high-end laptops combine a smaller SSD with a larger HDD.</p>
-<p>As for storage – get a lot – but don’t think about it too hard, because it’s cheap. Both a 1TB SSD and a 4TB HDD are around $100. Storage is cheap enough these days that it is almost always more cost efficient to buy more storage rather than making a highly-paid professional spend their time trying to figure out how to move things around.</p>
-<p>One litmus test of an IT organization that is well-equipped to support data science is whether they understand this. Smart organizations know that just getting more storage is almost always worth the cost in terms of the time of admins and data scientists.</p>
-<p>If you’re running a multi-user server, the amount of storage you need depends a lot on your data and your workflows. A reasonable rule of thumb is to choose</p>
-<p><span class="math display">\[
-\text{Amount of Storage} = \text{data saved} + 1Gb * \text{n users}
-\]</span></p>
-<p>One thing to keep in mind is that you can basically just choose storage to match your data size and add a Gigabyte per person.</p>
-<p>Aside from actual data, the amount of space each person needs on the server is small. Code is very small and it’s rare to see R and Python packages take up more than a few dozen Mb per data scientist.</p>
-<div class="callout callout-style-default callout-note callout-titled">
-<div class="callout-header d-flex align-content-center">
-<div class="callout-icon-container">
-<i class="callout-icon"></i>
-</div>
-<div class="callout-title-container flex-fill">
-Note
-</div>
-</div>
-<div class="callout-body-container callout-body">
-<p>If you’re working with a professional IT admin, they may be concerned about the storage implications of having package copies for each person on their team. I’ve heard this concern a lot from IT/Admins thinking prospectively about running their server and almost never of a case where it’s actually been a problem.</p>
-<p>Finding a person who has more than a few hundred Mb of packages would be very strange indeed.</p>
-</div>
-</div>
-<p>So it really comes down to how much data you expect to save on the server. In some organizations, each data scientist will save dozens of flat files of a Gb or more for each of their projects. That team would need a lot of storage. In other teams, all the data lives in a database and you basically don’t need anything beyond that 1 Gb per person.</p>
-<p>If you’re operating in the cloud, this really isn’t an important choice. As you’ll see in the lab, upgrading the amount of storage you have is a really trivial operation, requiring at most a few minutes of downtime. Choose a size you guess will be adequate and add more if you need.</p>
-</section>
-<section id="recommendation-4-get-a-gpumaybe" class="level2" data-number="15.5">
-<h2 data-number="15.5" class="anchored" data-anchor-id="recommendation-4-get-a-gpumaybe"><span class="header-section-number">15.5</span> Recommendation 4: Get a GPU…maybe</h2>
-<p>The most common special architecture chips is the graphical processing unit (GPU). GPUs are specialized chips used for tasks like editing photo or videos, rendering video game graphics, some kinds of machine learning, and (yes) Bitcoin mining.</p>
-<p>Like a CPU, a GPU is just an addition factory but with a different architecture. A CPU has a few fast cores, so it can only work on a few problems simultaneously, but it does them very fast. In contrast, a GPU takes the opposite approach, with many slower cores. Where a consumer-grade CPU has 4-16 cores, mid-range GPUs have 700-4,000 cores, but each one runs between 1% and 10% the speed of a CPU core.</p>
-<p>For GPU-centric tasks, the overwhelming parallelism of a GPU is more important than the speed of any individual core, and GPU computation can be dramatically faster. For the purposes of data science, many popular machine learning techniques – including neural networks, XGBoost, and other tree-based models – potentially run much much faster on GPUs relative to CPUs.</p>
-<p>Some machines are also adding other types of specialized chips to do machine learning – though these generally aren’t accessible for training models. For example, iPhone TODO.</p>
-<p>The choice of whether you need a GPU to do your work will really depend on what you’re doing and your budget.</p>
-<p>Only certain kinds of data science tasks are even amenable to GPU-backed acceleration. Many data science tasks can only be done in sequence others can be parallelized, but splitting it into a small number of CPU cores is perfectly adequate. For the most part, the things that will benefit most from GPU computing are training highly parallel machine learning models like a neural network or tree-based models.</p>
-<p>If you do have one of these use cases, GPU computing can massively speed up your computation – making models trainable in hours instead of days.</p>
-<p>If you are planning to use cloud resources for your computing, GPU-backed instances are quite pricey, and you’ll want to be careful about only putting those machines up when you’re using them.</p>
-<p>It’s also worth noting that using a GPU won’t happen automatically. The tooling has gotten good enough that it’s usually pretty easy to set up, but your computer won’t train your XGBoost models on your GPU unless you tell it to do so.</p>
-<p>Because GPUs are expensive, I generally wouldn’t bother with GPU-backed computing unless you’ve already tried without a GPU and find that it takes too long to be feasible.</p>
-</section>
-<section id="scaling-servers" class="level2" data-number="15.6">
-<h2 data-number="15.6" class="anchored" data-anchor-id="scaling-servers"><span class="header-section-number">15.6</span> Scaling Servers</h2>
-<p>There are two reasons you might need to scale to a bigger server. The first reason that people think of most often is because people are running big jobs. This can happen at any scale of organization. There are data science teams of one who have use cases that necessitate terrabytes of data. There are also issues that come up as your data science team gets bigger.</p>
-<p>Either way, there are two basic options for how to scale your data science workbench. The first is <em>vertical scaling</em>, which is just a fancy way of saying get a bigger server. If your budget allows it, you shouldn’t feel shy about vertically scaling – the complexity of managing a <code>t3.nano</code> with 2 cores and 0.5 Gb of memory is exactly the same as a <code>C5.24xlarge</code> with 96 cores and 192 Gb of memory. In fact, the bigger one may well be easier to manage, since you won’t have to worry about running low on resources.</p>
-<p>AWS resource costs generally scale linearly within a server family. But there are limits. As of this writing, AWS’s general-use instance types max out at 96-128 cores these days. That’s probably sufficient for many workloads, but if you’ve got an RStudio Server with 50 concurrent users doing reasonably heavy compute loads, that can quickly get eaten up.</p>
-<p>The nice thing about being in the cloud is that vertical scaling is almost trivially easy, as we’ll see in the lab in this chapter.</p>
-<p>If your needs grow beyond the capacity of a single server, you’re starting to get into <em>horizontal scaling</em> territory. Once you’re thinking about horizontal scaling, you should almost certainly get an IT/Admin professional involved. See <a href="../sec4/4-4-ent-servers.html">Chapter&nbsp;<span>19</span></a> for more on how to talk to them about it.</p>
-</section>
-<section id="aws-costs" class="level2" data-number="15.7">
-<h2 data-number="15.7" class="anchored" data-anchor-id="aws-costs"><span class="header-section-number">15.7</span> AWS Costs</h2>
-<p>That said, a modestly-sized server is still pretty cheap if you’re only putting it up for a short amount of time.</p>
-<p>I’m writing this on a 2021 M1 Macbook Pro with 10 CPUs and 32 Gb of memory. If you wanted that same computational power from an AWS server, it’s roughly comparable to a <code>t3.2xlarge</code> – with 8 CPUs and 32Gb of memory. That server costs is $0.33 an hour. So a full year running full time for an instance is nearly $3,000, but if you’re only running that instance for a little while – say, the few hours it’ll take you to complete this lab – it will probably only be a few dollars.</p>
-</section>
-<section id="comprehension-questions" class="level2" data-number="15.8">
-<h2 data-number="15.8" class="anchored" data-anchor-id="comprehension-questions"><span class="header-section-number">15.8</span> Comprehension Questions</h2>
-<ol type="1">
-<li><p>Think about the scenarios below – which part of your computer would you want to upgrade to solve the problem?</p>
-<ol type="1">
-<li><p>You try to load a big csv file into pandas in Python. It churns for a while and then crashes.</p></li>
-<li><p>You go to build a new ML model on your data. You’d like to re-train the model once a day, but it turns out training this model takes 26 hours on your laptop.</p></li>
-<li><p>You design an visualization <code>Matplotlib</code> , and create a whole bunch in a loop, you want to parallelize the operation. Right now you’re running on a <code>t2.small</code> with 1 CPU.</p></li>
-</ol></li>
-<li><p>Draw a mind map of the following: CPU, RAM, Storage, Operations Per Second, Parallel Operations, GPU, Machine Learning</p></li>
-<li><p>What are the architectural differences between a CPU and a GPU? Why does this make a GPU particularly good for Machine Learning?</p>
-<h2 id="aws-instance-classes-for-data-science" data-number="15.9" class="anchored"><span class="header-section-number">15.9</span> AWS Instance Classes for Data Science</h2>
-<p>AWS offers a variety of different EC2 instance types. There are a few different types you’ll probably consider, here’s a quick guide to the types most commonly used for data science purposes.</p>
-<p>Within each family, there are different sizes available, ranging from <em>nano</em> to <em>2xl</em>. Instances are denoted by <em>&lt;family&gt;.&lt;size&gt;</em>. So, for example, when we put our instance originally on a free tier machine, we put it on a <code>t2.micro</code>.</p>
-<p>In most cases, going up a size doubles the amount of RAM, the number of cores, and the cost.</p>
-<table class="table">
-<colgroup>
-<col style="width: 22%">
-<col style="width: 75%">
-</colgroup>
-<thead>
-<tr class="header">
-<th>Instance Type</th>
-<th>Notes</th>
-</tr>
-</thead>
-<tbody>
-<tr class="odd">
-<td><code>t3</code></td>
-<td><p>The “standard” configuration. Relatively cheap per core/Gb RAM.</p>
-<p>good b/c of instance credits, limited size</p></td>
-</tr>
-<tr class="even">
-<td><code>C</code></td>
-<td>Faster CPUs</td>
-</tr>
-<tr class="odd">
-<td><code>R</code></td>
-<td>Higher ratio of RAM to CPU</td>
-</tr>
-<tr class="even">
-<td><code>P</code></td>
-<td>GPU instances, very expensive</td>
-</tr>
-</tbody>
-</table>
-<h2 id="lab-changing-instance-size" data-number="15.10" class="anchored"><span class="header-section-number">15.10</span> Lab: Changing Instance Size</h2></li>
-</ol>
-<p>Ok, now we’re going to experience the real magic of the cloud – <em>flexibility.</em></p>
-<p>We’re going to upgrade the size of our server in just a minute or two.</p>
-<section id="step-1-confirm-current-server-size" class="level3" data-number="15.10.1">
-<h3 data-number="15.10.1" class="anchored" data-anchor-id="step-1-confirm-current-server-size"><span class="header-section-number">15.10.1</span> Step 1: Confirm current server size</h3>
-<p>First, let’s confirm what we’ve got available. You can check the number of CPUs you’ve got with <code>lscpu</code> in a terminal. Similarly, you can check the amount of RAM with <code>free -h</code>. This is just so you can prove to yourself later that the instance really changed.</p>
-</section>
-<section id="step-2-change-the-instance-type-and-bring-it-back" class="level3" data-number="15.10.2">
-<h3 data-number="15.10.2" class="anchored" data-anchor-id="step-2-change-the-instance-type-and-bring-it-back"><span class="header-section-number">15.10.2</span> Step 2: Change the instance type and bring it back</h3>
-<p>Now, you can go to the instance page in the AWS console. The first step is to stop (not terminate!) the instance. This means that changing instance type <em>does</em> require some downtime for the instance, but it’s quite limited.</p>
-<p>Once the instance has stopped, you can change the instance type under Actions &gt; Instance Settings. Then start the instance. It’ll take a few seconds to start the instance.</p>
-<p><em>And that’s it</em>.</p>
-</section>
-<section id="step-3-confirm-new-server-size" class="level3" data-number="15.10.3">
-<h3 data-number="15.10.3" class="anchored" data-anchor-id="step-3-confirm-new-server-size"><span class="header-section-number">15.10.3</span> Step 3: Confirm new server size</h3>
-<p>So, for example, I changed from a <code>t2.micro</code> to a <code>t2.small</code>. Both only have 1 CPU, so I won’t see any difference in <code>lscpu</code>, but running <code>free -h</code> before and after the switch reveals the difference in the total column:</p>
-<pre><code>test-user@ip-172-31-53-181:~$ free -h
-               total        used        free      shared  buff/cache   available
-Mem:           966Mi       412Mi       215Mi       0.0Ki       338Mi       404Mi
-Swap:             0B          0B          0B
-test-user@ip-172-31-53-181:~$ free -h
-               total        used        free      shared  buff/cache   available
-Mem:           1.9Gi       225Mi       1.3Gi       0.0Ki       447Mi       1.6Gi
-Swap:             0B          0B          0B</code></pre>
-<p>I got twice as much RAM!</p>
-<p>There are some rules around being able to change from one instance type to another…but this is an amazing superpower if you’ve got variable workloads or a team that’s growing. The ability to scale a machine so easily is a game-changer.</p>
-<p>The work we did in earlier lab chapters, for example adding the elastic IP and daemonizing JupyterHub, are the reason that we’re able to bring it back up so smoothly.</p>
-<p>It’s similarly easy to resize the EBS volume attached to your server for more storage.</p>
-<p>There are two caveats worth knowing for EBS:</p>
-<ol type="1">
-<li>You can only automatically adjust volume sizes <em>up</em>, so you’d have to manually transfer all of your data if you ever wanted to scale back down.</li>
-<li>If you resize the volume, you’ll also have to adjust the Linux filesystem so it knows about the new space available. AWS has a great walk through called <a href="https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/recognize-expanded-volume-linux.html">Extend a Linux filesystem after resizing the volume</a> that I recommend you follow.</li>
-</ol>
-
-
-</section>
-</section>
-<section id="footnotes" class="footnotes footnotes-end-of-document" role="doc-endnotes">
-<hr>
-<ol>
-<li id="fn1"><p>The reason why this is the case and how it works is fascinating. If you’re interested, it comes back to Alan Turing’s famous paper on computability. I recommend <a href="https://www.goodreads.com/en/book/show/2333956.The_Annotated_Turing"><strong>The Annotated Turing: A Guided Tour Through Alan Turing’s Historic Paper on Computability and the Turing Machine</strong></a> by Charles Petzold for a surprisingly readable walkthrough of the paper.<a href="#fnref1" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
-<li id="fn2"><p>You probably don’t experience this personally. Modern computers are pretty smart about dumping RAM onto the hard disk before shutting down, and bringing it back on startup, so you usually won’t notice this happening.<a href="#fnref2" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
-</ol>
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-  <li><a href="#what-enterprise-it-is-about" id="toc-what-enterprise-it-is-about" class="nav-link active" data-scroll-target="#what-enterprise-it-is-about">What enterprise IT is about</a></li>
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-<h1 class="title"><span id="sec-4-intro" class="quarto-section-identifier">Making it Enterprise-Grade</span></h1>
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-<p>Over the last few chapters, we walked through getting set up with a server, accessing and managing the server via SSH, understanding DNS and getting a real URL, securing the server with SSL/HTTPS, and right-sizing the server for your needs.</p>
-<p>And if you walked through the process with the labs, you’ve got a data science workbench running RStudio Server, JupyterHub, and a model-serving API all of your own. That’s awesome!</p>
-<p>That server is great if you’re working alone on some data science projects you want to host in the cloud or if you’ve got a small team of data scientists in a small organization.</p>
-<p>But if you work at a large organization, an organization with more-stringent security needs, or a larger team of data scientists, you’re going to need to start considering some more complex ways of managing your data science environment for security and stability.</p>
-<p>Broadly speaking, these concerns fall under the context of <em>enterprise</em>. In this context, Enterprise roughly translates to “a large organization with well-defined IT/Admin responsibilities and roles”. If you’re not in an Enterprise, you likely have the rights and ability to just stand up a data science workbench and use it, like we did in the last section.</p>
-<p>If you are in an Enterprise, you probably had to do all that on a personal account, and almost certainly couldn’t connect to your real data sources.</p>
-<p>In general, organizations are trying to implement something called the <em>principle of least privilege</em>. The idea behind this is that they are trying to keep systems safe and stable by giving people the permissions they need to get their work done – and no more. For example, let’s say you’re working in a data science workbench environment. You need a place where you can write code and load data. It might occasionally be useful to have root access on the server to be able to make updates to the server. But are you going to get that in an enterprise environment? Almost certainly not, because you don’t need it to get your work done day-to-day. Instead, you’ll have to coordinate with the IT/Admin team if you need to get something done that requires root access.</p>
-<p>Doing open source data science in an Enterprise almost certainly means having to work across teams to get your workbench built and having to convince other people that you’ll be a good actor at the end of the day.</p>
-<p>The goal of the next few chapters is to help you understand the ways your data science workbench isn’t enterprise and how to communicate with the IT/Admins at your organization who are responsible for such things. We’ll get into how to integrate open-source data science into an organization, what more complex network architecture might look like, how auth works, and how to scale your environment.</p>
-<p>Hopefully you won’t have to implement much of this yourself. Instead, the hope is that reading and understanding the content in this chapter will help make you a better partner to the teams at your organization who <em>are</em> responsible for these things. You’ll be equipped with the language and mental models to ask good questions and give informative answers to the questions the IT/Admins have about your team’s requirements.</p>
-<section id="what-enterprise-it-is-about" class="level2">
-<h2 class="anchored" data-anchor-id="what-enterprise-it-is-about">What enterprise IT is about</h2>
-<p>As a data scientist, your primary concern about your data science environment is that it’s useful. You want to be able to get all the data you want at your fingertips.</p>
-<p>Many data scientists in enterprises find that this desire runs headlong into requirements from their organization’s IT/Admin teams.</p>
-<p>This can be extremely frustrating, so it’s helpful to understand the concerns enterprise IT/Admins have in mind. Broadly, IT/Admins care about the security and stability of the systems they control.</p>
-<p>Great IT/Admin teams also care about the usefulness of the system to users (that’s you), but it’s usually a distant third. And there is sometimes a tension here. After all the only system that’s completely secure is the one that doesn’t exist at all.</p>
-<p>But that’s not always the case. Often, there’s a lot to gain by partnering with the IT/Admin team at your organization. You may be primarily focused on getting stuff done minute-to-minute, but a data science platform that is insecure and allows bad actors to break in and steal data is not useful. And one where you can do what you want but end up crashing the workbench for 50 other users is ultimately self-defeating.</p>
-<p>Balancing security, stability, and usefulness is always about tradeoffs. Great IT/Admin organizations are constantly in conversations with other parts of the organization to figure out the right stance for your organization given the set of tradeoffs you face.</p>
-<p>Unfortunately, many IT/Admin organizations don’t act that way – they act as gatekeepers to the resources you need to do your job. That means you’ll have to figure out how to communicate with those teams, understand what matters to them, help them understand what matters to you, and reach acceptable organizational outcomes.</p>
-<p>You probably already have a good understanding of how a data science environment can be useful – but what about secure and stable. What do they mean?</p>
-<p>Security is about making sure that the right people can interact with the systems they’re supposed to and that unauthorized people can’t.</p>
-<p>IT security professionals think about <em>security in layers</em>. And while you’ve done a good job setting your server up to comply with basic security best practices, there are no layers. That server front door is open to the internet. Literally anyone in the world can come to that authentication page for your RStudio Server or JupyterHub and start trying out passwords. That means you’re just one person choosing the password <code>password</code> away from a bad actor getting access to your server.</p>
-<p>Lest you think you’re immune because you’re not an interesting target, there are plenty of bots out there randomly trying to break in to every existing IP address, not because they care about what’s inside, but because they want to co-opt your resources for their own purposes like crypto mining or virtual DDOS attacks on Turkish banks.<a href="#fn1" class="footnote-ref" id="fnref1" role="doc-noteref"><sup>1</sup></a></p>
-<p>Moreover, security and IT professionals aren’t just concerned with bad actors from outside (called outsider threat) or even someone internal who decides to steal data or resources (insider threat). They are (or at least should be) also concerned with accidents and mistakes – data that is accidentally permanently deleted is bad the same way stolen data is bad.</p>
-<p>Stability is ensuring enterprise-grade systems are around when people need them, and that they are stable during whatever load they face during the course of operating. The importance of stability tends to rise along with the scale of the team and the centrality of their operations to the functioning of your organization.</p>
-<p>If you’re a team of three data scientists who sit in a room together, it probably won’t be a huge deal if someone accidentally knocks your data science workbench offline for 30 minutes because they tried to run a job that was too big. You’re probably all sitting in the same room and you can learn something from the experience.</p>
-<p>That’s not the case when you get to enterprise-grade tooling. An enterprise-grade data science workbench probably supports dozens or hundreds of professionals across multiple teams. The server being down isn’t a sorta funny occurrence you can all fix together – it’s a problem that must be fixed immediately – or even better avoided altogether.</p>
-<p>IT/Admins think hard about how to provide resources in a way that avoids having servers go down because they’re hitting resource constraints.</p>
-<p>One thing that is almost certain to be untrue in an enterprise context is that you’ll have root access as a user of the system.</p>
-<p>There is no one-size-fits-all (or even most) position for security. Instead, great security teams are constantly articulating and making decisions about tradeoffs.</p>
-</section>
-<section id="labs-in-this-section" class="level2">
-<h2 class="anchored" data-anchor-id="labs-in-this-section">Labs in this Section</h2>
-<p>There are no labs in this section. This section is about how to interact with a professional IT/Admin group. Since it’s about work you really shouldn’t undertake yourself, there are no labs for you to DIY these things.</p>
-<p>If you want to go deeper into any of the topics, there are plenty of great resources online – a google search should turn them up quickly</p>
-
-
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-<hr>
-<ol>
-<li id="fn1"><p>Yes, these both really happened.<a href="#fnref1" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
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- <span class="menu-text"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Getting Started with the Cloud</span></span></a>
+  <a href="./chapters/sec2/2-5-scale.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Server Resources and Scaling</span></span></a>
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-  <a href="./chapters/sec3/3-2-linux-admin.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Basic Linux SysAdmin</span></span></a>
-  </div>
-</li>
-          <li class="sidebar-item">
-  <div class="sidebar-item-container"> 
-  <a href="./chapters/sec3/3-3-networking.html" class="sidebar-item-text sidebar-link">
+  <a href="./chapters/sec2/2-6-networking.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">12</span>&nbsp; <span class="chapter-title">Intro to Computer Networks</span></span></a>
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-  <a href="./chapters/sec3/3-4-dns.html" class="sidebar-item-text sidebar-link">
+  <a href="./chapters/sec2/2-7-dns.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">13</span>&nbsp; <span class="chapter-title">DNS allows for human-readable addresses</span></span></a>
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-  <a href="./chapters/sec3/3-5-ssl.html" class="sidebar-item-text sidebar-link">
+  <a href="./chapters/sec2/2-8-ssl.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">14</span>&nbsp; <span class="chapter-title">You should use SSL/HTTPS</span></span></a>
   </div>
-</li>
-          <li class="sidebar-item">
-  <div class="sidebar-item-container"> 
-  <a href="./chapters/sec3/3-6-servers.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Choosing the right server for you</span></span></a>
-  </div>
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       <div class="sidebar-item-container"> 
-            <a href="./chapters/sec4/4-0-sec-intro.html" class="sidebar-item-text sidebar-link">
+            <a href="./chapters/sec3/3-0-sec-intro.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text">Making it Enterprise-Grade</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true" aria-label="Toggle section">
+          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-3" aria-expanded="true" aria-label="Toggle section">
             <i class="bi bi-chevron-right ms-2"></i>
           </a> 
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-      <ul id="quarto-sidebar-section-4" class="collapse list-unstyled sidebar-section depth1 show">  
+      <ul id="quarto-sidebar-section-3" class="collapse list-unstyled sidebar-section depth1 show">  
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
-  <a href="./chapters/sec4/4-1-os-ds-in-ent.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></a>
+  <a href="./chapters/sec3/3-1-os-ds-in-ent.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Open Source Data Science in the Enterprise</span></span></a>
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-  <a href="./chapters/sec4/4-2-ent-networks.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></a>
+  <a href="./chapters/sec3/3-2-ent-networks.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Enterprise Networking</span></span></a>
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-  <a href="./chapters/sec4/4-3-auth.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></a>
+  <a href="./chapters/sec3/3-3-auth.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Auth in Enterprise</span></span></a>
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-  <a href="./chapters/sec4/4-4-ent-servers.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">19</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></a>
+  <a href="./chapters/sec3/3-4-ent-servers.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Enterprise Server Management</span></span></a>
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-            <a class="sidebar-item-text sidebar-link text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-5" aria-expanded="true">
+            <a class="sidebar-item-text sidebar-link text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true">
  <span class="menu-text">Appendices</span></a>
-          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-5" aria-expanded="true" aria-label="Toggle section">
+          <a class="sidebar-item-toggle text-start" data-bs-toggle="collapse" data-bs-target="#quarto-sidebar-section-4" aria-expanded="true" aria-label="Toggle section">
             <i class="bi bi-chevron-right ms-2"></i>
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-      <ul id="quarto-sidebar-section-5" class="collapse list-unstyled sidebar-section depth1 show">  
+      <ul id="quarto-sidebar-section-4" class="collapse list-unstyled sidebar-section depth1 show">  
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  <span class="menu-text"><span class="chapter-number">B</span>&nbsp; <span class="chapter-title">Lab Map</span></span></a>
   </div>
+</li>
+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="./chapters/append/cheatsheets.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">C</span>&nbsp; <span class="chapter-title">Cheatsheets</span></span></a>
+  </div>
 </li>
       </ul>
   </li>
diff --git a/search.json b/search.json
index a3e1b8e46..b02353801 100644
--- a/search.json
+++ b/search.json
@@ -53,7 +53,7 @@
     "href": "chapters/intro.html#about-this-book",
     "title": "Introduction",
     "section": "About this book",
-    "text": "About this book\nOver the course of engaging with many organizations, I’ve seen which patterns work to grease the path to production for data scientists and which ones tend to impede it.\nMy goal is that this book helps you create data science projects that are easier and simpler to deploy, and that you have the knowledge and skills to get them into production when it’s time.\nTo that end this book is divided into four sections.\nSection 1 is about applying DevOps best practices to a data science context. There’s a lot data scientists can learn from DevOps, but there are important differences between data science and general purpose software engineering that you’ll learn about.\nSection 2 is an introduction to the tools IT/Admins use in their work like the command line, bash, and Docker. These tools are all useful for you to understand as a data scientist and also will be useful if you end up having to do any IT/Admin tasks.\nSection 3 is a walk through of basic concepts in IT Administration that will get you to the point of being able to host and manage your own small server. If you are a hobbyist or have only a small data science team, this might make you able to operate without any IT/Admin support. Even if you do work at an organization with significant IT/Admin support, it will equip you with the vocabulary to talk to the IT/Admins at your organization and some basic skills of how to do IT/Admin tasks yourself.\nSection 4 is about how all of what you learned in Section 3 changes when you go to enterprise scale. If section 3 explains how to do IT/Admin tasks yourself, section 4 is my attempt to explain why you shouldn’t.\n\nComprehension Questions\nEach chapter in this book includes comprehension questions. As you get to the end of the chapter, take a moment to consider these questions. If you feel comfortable answering them, you’ve probably understood the content of the chapter pretty well.\nAlternatively, feel free to jump ahead to them as you’re reading the chapter. If you can already answer them all, you can probably skip that chapter.\n\n\n\n\n\n\nMental Models + Mental Maps\n\n\n\nThroughout the book, I’ll talk a lot about building a mental model of different concepts.\nA mental map is a way to represent mental models.\nIn a mental map, you draw each of the nouns as nodes and connect them with arrows that are labelled to explain the relationship.\nMental maps are a great way to test your mental models, so I’ll suggest them as comprehension questions in many chapters.\nHere’s an example about this book:\n\n\n\n\ngraph LR\n    A[I] --&gt;|Wrote| B[DO4DS]\n    C[You] --&gt; |Are Reading| B\n    B --&gt; |Includes| D[Exercises]\n    D --&gt; |Some Are| E[Mind Maps]\n\n\n\n\n\nNote how every node is a noun and the edges (labels on the arrows) are verbs. It’s pretty simple! But writing down the relationships between entities like this is a great check on understanding.\n\n\n\n\nLabs\nMany chapters also contain labs. The idea of these labs is to give you hands-on experience with the concepts at hand.\nThese labs all tie together. If you follow the labs in this book, you’ll build up a reasonably complete data science platform that includes a place for you to work, a way to store data, and a deployment environment.\nPalmer Penguins is a public dataset meant for demonstrating data exploration and visualization. We’re going to pretend we care deeply about the relationship between penguin bill length and mass and we’re going to build up an entire data science environment dedicated to exploring that relationship.\nThe front end of this environment is going to be a website that contains an app that allows you to get predictions from a machine learning model of a penguin’s mass based on bill length and other features. We’re also going to include pages dedicated to exploratory data analysis and model building on the website.\nOn the backend, we’re going to build a data science workbench on an AWS EC2 instance where we can do this work. It will include RStudio Server and JupyterHub for working. It will additionally host the machine learning model as an API and the Shiny app that appears on the website.\nThe whole thing will get auto-deployed from a git repo using GitHub Actions.\nFrom an architectural perspective, it’ll look something like this:\n\n\n\n\n\ngraph LR\n    subgraph Palmer Penguins Site\n        A[\"EDA \n        R Quarto\"] \n        B[\"Model Build \n        Jupyter\"] \n        C[\"Model Explorer \n        PyShiny\"]\n    end\n    subgraph Git Repo\n        D[Repo] --&gt; |GHA| A\n        D --&gt; |GHA| B\n    end\n    subgraph AWS\n        subgraph EC2\n            F[Shiny]\n            G(RStudio Server)\n            H(Jupyter Hub)\n            I[FastAPI]\n            J[DuckDB]\n            J --&gt; I\n            F --&gt; C\n        end\n        subgraph S3\n            E[Model]\n        end\n    end\n\n\n\n\n\n\nIf you’re interested in exactly which pieces get completed in each chapter, check out Appendix B.\n\n\nConventions\nThroughout the book, I will italicize terms of art the first time I introduce them as well as the names of other publications. Bolding will be reserved for emphasis.\nR, Python, and system package names will be in code font and will have braces around them like {package}.\nVariables that you would replace with your own values will appear in code font inside angled brackets like &lt;your-variable&gt;."
+    "text": "About this book\nOver the course of engaging with many organizations, I’ve seen which patterns work to grease the path to production for data scientists and which ones tend to impede it.\nMy goal is that this book helps you create data science projects that are easier and simpler to deploy, and that you have the knowledge and skills to get them into production when it’s time.\nTo that end this book is divided into three sections.\nSection 1 is about applying DevOps best practices to a data science context. There’s a lot data scientists can learn from DevOps, but there are important differences between data science and general purpose software engineering that you’ll learn about.\nSection 2 is a walk through of basic concepts in IT Administration that will get you to the point of being able to host and manage your own small server. If you are a hobbyist or have only a small data science team, this might make you able to operate without any IT/Admin support. Even if you do work at an organization with significant IT/Admin support, it will equip you with the vocabulary to talk to the IT/Admins at your organization and some basic skills of how to do IT/Admin tasks yourself.\nSection 3 is about how all of what you learned in Section 2 changes when you go to enterprise scale. If section 2 explains how to do IT/Admin tasks yourself, section 3 is my attempt to explain why you shouldn’t.\n\nComprehension Questions\nEach chapter in this book includes comprehension questions. As you get to the end of the chapter, take a moment to consider these questions. If you feel comfortable answering them, you’ve probably understood the content of the chapter pretty well.\nAlternatively, feel free to jump ahead to them as you’re reading the chapter. If you can already answer them all, you can probably skip that chapter.\n\n\n\n\n\n\nMental Models + Mental Maps\n\n\n\nThroughout the book, I’ll talk a lot about building a mental model of different concepts.\nA mental map is a way to represent mental models.\nIn a mental map, you draw each of the nouns as nodes and connect them with arrows that are labelled to explain the relationship.\nMental maps are a great way to test your mental models, so I’ll suggest them as comprehension questions in many chapters.\nHere’s an example about this book:\n\nNote how every node is a noun and the edges (labels on the arrows) are verbs. It’s pretty simple! But writing down the relationships between entities like this is a great check on understanding.\n\n\n\n\nLabs\nMany chapters also contain labs. The idea of these labs is to give you hands-on experience with the concepts at hand.\nThese labs all tie together. If you follow the labs in this book, you’ll build up a reasonably complete data science platform that includes a place for you to work, a way to store data, and a deployment environment.\nPalmer Penguins is a public dataset meant for demonstrating data exploration and visualization. We’re going to pretend we care deeply about the relationship between penguin bill length and mass and we’re going to build up an entire data science environment dedicated to exploring that relationship.\nThe front end of this environment is going to be a website that contains an app that allows you to get predictions from a machine learning model of a penguin’s mass based on bill length and other features. We’re also going to include pages dedicated to exploratory data analysis and model building on the website.\nOn the backend, we’re going to build a data science workbench on an AWS EC2 instance where we can do this work. It will include RStudio Server and JupyterHub for working. It will additionally host the machine learning model as an API and the Shiny app that appears on the website.\nThe whole thing will get auto-deployed from a git repo using GitHub Actions.\nFrom an architectural perspective, it’ll look something like this:\n\nIf you’re interested in exactly which pieces get completed in each chapter, check out Appendix B.\n\n\nConventions\nThroughout the book, I will italicize terms of art the first time I introduce them as well as the names of other publications. Because so many of the technical terms in this book are usually referred to by abbreviations or acronyms, I’ll use the abbreviation or acronym in the text and include the full term in parentheses the first time it’s mentioned.\nBolding will be reserved for emphasis.\nR, Python, and system package names will be in code font and will have braces around them like {package}. Networking concepts and terms, including URLs, will appear in \\(\\text{equation font}\\).\nVariables that you would replace with your own values will appear in code font inside angled brackets like &lt;your-variable&gt;."
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     "title": "DevOps Lessons for Data Science",
     "section": "Labs in this section",
-    "text": "Labs in this section\nEach chapter in this section has a lab so you can get hands-on experience implementing the best practices I propose.\nIf you complete the labs, you’ll have stood up your Palmer Penguins website to explore the relationship between penguin bill length and mass. Your website will include pages on exploratory data analysis and model building. This website will automatically build and deploy based on changes in a git repo.\nBy the end of the section, you’ll also create a Shiny app that visualizes model predictions and an API that hosts the model and provides real-time predictions to the app. We won’t get to standing up the app and API to live on your website – that’ll have to wait for Section 3.\nFor more details on exactly what you’ll do in each chapter, see Appendix B."
+    "text": "Labs in this section\nEach chapter in this section has a lab so you can get hands-on experience implementing the best practices I propose.\nIf you complete the labs, you’ll have stood up your Palmer Penguins website to explore the relationship between penguin bill length and mass. Your website will include pages on exploratory data analysis and model building. This website will automatically build and deploy based on changes in a git repo.\nBy the end of the section, you’ll also create a Shiny app that visualizes model predictions and an API that hosts the model and provides real-time predictions to the app. Additionally, you’ll get to practice putting that API inside a Docker Container to see how using Docker can make your life easier when moving code around.\nFor more details on exactly what you’ll do in each chapter, see Appendix B."
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     "href": "chapters/sec1/1-1-env-as-code.html#reproducing-the-rest-of-the-stack",
     "title": "1  Environments as Code",
     "section": "1.5 Reproducing the rest of the stack",
-    "text": "1.5 Reproducing the rest of the stack\nAs a data scientist, your responsibility in a production environment ends at responsibly creating and using virtual environments for your packages. That said, there may not be an IT/Admin to take care of the rest for your team.\nLet’s talk a little about how to reproduce the rest of the stack.\nManaging R and Python versions has gotten easier over the years. There are great tools like {rig} in R and {pyenv} in Python that makes it easy to manage the versions of R and Python that are available on a system.\nMany R and Python libraries are wrappers for system libraries, often written in C++ for speed. For example, many popular packages for geospatial analysis are just thin language wrappers that call out to the system libraries. In this case, it might be important to be able to maintain a particular version of the underlying system library to ensure that your code runs at all in the future.\nThere are many tools you can use to record and reproduce the R and Python versions you’re using, the system libraries, and the operating system itself.\nThese days, the clear leader of the pack on this front is Docker. Since its introduction in 2013, it has become an increasingly popular way to create, maintain, and use standalone environments – and for good reason!\n\n\n\n\n\nIn most cases, the only requirement to run any Docker container is having Docker installed. If you put your project in a Docker container and it runs today, you can be reasonably confident that the container itself can run almost anywhere else, irrespective of what else is running on that machine.2\nIn Chapter 9, you’ll learn the basics of how to use Docker as a tool for reproducing a data science project and moving it around."
+    "text": "1.5 Reproducing the rest of the stack\nAs a data scientist, your responsibility in a production environment ends at responsibly creating and using virtual environments for your packages. That said, there may not be an IT/Admin to take care of the rest for your team.\nLet’s talk a little about how to reproduce the rest of the stack.\nManaging R and Python versions has gotten easier over the years. There are great tools like {rig} in R and {pyenv} in Python that makes it easy to manage the versions of R and Python that are available on a system.\nMany R and Python libraries are wrappers for system libraries, often written in C++ for speed. For example, many popular packages for geospatial analysis are just thin language wrappers that call out to the system libraries. In this case, it might be important to be able to maintain a particular version of the underlying system library to ensure that your code runs at all in the future.\nThere are many tools you can use to record and reproduce the R and Python versions you’re using, the system libraries, and the operating system itself.\nThese days, the clear leader of the pack on this front is Docker. Since its introduction in 2013, it has become an increasingly popular way to create, maintain, and use standalone environments – and for good reason!\n\n\n\n\n\nIn most cases, the only requirement to run any Docker container is having Docker installed. If you put your project in a Docker container and it runs today, you can be reasonably confident that the container itself can run almost anywhere else, irrespective of what else is running on that machine.2\nIn Chapter 6, you’ll learn the basics of how to use Docker as a tool for reproducing a data science project and moving it around."
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     "title": "1  Environments as Code",
     "section": "1.8 Cheatsheet: Environments as Code",
-    "text": "1.8 Cheatsheet: Environments as Code\n\n1.8.1 Checking library + repository status\n\n\n\n\n\n\n\n\nStep\nR Command\nPython Command\n\n\n\n\nCheck whether library in sync with lockfile.\nre nv::status()\nNone\n\n\n\n\n\n1.8.2 Creating and Using a Standalone Project Library\nMake sure you’re in a standalone project library.\n\n\n\n\n\n\n\n\nStep\nR Command\nPython Command\n\n\n\n\nMake sure you’ve got {r  env}/{venv}.\nin s t a l l .packages(\"renv\")\nIncluded w/ Python 3.5+\n\n\nCreate a standalone library.\nrenv::init()\np y t hon -m venv &lt;dir&gt;\nConvention: u s e .venv for &lt;dir&gt;\n\n\nActivate project library.\nrenv::activate()\nHappens automatically if using projects.\nsou r c e &lt; d ir&gt; /bin/activate\n\n\nInstall packages as normal.\nins t a l l . packages(\"&lt;pkg&gt;\")\npyth o n - m pip install &lt;pkg&gt;\n\n\nSnapshot package state.\nrenv::snapshot()\npip fr e e z e &gt;  requirements.txt\n\n\nExit project environment.\nLeave R project.\ndeactivate\n\n\n\n\n\n1.8.3 Collaborating on someone else’s project\nStart by downloading the project into a directory on your machine.\n\n\n\n\n\n\n\n\nStep\nR Command\nPython Command\n\n\n\n\nMove into project directory.\nse t w d (\"&lt;project-dir&gt;\")\nOr just open R project in RStudio.\ncd &lt;project-dir&gt;\n\n\nCreate project environment.\nrenv::init()\np y t hon -m venv &lt;dir&gt;\nRecommend: u s e .venv for &lt;dir&gt;\n\n\nEnter project environment.\nHappens automatically or renv::activate()\ns o u rce &lt; d ir&gt; /bin/activate\n\n\nRestore packages.\nHappens automatically or renv::restore()\np ip i n s t all - r  requirements.txt"
+    "text": "1.8 Cheatsheet: Environments as Code\n\n1.8.1 Checking library + repository status\n\n\n\n\n\n\n\n\nStep\nR Command\nPython Command\n\n\n\n\nCheck whether library in sync with lockfile.\nre nv::status()\nNone\n\n\n\n\n\n1.8.2 Creating and Using a Standalone Project Library\nMake sure you’re in a standalone project library.\n\n\n\n\n\n\n\n\nStep\nR Command\nPython Command\n\n\n\n\nMake sure you’ve got {r  env}/{venv}.\nin s t a l l  .packages(\"renv\")\nIncluded w/ Python 3.5+\n\n\nCreate a standalone library.\nrenv::init()\np y t  hon -m venv &lt;dir&gt;\nConvention: u s  e .venv for &lt;dir&gt;\n\n\nActivate project library.\nrenv::activate()\nHappens automatically if using projects.\nsou r c e &lt; d  ir&gt; /bin/activate\n\n\nInstall packages as normal.\nins t a l l .  packages(\"&lt;pkg&gt;\")\npyth o n - m  pip install &lt;pkg&gt;\n\n\nSnapshot package state.\nrenv::snapshot()\npip fr e e z e &gt;   requirements.txt\n\n\nExit project environment.\nLeave R project.\ndeactivate\n\n\n\n\n\n1.8.3 Collaborating on someone else’s project\nStart by downloading the project into a directory on your machine.\n\n\n\n\n\n\n\n\nStep\nR Command\nPython Command\n\n\n\n\nMove into project directory.\nset wd  (\"&lt;project-dir&gt;\")\nOr just open R project in RStudio.\ncd &lt;project-dir&gt;\n\n\nCreate project environment.\nrenv::init()\npy thon -m venv &lt;dir&gt;\nRecommend: u se .venv for &lt;dir&gt;\n\n\nEnter project environment.\nHappens automatically or renv::activate()\nsource &lt; dir&gt; /bin/activate\n\n\nRestore packages.\nHappens automatically or renv::restore()\npip install -r   requirements.txt"
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     "title": "2  Data Project Architecture Guidelines",
     "section": "2.7 Consider auth to data up front",
-    "text": "2.7 Consider auth to data up front\nIf everyone who views your project has the same permissions to see the data, life is easy. You can just allow the project access to the data and check for authorization to view the project.\nBut if you need to provide different data access to different users, you’re much more constrained. First off, you probably need to use an app rather than a report so that you can respond to which user is accessing the app.\nThen you have to figure out how you’re actually going to change data access based on who’s viewing the app.\nSometimes this can be accomplished in the app itself. Many app frameworks pass the username or user groups into the session, and you can write code that changes app behavior based on the user. For example, you can gate access to certain tabs or features of your app based on the user.\nSometimes you’ll actually have to pass database credentials along to the database. If this is the case for you, you’ll need to figure out how to establish the user’s database credentials, how to make sure those credentials stay only in the user’s session, and how those credentials get passed along to the database. This is most commonly done with technologies like Kerberos or OAuth and require coordination with an IT/Admin. More on this topic in Chapter 18."
+    "text": "2.7 Consider auth to data up front\nIf everyone who views your project has the same permissions to see the data, life is easy. You can just allow the project access to the data and check for authorization to view the project.\nBut if you need to provide different data access to different users, you’re much more constrained. First off, you probably need to use an app rather than a report so that you can respond to which user is accessing the app.\nThen you have to figure out how you’re actually going to change data access based on who’s viewing the app.\nSometimes this can be accomplished in the app itself. Many app frameworks pass the username or user groups into the session, and you can write code that changes app behavior based on the user. For example, you can gate access to certain tabs or features of your app based on the user.\nSometimes you’ll actually have to pass database credentials along to the database. If this is the case for you, you’ll need to figure out how to establish the user’s database credentials, how to make sure those credentials stay only in the user’s session, and how those credentials get passed along to the database. This is most commonly done with technologies like Kerberos or OAuth and require coordination with an IT/Admin. More on this topic in Chapter 17."
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     "title": "3  Using databases and data APIs",
     "section": "3.3 Environment variables to secure data connections",
-    "text": "3.3 Environment variables to secure data connections\nWhen you take an app to production, authenticating to your data source while keeping your secrets secure is crucial.\nThe single most important thing you can do to secure your credentials is to avoid ever putting credentials in your code. Your username and password or API key should never appear in your code.\nThe simplest way to provide credentials without the values appearing in your code is with an environment variable. Environment variables are set before your code starts – sometimes from completely outside Python or R.\n\n3.3.1 Getting environment variables\nThe power of using an environment variable is that you reference them by name. Just sharing that there’s an environment variable called API_KEY doesn’t reveal anything secret, so if your code just includes environment variables, it’s completely safe to share with others.\n\n\n\n\n\n\nNote\n\n\n\nIt is convention to make environment variable names in all caps with words separated by underscores. The values are always simple character values, though these can be cast to some other type inside R or Python.\n\n\nIn Python, you can read environment variables from the os.environ dictionary or by using os.getenv(\"&lt;VAR_NAME&gt;\"). In R, you can get environment variables with Sys.getenv(\"&lt;VAR_NAME&gt;\").\nIt’s common to provide environment variables directly to functions as arguments, though you can also put the values in normal Python or R variables and use them from there.\n\n\n3.3.2 Setting environment variables\nThe most common way to set environment variables in a development environment is to load secrets from a plain text file. In Python, environment variables are usually set by reading a .env file into your Python session. The {python-dotenv} package is a good choice for doing this.\nR automatically reads the .Renviron file as environment variables and also sources the .Rprofile file, where you can set environment variables with Sys.setenv(). I personally prefer putting everything in .Rprofile for simplicity – but that’s not a universal opinion.\nSome organizations don’t ever want credentials files in plain text. After all, if someone stole a plain text secrets file, there’s nothing to stop them from using them.\nThere are packages in both R and Python called {keyring} that allow you to use the system keyring to securely store environment variables and recall them at runtime.\nSetting environment variables in production is a little harder.\nJust moving your secrets from your code into a different file you push to prod is still bad. And using {keyring} in a production environment is quite cumbersome.\nYour production environment may provide environment management tools. For example, GitHub Actions and Posit Connect both provide you the ability to set secrets that aren’t visible to the users, but are accessible to the code at runtime in an environment variable.\nIncreasingly, organizations are using token-based authorization schemes that just exchange one cryptographically secure token for another, never relying on credentials at all. The tradeoff for the enhanced security is that they can be difficult to implement, likely requiring coordination with an IT/Admin to use technologies like Kerberos or OAuth. There’s more on how to do that in Chapter 18."
+    "text": "3.3 Environment variables to secure data connections\nWhen you take an app to production, authenticating to your data source while keeping your secrets secure is crucial.\nThe single most important thing you can do to secure your credentials is to avoid ever putting credentials in your code. Your username and password or API key should never appear in your code.\nThe simplest way to provide credentials without the values appearing in your code is with an environment variable. Environment variables are set before your code starts – sometimes from completely outside Python or R.\n\n3.3.1 Getting environment variables\nThe power of using an environment variable is that you reference them by name. Just sharing that there’s an environment variable called API_KEY doesn’t reveal anything secret, so if your code just includes environment variables, it’s completely safe to share with others.\n\n\n\n\n\n\nNote\n\n\n\nIt is convention to make environment variable names in all caps with words separated by underscores. The values are always simple character values, though these can be cast to some other type inside R or Python.\n\n\nIn Python, you can read environment variables from the os.environ dictionary or by using os.getenv(\"&lt;VAR_NAME&gt;\"). In R, you can get environment variables with Sys.getenv(\"&lt;VAR_NAME&gt;\").\nIt’s common to provide environment variables directly to functions as arguments, though you can also put the values in normal Python or R variables and use them from there.\n\n\n3.3.2 Setting environment variables\nThe most common way to set environment variables in a development environment is to load secrets from a plain text file. In Python, environment variables are usually set by reading a .env file into your Python session. The {python-dotenv} package is a good choice for doing this.\nR automatically reads the .Renviron file as environment variables and also sources the .Rprofile file, where you can set environment variables with Sys.setenv(). I personally prefer putting everything in .Rprofile for simplicity – but that’s not a universal opinion.\nSome organizations don’t ever want credentials files in plain text. After all, if someone stole a plain text secrets file, there’s nothing to stop them from using them.\nThere are packages in both R and Python called {keyring} that allow you to use the system keyring to securely store environment variables and recall them at runtime.\nSetting environment variables in production is a little harder.\nJust moving your secrets from your code into a different file you push to prod is still bad. And using {keyring} in a production environment is quite cumbersome.\nYour production environment may provide environment management tools. For example, GitHub Actions and Posit Connect both provide you the ability to set secrets that aren’t visible to the users, but are accessible to the code at runtime in an environment variable.\nIncreasingly, organizations are using token-based authorization schemes that just exchange one cryptographically secure token for another, never relying on credentials at all. The tradeoff for the enhanced security is that they can be difficult to implement, likely requiring coordination with an IT/Admin to use technologies like Kerberos or OAuth. There’s more on how to do that in Chapter 17."
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     "text": "3.6 Lab 3: Use a database and an API\nIn this lab, we’re going to build out both the data layer and the presentation layer for our penguin mass model exploration. We’re going to create an app to explore the model, which will look like this: \nLet’s start by moving the data into a real data layer.\n\n3.6.1 Step 1: Put the data in DuckDB\nLet’s start by moving the data into a DuckDB database and use it from there for the modeling and EDA scripts.\nTo start, let’s load the data.\nHere’s what that looks like in R:\ncon &lt;- DBI::dbConnect(duckdb::duckdb(), dbdir = \"my-db.duckdb\")\nDBI::dbWriteTable(con, \"penguins\", palmerpenguins::penguins)\nDBI::dbDisconnect(con)\nOr equivalently, in Python:\nimport duckdb\nfrom palmerpenguins import penguins\n\ncon = duckdb.connect('my-db.duckdb')\ndf = penguins.load_penguins()\ncon.execute('CREATE TABLE penguins AS SELECT * FROM df')\ncon.close()\nNow that the data is loaded, let’s adjust our scripts to use the database.\nIn R, we are just going to replace our data loading with connecting to the database. Leaving out all the parts that don’t change, it looks like\n\n\neda.qmd\n\n\ncon &lt;- DBI::dbConnect(\n  duckdb::duckdb(), \n  dbdir = \"my-db.duckdb\"\n  )\ndf &lt;- dplyr::tbl(con, \"penguins\")\n\nWe also need to call to DBI::dbDisconnect(con) at the end of the script.\nBecause we wrote our data processing code in {dplyr}, we actually don’t have to change anything. Under the hood, {dplyr} can switch seamlessly to a database backend, which is really cool.\n\n\neda.qmd\n\ndf %&gt;%\n  group_by(species, sex) %&gt;%\n  summarise(\n    across(\n        ends_with(\"mm\") | ends_with(\"g\"),\n      \\(x) mean(x, na.rm = TRUE)\n      )\n    ) %&gt;%\n  dplyr::collect() %&gt;%\n  knitr::kable()\n\nIt’s not necessary, but I’ve added a call to dplyr::collect in line 31. It will be implied if I don’t put it there manually, but it helps make obvious that all the work before there has been pushed off to the database. Only the result of this code is coming back to the R process. Obviously it doesn’t matter for this small dataset, but this would be a huge benefit if the dataset were much larger.\nIn Python, we’re just going to load the entire dataset into memory for modeling, so the line loading the dataset changes to\n\n\nmodel.qmd\n\ncon = duckdb.connect('my-db.duckdb')\ndf = con.execute(\"SELECT * FROM penguins\").fetchdf().dropna()\ncon.close()\n\n\nNow let’s switch to figuring out the connection we’ll need to our processing layer in the presentation layer.\n\n\n3.6.2 Step 2: Call the model API from code\nBefore you start, make sure the API is running on your machine from the last lab.\n\n\n\n\n\n\nNote\n\n\n\nI’m assuming it’s running on port 8080 in this lab. If you’ve put it somewhere else, change the 8080 in the code below to match the port on your machine.\n\n\nIf you want to call the model in code, you can use any http request library. In R you should use httr2 and in Python you should use requests.\nHere’s what it looks like to call the API in Python\n\nimport requests\n\nreq_data = {\n  \"bill_length_mm\": 0,\n  \"species_Chinstrap\": False,\n  \"species_Gentoo\": False,\n  \"sex_male\": False\n}\nreq = requests.post('http://127.0.0.1:8080/predict', json = req_data)\nres = req.json().get('predict')[0]\n\nor equivalently in R\n\nreq &lt;- httr2::request(\"http://127.0.0.1:8080/predict\") |&gt;\n  httr2::req_body_json(\n    list(\n      \"bill_length_mm\" = 0,\n      \"species_Chinstrap\" = FALSE,\n      \"species_Gentoo\" = FALSE,\n      \"sex_male\" = FALSE\n    )\n  ) |&gt;\n  httr2::req_perform()\nres &lt;- httr2::resp_body_json(r)$predict[[1]]\n\nNote that there’s no translation necessary to send the request. The {requests} and{httr2} packages automatically know what to do with the Python dictionary and the R list.\nGetting the result back takes a little more work to find the right spot in the JSON returned. This is quite common.\n\n\n\n\n\n\nNote\n\n\n\nThe {vetiver} package also includes the ability to auto-query a {vetiver} API. I’m not using it here to expose the details of calling an API.\n\n\nNow, let’s take this API-calling code and build the presentation layer around it.\n\n\n3.6.3 Step 3: Build a shiny app\nWe’re going to use the {shiny} package, which is an R and Python package for creating interactive web apps using just Python code. If you don’t know much about {shiny}, you can choose to just blindly follow the examples here, or you could spend some time with the Mastering Shiny book to learn to use it yourself.\nEither way, an app that looks like the picture above would look like this in Python\n\n\napp.py\n\nfrom shiny import App, render, ui, reactive\nimport requests\n\napi_url = 'http://127.0.0.1:8080/predict'\n\napp_ui = ui.page_fluid(\n    ui.panel_title(\"Penguin Mass Predictor\"), \n    ui.layout_sidebar(\n        ui.panel_sidebar(\n            [ui.input_slider(\"bill_length\", \"Bill Length (mm)\", 30, 60, 45, step = 0.1),\n            ui.input_select(\"sex\", \"Sex\", [\"Male\", \"Female\"]),\n            ui.input_select(\"species\", \"Species\", [\"Adelie\", \"Chinstrap\", \"Gentoo\"]),\n            ui.input_action_button(\"predict\", \"Predict\")]\n        ),\n        ui.panel_main(\n            ui.h2(\"Penguin Parameters\"),\n            ui.output_text_verbatim(\"vals_out\"),\n            ui.h2(\"Predicted Penguin Mass (g)\"), \n            ui.output_text(\"pred_out\")\n        )\n    )   \n)\n\ndef server(input, output, session):\n    @reactive.Calc\n    def vals():\n        d = {\n            \"bill_length_mm\" : input.bill_length(),\n            \"sex_Male\" : input.sex() == \"Male\",\n            \"species_Gentoo\" : input.species() == \"Gentoo\", \n            \"species_Chinstrap\" : input.species() == \"Chinstrap\"\n\n        }\n        return d\n    \n    @reactive.Calc\n    @reactive.event(input.predict)\n    def pred():\n        r = requests.post(api_url, json = vals())\n        return r.json().get('predict')[0]\n\n    @output\n    @render.text\n    def vals_out():\n        return f\"{vals()}\"\n\n    @output\n    @render.text\n    def pred_out():\n        return f\"{round(pred())}\"\n\napp = App(app_ui, server)\n\nAnd like this in R\n\n\napp.R\n\nlibrary(shiny)\n\napi_url &lt;- \"http://127.0.0.1:8080/predict\"\n\nui &lt;- fluidPage(\n  titlePanel(\"Penguin Mass Predictor\"),\n\n  # Model input values\n  sidebarLayout(\n    sidebarPanel(\n      sliderInput(\n        \"bill_length\",\n        \"Bill Length (mm)\",\n        min = 30,\n        max = 60,\n        value = 45,\n        step = 0.1\n      ),\n      selectInput(\n        \"sex\",\n        \"Sex\",\n        c(\"Male\", \"Female\")\n      ),\n      selectInput(\n        \"species\",\n        \"Species\",\n        c(\"Adelie\", \"Chinstrap\", \"Gentoo\")\n      ),\n      # Get model predictions\n      actionButton(\n        \"predict\",\n        \"Predict\"\n      )\n    ),\n\n    mainPanel(\n      h2(\"Penguin Parameters\"),\n      verbatimTextOutput(\"vals\"),\n      h2(\"Predicted Penguin Mass (g)\"),\n      textOutput(\"pred\")\n    )\n  )\n)\n\nserver &lt;- function(input, output) {\n  # Input params\n  vals &lt;- reactive(\n    list(\n      bill_length_mm = input$bill_length,\n      species_Chinstrap = input$species == \"Chinstrap\",\n      species_Gentoo = input$species == \"Gentoo\",\n      sex_male = input$sex == \"Male\"\n    )\n  )\n\n  # Fetch prediction from API\n  pred &lt;- eventReactive(\n    input$predict,\n    httr2::request(api_url) |&gt;\n      httr2::req_body_json(vals()) |&gt;\n      httr2::req_perform() |&gt;\n      httr2::resp_body_json(),\n    ignoreInit = TRUE\n  )\n\n  # Render to UI\n  output$pred &lt;- renderText(pred()$predict[[1]])\n  output$vals &lt;- renderPrint(vals())\n}\n\n# Run the application\nshinyApp(ui = ui, server = server)\n\nOver the next few chapters, we’re going to implement more architectural best practices for the app, and in [Chapter @env-as-code] we’ll actually go to deployment."
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     "title": "3  Using databases and data APIs",
     "section": "3.7 HTTP Code Cheatsheet",
     "text": "3.7 HTTP Code Cheatsheet\nAs you work more with http traffic, you’ll learn some of the common codes. Here’s a cheatsheet for some of the most frequent you’ll see.\n\n\n\n\n\n\n\nCode\nMeaning\n\n\n\n\n200\nEveryone’s favorite, a successful response.\n\n\n3xx\nYour query was redirected somewhere else, usually ok.\n\n\n4xx\nErrors with the request\n\n\n400\nBad request. This isn’t a request the server can understand.\n\n\n401 and 403\nUnauthorized or forbidden. Required authentication hasn’t been provided.\n\n\n404\nNot found. There isn’t any content to access here.\n\n\n5xx\nErrors with the server once your request got there.\n\n\n500\nGeneric server-side error. Your request was received, but there was an error processing it.\n\n\n504\nGateway timeout. This means that a proxy or gateway between you and the server you’re trying to access timed out before it got a response from the server."
@@ -291,7 +291,7 @@
     "href": "chapters/sec1/1-4-monitor-log.html#observing-operations",
     "title": "4  Logging and Monitoring",
     "section": "4.2 Observing Operations",
-    "text": "4.2 Observing Operations\nNow let’s turn to the issue of observing the operational qualities of your code. The operational qualities of your project are things like the system resources its consuming, the number of users, and user interactions just before an error occurred.\nThe first step to making your app or API observable is to add logging. You may be used to just adding print statements throughout your code. And, honestly, this is far better than nothing. But purpose-built tooling for logging includes ways to apply consistent formats, emit logs in useful ways, and provide visibility into severity of issues.\nThere are great logging packages in both Python and R. Python’s logging package is standard. There is not a standard logging package in R, but I recommend {log4r}.\nThese packages – and basically every other logging package – work very similarly. At the outset of your code, you’ll create and parameterize a log session that persists as long as the Python or R session. When your code does something you want to love, you’ll you’ll use the log session to write log statements. When the log statement runs, it creates a log entry.\nFor example, here’s what logging for an app starting up might look like in Python\n\n\n\napp.py\n\nimport logging\n\n# Configure the log object\nlogging.basicConfig(\n    format='%(asctime)s - %(message)s',\n    level=logging.INFO\n)\n\n# Log app start\nlogging.info(\"App Started\")\n\n\nAnd here’s what that looks like using {log4r}\n\n\n\napp.R\n\n# Configure the log object\nlog &lt;- log4r::logger()\n\n# Log app start\nlog4r::info(log, \"App Started\")\n\n\nWhen the R or Python interpreter hits either of these lines, it will create a log entry that looks something like this:\n2022-11-18 21:57:50 INFO App Started\nLike all log entries, this entry has three components:\n\nThe log metadata is data what the logging library automatically includes on every entry. It is configured when you initialize logging. In the example above, the only metadata is the timestamp. Log metadata can include additional information, like which server you’re running on.\nThe second component is the log level. The log level indicates the severity of the event you’re logging. In the example above the log level was INFO.\nThe last component is the log data, which provides details on the event you want to log – App Started in this case.\n\n\n4.2.1 Understanding log levels\nThe log level indicates how serious the logged event is. Most logging libraries have 5-7 log levels. As you’re writing statements into your code, you’ll have to think carefully about the appropriate logging level for a given event.\nBoth the Python {logging} library and {log4r} have five levels from least to most scary:\n\nDebug: what the code was doing in detail that will only make sense to someone who really knows the code. For example, you might include which function ran and with what arguments in a debug log.\nInfo: something normal happened in the app. Info statements record things like starting and stopping, successfully making database and other connections, and runtime configuration options.\nWarn/Warning: an unexpected application issue that isn’t fatal. For example, you might include having to retry doing something or noticing that resource usage is high. If something were to go wrong later, these might be helpful breadcrumbs to look at.\nError: an issue that will make an operation not work, but that won’t bring down your app. An example might be a user submitting invalid input and the app recovering.\nCritical: an error so big that the app itself shuts down. This is the SOS your app sends as it shuts down. For example, if your app cannot run without a connection to an outside service, you might log an inability to connect as a Critical error.\n\nWhen you initialize your logging session, you’ll set your log level, which is the least critical level you want to see in the session. In development, you probably want to log everything down to the debug level, while that probably isn’t ideal in prod.\n\n\n4.2.2 Configuring log formats and log handling\nWhen you initialize your logging session, you’ll choose where logs will be written and in what format. You’ll configure the format with a formatter or layout and where it goes with a handler or an appender.\nFor most logging frameworks, the default is to emit logs to the console in plain text.\nFor example, a plain text log of an app starting might put this on your console\n2022-11-18 21:57:50 INFO App Started\nYou’ll decide the format of your log based on how you’re planning to consume them.\nPlain text logs is a great choice if humans are going to be directly reading them. If you’re shipping your logs off to an aggregation service, you might prefer to have structured logs.\nThe most common structured logging format is JSON, though YAML and XML are often options. If you used JSON logging, the same record might be emitted as\n{\n  \"time\": \"2022-11-18 21:57:50\",\n  \"level\": \"INFO\", \n  \"data\": \"App Started\"\n}\nWhere your logs go should be determined by where your code is running.\nIn development, printing logs for the console makes it easy to iterate quickly.\nIn production, the most common way to handle logs is to append them to a file. It makes them easy for humans to access and many tools for aggregating and consuming logs are comfortable watching a file and aggregating lines as they are written.\nIf you are emitting logs to file, you may also want to consider how long those logs stay around.\nLog rotation is the process of periodically creating new log files, storing old logs for a set retention period, and deleting files outside that period. A common log rotation pattern is to have a log file that lasts for 24 hours, is retained for 30 days, and is then deleted.\nThe Python {logging} library does log rotation itself. {log4r} does not, but there is a Linux library called logrotate that you can use in concert with {log4r}.1\nIf you’re running in a Docker container you don’t want to write to a file on disk. As you’ll learn more about in Chapter 9, anything that lives inside a Docker container is ephemeral. This is obviously bad if you’re writing a log that might contain clues for why a Docker container was unexpectedly killed.\nIn that case, it’s common practice for a service running in a container to emit logs inside the container and then have some sort of more permanent service collecting the logs outside. This is usually accomplished by sending normal operating logs to go to stdout (usually pronounced standard out) and failures to go to stderr (standard error).\nIt’s also possible you want to do something else completely custom with your logs. This is most common for critical or error logs. For example, you may want to send an email, slack, or text message immediately if your system emits a high-level log message.\nIt’s also very common to have different format and location settings in development vs in production. The most common way to enable different logging configurations in different environments is with config files and environment variables. More on how to use these tools in Chapter 1.\n\n\n4.2.3 Working with Metrics\nThe most common place to see metrics in a data science context is when deploying and monitoring ML models in production. Additionally, monitoring ETL data quality is ripe for more monitoring.\nIf you are going to configure metrics emission or consumption, most modern metrics stacks are built around the open source tools Prometheus and Grafana.\nPrometheus is an open source monitoring tool that makes it easy to store metrics data, query that data, and alert based on it. Grafana is an open source dashboarding tool that sits on top of Prometheus to do visualization of the metrics. They are usually used together to do monitoring and visualization of metrics.\nYou can run Prometheus and Grafana yourself, but Grafana Labs provides a generous free tier for their SaaS service. This is great because you can just set up their service and point your app to it.\nBecause the Prometheus/Grafana stack started out in the DevOps world, they are most optimized to do monitoring of a whole server or fleet of servers – but it’s not hard to use them to monitor things you might care about like data quality, API response times, or other things.\nIf you want to register metrics from your API or app with Prometheus, there is an official Prometheus client in Python and the {openmetrics} package in R makes it easy to register metrics from a Plumber API or Shiny app.\nThere’s a great Get Started with Grafana and Prometheus doc on the Grafana Labs website if you want to actually try it out."
+    "text": "4.2 Observing Operations\nNow let’s turn to the issue of observing the operational qualities of your code. The operational qualities of your project are things like the system resources its consuming, the number of users, and user interactions just before an error occurred.\nThe first step to making your app or API observable is to add logging. You may be used to just adding print statements throughout your code. And, honestly, this is far better than nothing. But purpose-built tooling for logging includes ways to apply consistent formats, emit logs in useful ways, and provide visibility into severity of issues.\nThere are great logging packages in both Python and R. Python’s logging package is standard. There is not a standard logging package in R, but I recommend {log4r}.\nThese packages – and basically every other logging package – work very similarly. At the outset of your code, you’ll create and parameterize a log session that persists as long as the Python or R session. When your code does something you want to love, you’ll you’ll use the log session to write log statements. When the log statement runs, it creates a log entry.\nFor example, here’s what logging for an app starting up might look like in Python\n\n\n\napp.py\n\nimport logging\n\n# Configure the log object\nlogging.basicConfig(\n    format='%(asctime)s - %(message)s',\n    level=logging.INFO\n)\n\n# Log app start\nlogging.info(\"App Started\")\n\n\nAnd here’s what that looks like using {log4r}\n\n\n\napp.R\n\n# Configure the log object\nlog &lt;- log4r::logger()\n\n# Log app start\nlog4r::info(log, \"App Started\")\n\n\nWhen the R or Python interpreter hits either of these lines, it will create a log entry that looks something like this:\n2022-11-18 21:57:50 INFO App Started\nLike all log entries, this entry has three components:\n\nThe log metadata is data what the logging library automatically includes on every entry. It is configured when you initialize logging. In the example above, the only metadata is the timestamp. Log metadata can include additional information, like which server you’re running on.\nThe second component is the log level. The log level indicates the severity of the event you’re logging. In the example above the log level was INFO.\nThe last component is the log data, which provides details on the event you want to log – App Started in this case.\n\n\n4.2.1 Understanding log levels\nThe log level indicates how serious the logged event is. Most logging libraries have 5-7 log levels. As you’re writing statements into your code, you’ll have to think carefully about the appropriate logging level for a given event.\nBoth the Python {logging} library and {log4r} have five levels from least to most scary:\n\nDebug: what the code was doing in detail that will only make sense to someone who really knows the code. For example, you might include which function ran and with what arguments in a debug log.\nInfo: something normal happened in the app. Info statements record things like starting and stopping, successfully making database and other connections, and runtime configuration options.\nWarn/Warning: an unexpected application issue that isn’t fatal. For example, you might include having to retry doing something or noticing that resource usage is high. If something were to go wrong later, these might be helpful breadcrumbs to look at.\nError: an issue that will make an operation not work, but that won’t bring down your app. An example might be a user submitting invalid input and the app recovering.\nCritical: an error so big that the app itself shuts down. This is the SOS your app sends as it shuts down. For example, if your app cannot run without a connection to an outside service, you might log an inability to connect as a Critical error.\n\nWhen you initialize your logging session, you’ll set your log level, which is the least critical level you want to see in the session. In development, you probably want to log everything down to the debug level, while that probably isn’t ideal in prod.\n\n\n4.2.2 Configuring log formats and log handling\nWhen you initialize your logging session, you’ll choose where logs will be written and in what format. You’ll configure the format with a formatter or layout and where it goes with a handler or an appender.\nFor most logging frameworks, the default is to emit logs to the console in plain text.\nFor example, a plain text log of an app starting might put this on your console\n2022-11-18 21:57:50 INFO App Started\nYou’ll decide the format of your log based on how you’re planning to consume them.\nPlain text logs is a great choice if humans are going to be directly reading them. If you’re shipping your logs off to an aggregation service, you might prefer to have structured logs.\nThe most common structured logging format is JSON, though YAML and XML are often options. If you used JSON logging, the same record might be emitted as\n{\n  \"time\": \"2022-11-18 21:57:50\",\n  \"level\": \"INFO\", \n  \"data\": \"App Started\"\n}\nWhere your logs go should be determined by where your code is running.\nIn development, printing logs for the console makes it easy to iterate quickly.\nIn production, the most common way to handle logs is to append them to a file. It makes them easy for humans to access and many tools for aggregating and consuming logs are comfortable watching a file and aggregating lines as they are written.\nIf you are emitting logs to file, you may also want to consider how long those logs stay around.\nLog rotation is the process of periodically creating new log files, storing old logs for a set retention period, and deleting files outside that period. A common log rotation pattern is to have a log file that lasts for 24 hours, is retained for 30 days, and is then deleted.\nThe Python {logging} library does log rotation itself. {log4r} does not, but there is a Linux library called logrotate that you can use in concert with {log4r}.1\nIf you’re running in a Docker container you don’t want to write to a file on disk. As you’ll learn more about in Chapter 6, anything that lives inside a Docker container is ephemeral. This is obviously bad if you’re writing a log that might contain clues for why a Docker container was unexpectedly killed.\nIn that case, it’s common practice for a service running in a container to emit logs inside the container and then have some sort of more permanent service collecting the logs outside. This is usually accomplished by sending normal operating logs to go to stdout (usually pronounced standard out) and failures to go to stderr (standard error).\nIt’s also possible you want to do something else completely custom with your logs. This is most common for critical or error logs. For example, you may want to send an email, slack, or text message immediately if your system emits a high-level log message.\nIt’s also very common to have different format and location settings in development vs in production. The most common way to enable different logging configurations in different environments is with config files and environment variables. More on how to use these tools in Chapter 1.\n\n\n4.2.3 Working with Metrics\nThe most common place to see metrics in a data science context is when deploying and monitoring ML models in production. Additionally, monitoring ETL data quality is ripe for more monitoring.\nIf you are going to configure metrics emission or consumption, most modern metrics stacks are built around the open source tools Prometheus and Grafana.\nPrometheus is an open source monitoring tool that makes it easy to store metrics data, query that data, and alert based on it. Grafana is an open source dashboarding tool that sits on top of Prometheus to do visualization of the metrics. They are usually used together to do monitoring and visualization of metrics.\nYou can run Prometheus and Grafana yourself, but Grafana Labs provides a generous free tier for their SaaS service. This is great because you can just set up their service and point your app to it.\nBecause the Prometheus/Grafana stack started out in the DevOps world, they are most optimized to do monitoring of a whole server or fleet of servers – but it’s not hard to use them to monitor things you might care about like data quality, API response times, or other things.\nIf you want to register metrics from your API or app with Prometheus, there is an official Prometheus client in Python and the {openmetrics} package in R makes it easy to register metrics from a Plumber API or Shiny app.\nThere’s a great Get Started with Grafana and Prometheus doc on the Grafana Labs website if you want to actually try it out."
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     "text": "Strictly speaking, this is not true. There are a lot of different ways to kick off CI/CD jobs. But the right way to do it is to base it on git operations.↩︎\nA completed merge counts as a push.↩︎"
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+    "text": "6.1 Container lifecycle\nDocker is primarily concerned with the creation, movement, and running of containers. A container is a software entity that packages code and its dependencies down to the operating system. Containers make it possible to have completely different environments coexisting side by side on one physical machine.\n\n\n\n\n\n\nNote\n\n\n\nContainers aren’t the only way to run multiple virtual environments side-by-side – they’re just the most popular.\nDocker Containers also aren’t the only type of container, though they’re often treated that way. You may run across other kinds, like Apptainer (formerly Singularity), which is often used in high performance computing contexts.\n\n\nA Docker Image is an immutable snapshot of a container. When you want to run a container, you pull the image and run it as an instance, which is what you’ll actually interact with.\nImages are most often stored in registries, which are similar to git repositories. The most common registry is Docker Hub, which allows public hosting and private hosting of images in free and paid tiers. Docker Hub includes official images for operating systems and programming languages, as well as many, many community-contributed containers. Some organizations run their own private registries, usually using registry as a service offerings from cloud providers.2\nImages are built from Dockerfiles – the code that defines the image. Dockerfiles are usually stored in a git repository. It’s common to build images in a CI/CD pipeline so changes to the Dockerfile are immediately built and pushed to the registry.\nAll instances run on an underlying machine, called a host. A primary feature – also a liability – of using containers is that they are completely ephemeral. Unless configured otherwise, anything inside an instance when it shuts down vanishes without a trace.\nYou can control Docker Containers from the Docker Desktop app. If you’re going to be using Docker on a server, you’ll mostly be interacting via the command line interface (CLI). All Docker CLI commands are formatted as docker &lt;command&gt;.\nThe graphic below shows the different states for a container and the CLI commands to move from one to another.\n\n\n\n\n\n\n\nNote\n\n\n\nI’ve included docker pull on the graphic for completeness, but you’ll almost never run it. docker run auto-pulls the container(s) it needs.\n\n\nThere’s a cheatsheet for Docker CLI commands at the end of this chapter.\n\n6.1.1 Image Names\nIn order to build, push, pull, or run an image, you’ll need to know which image you’re talking about. Every image has a name that consists of an id and a tag.\n\n\n\n\n\n\nNote\n\n\n\nIf you’re using Docker Hub, container ids take the form &lt;user&gt;/&lt;container name&gt;, so I might have the container alexkgold/my-container. This should look familiar to GitHub users.\nOther registries may enforce similar conventions for ids, or they may allow ids in any format they want.\n\n\nTags are used to specify versions of variants of containers and come after the id and :. For example, the official Python docker image has versions for each version of Python like python:3 as well as variants for different operating systems and a slim version that saves space by excluding recommended packages.\nSome tags, usually used for versions, are immutable. For example, the rocker/r-ver container is a container that is built on Ubuntu and has a version of R built in. There’s a rocker/r-ver:4.3.1, which is a container with R 4.3.1.\nOther tags are relative to the point in time. If you don’t see a tag on a container name, it’s using the default latest. Other common relative tags refer to the current development state of the software inside like devel, release, or stable."
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+    "section": "6.2 Running Containers",
+    "text": "6.2 Running Containers\nThe docker run command runs container images as an instance. You can run docker run &lt;image name&gt; to get a running container. However, most things you want to do with your instance require several command line flags.\nThere are a few flags that are useful to manage how your containers run and get cleaned up.\nThe -name &lt;name&gt; flag names an instance. It’s not required, but can be useful to give the instance a name you can remember or use in code. If you don’t provide a name, each instance gets a random alphanumeric id on start.\nThe -rm flag automatically removes the container after its done. If you don’t use the -rm flag, the container will stick around until you clean it up manually with docker rm. The -rm flag can be useful when you’re iterating quickly – especially because you can’t re-use names until you remove the container.\nThe -d flag will run your container in detached mode. This is useful when you want your container to run in the background and not block your terminal session. It’s useful when running containers in production, but you probably don’t want to use it when you’re trying things out and want to see logs streaming out as the container runs.\n\n6.2.1 Getting information in and out\nWhen a container runs, it is isolated from the host. This is a great feature – it means programs running inside the container can address the container’s filesystem and networking without worrying about the host outside. But it also means that using resources on the host requires explicit declarations as part of the docker run command.\nIn order to get data in or out of a container, you need to mount a shared volume (directory) between the container and host with the -v flag. You specify a host directory and a container directory separated by :. Anything in the volume will be available to both the host and the container at the file paths specified.\nFor example, maybe you’ve got a container that runs a job against data it expects in the /data directory. On your host machine, this data lives at /home/alex/data. You could make this happen with\n{bash filename=Terminal} docker run -v /home/alex/data:/data\nHere’s a diagram of how this works.\n\nSimilarly, if you have a service running in a container on a particular port, you’ll need to map the container port to a host port with the -p flag.\n\n\n6.2.2 Other runtime commands\nIf you want to see what containers you’ve got, docker ps lists them. This is especially useful to get instance ids if you didn’t bother with names.\nTo stop a running container docker stop does so nicely and docker kill terminates a container immediately.\nYou can view the logs from a container with docker logs.\nLastly, if you need to run a command inside a running instance, you can use docker exec. This is most commonly used to access the command line inside the container as if SSH-ing to a server with docker exec -it &lt;container&gt; /bin/bash.\nWhile it’s normal to SSH into a server to poke around, it’s somewhat of an anti-pattern to do the same in a container. In general you should prefer to review logs and adjust Dockerfiles and run commands rather than exec in."
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+    "text": "6.3 Building Images from Dockerfiles\nA Dockerfile is a set of instructions that you use to build a Docker Image. If you know how to accomplish something from the command line, you shouldn’t have too much trouble building a Dockerfile to do the same.\nOne thing to consider when creating Dockerfiles is that the resulting image is immutable. That means anything you build into the image is forever frozen in time. So you’ll definitely want to set up the versions of R and Python and install system requirements. Depending on the purpose of your container, you may want to copy in code, data, and/or R and Python packages, or you may want to mount those in a volume at runtime.\nThere are many Dockerfile commands. You can review them all in the Dockerfile documentation, but here are the handful that are enough to build most images.\n\nFROM – specify the base image. Usually the first line of the Dockerfile.\nRUN – run any command as if you were sitting at the command line inside the container.\nCOPY – copy a file from the host filesystem into the container.\nCMD - Specify what command to run on the container’s shell when it runs, usually the last line of the Dockerfile.3\n\nEvery Dockerfile command defines a new layer.\nA great feature of Docker is that it only rebuilds the layers it needs to when you make changes. For example, take the following Dockerfile:\nFROM ubuntu:latest\n\nCOPY my-data.csv /data/data.csv\n\nRUN [\"head\", \"/data/data.csv\"]\nLet’s say I wanted to change the head command to tail. Rebuilding this container would be nearly instantaneous because the container would only start rebuilding after the COPY command.\nOnce you’ve created your Dockerfile, you build it into an image using docker build -t &lt;image name&gt; &lt;build directory&gt;. If you don’t provide a tag, the default tag is latest.\nYou can then push the image to DockerHub or another registry using docker push &lt;image name&gt;."
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+    "text": "6.4 Comprehension Questions\n\nDraw a mental map of the relationship between the following: Dockerfile, Docker Image, Docker Registry, Docker Container\nWhen would you want to use each of the following flags for docker run? When wouldn’t you?\n\n-p, --name, -d, --rm, -v\n\nWhat are the most important Dockerfile commands?"
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+    "title": "6  Demystifying Docker",
+    "section": "6.5 Lab: Putting an API in a Container",
+    "text": "6.5 Lab: Putting an API in a Container\nPutting an API into a container is popular way to host them. In this lab, we’re going to put the Penguin Model Prediction API from Chapter 2 into a container.\nIf you’ve never used Docker before, start by installing Docker Desktop on your computer.\nYou should feel free to write your own Dockerfile to put the API in a container. If you want to make it easy, the {vetiver} package, which you’ll remember auto-generated the API for us, can also auto-generate a Dockerfile. Look at the package documentation for details.\nI’m using this code to generate my Dockerfile\nfrom pins import board_folder\nfrom vetiver import prepare_docker\n\nboard = board_folder(\"/data/model\", allow_pickle_read=True)\nprepare_docker(board, \"penguin_model\", \"docker\")\nOnce you’ve generated your Dockerfile, take a look at it. Here’s the one for my model:\n\n\nDockerfile\n\n# # Generated by the vetiver package; edit with care\n# start with python base image\nFROM python:3.9\n\n# create directory in container for vetiver files\nWORKDIR /vetiver\n\n# copy  and install requirements\nCOPY vetiver_requirements.txt /vetiver/requirements.txt\n\n#\nRUN pip install --no-cache-dir --upgrade -r /vetiver/requirements.txt\n\n# copy app file\nCOPY app.py /vetiver/app/app.py\n\n# expose port\nEXPOSE 8080\n\n# run vetiver API\nCMD [\"uvicorn\", \"app.app:api\", \"--host\", \"0.0.0.0\", \"--port\", \"8080\"]\n\nThis auto-generated Dockerfile is very nicely commented, so its easy to follow.\n\n\n\n\n\n\nNote\n\n\n\nThis container follows the best practices from Chapter 2. We’d expect the model to be updated much more frequently than the container itself, so the model isn’t built into the container. Instead, the container knows how to fetch the model using the {pins} package.\n\n\nNow build the container using docker build -t penguin-model ..\nYou can run the container using\ndocker run --rm -d \\\n  -p 8080:8080 \\\n  --name penguin-model \\\n  penguin-model\nIf you go to http://localhost:8080 you’ll find that…it doesn’t work? Why? If you run the container attached (remove the -d from the run command) you’ll get some feedback that might be helpful.\nIn line 15 of the Dockerfile, we copied the app.py in to the container. Let’s take a look at that file to see if we can find any hints.\n\n\napp.py\n\nfrom vetiver import VetiverModel\nimport vetiver\nimport pins\n\n\nb = pins.board_folder('./model', allow_pickle_read=True)\nv = VetiverModel.from_pin(b, 'penguin_model', version = '20230422T102952Z-cb1f9')\n\nvetiver_api = vetiver.VetiverAPI(v)\napi = vetiver_api.app\n\nLook at that (very long) line 6. The API is connecting to a local directory to pull the model. Is your spidey sense tingling? Something about container filesystem vs host filesystem?\nThat’s right – we put our model at /data/model on our host machine. But the API inside the container is looking for /data/model inside the container, which doesn’t exist!\nThis is a case where we need to mount a volume into the container like so\ndocker run --rm -d \\\n  -p 8080:8080 \\\n  --name penguin-model \\\n  -v /data/model:/data/model \\\n  penguin-model-local\nAnd NOW you should be able to get your model up in no time.\n\n6.5.1 Lab Extension\nRight now, logs from the API just stay inside the container instance. But that means that the logs go away when the container does. That’s obviously bad if the container dies because something goes wrong.\nHow might you make sure that the container’s logs get written somewhere more permanent?"
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+    "text": "This was truer before the introduction of M-series chips for Macs. Chip architecture differences fall below the level that a container captures, and many popular containers wouldn’t run on new Macs. These issues are getting better over time and will probably fully disappear relatively soon.↩︎\nThe big three container registries are AWS Elastic Container Registry (ECR), Azure Container Registry, and Google Container Registry.↩︎\nYou may also see ENTRYPOINT, which sets the command CMD runs against. Usually the default /bin/sh -c to run CMD in the shell will be the right choice.↩︎"
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+    "text": "Getting and running a server\nThe most common way to get a server for data science is to rent one from a cloud provider. In order to do data science tasks, many people combine their server with other services from the cloud provider. That’s why Chapter 7 is an introduction to what the cloud is and how you might want to use it for data science purposes.\nUnlike your phone or personal computer, you’ll never touch this cloud server you’ve rented. Instead, you’ll administer the server via a virtual interface from your computer. Moreover, servers generally don’t even have the kind of point-and-click interface you’re used to on your personal devices.\nInstead, you’ll access and manage your server from the text-only command line.That’s why Chapter 8 is all about how to set up the command line on your local machine to make it convenient and ergonomic and how to connect to your server for administration purposes using a technology called SSH.\nUnlike your Apple, Windows, or Android operating systems you’re used to on your personal devices, most servers run the Linux operating system. Chapter 9 will teach you a little about what Linux is and will introduce you to the basics of Linux administration including how to think about files and users on a multi-tenant server.\nBut you’re not interested in just running a Linux server. You want to use it to accomplish data science tasks. In particular, you’ll want to install data science tools like R, Python, RStudio, JupyterHub, and more. So you’ll need to learn how to install, run, and configure applications on your server. That’s why Chapter 10 is about application administration.\nWhen your phone or computer gets slow or you run out of storage, it’s probably time for a new one. But a server is a working machine that can be scaled up or down to accommodate more people or heavier workloads over time. That means that you may have to manage the server’s resources much more actively than your personal devices. That’s why Chapter 11 is all about managing and scaling server resources."
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+    "text": "Making it (safely) accessible\nUnless you’re doing something really silly, your personal devices aren’t accessible to anyone who isn’t physically touching the device. In contrast, most servers are only useful because they’re addressable on a computer network, perhaps even the open internet.\nMaking a server accessible to people over the internet makes it useful, but it also introduces risk. Many dastardly plans for your personal devices are thwarted because a villain would have to physically steal it to get access. For a server, allowing digital access means there are many more potential threats looking to steal data or hijack your computational resources for nefarious ends. You’ve got to be careful about how you’re providing access to the machine.\nMoreover, risk aside, computer networking is a complicated topic, and making it work right can be somewhat difficult. Following random tutorials on the internet is a great way to eventually get your server working, but have no idea what happened or why it suddenly works.\nThe good news is that it’s not magic. Chapter 12 is all about how computers find each other across a network. Once you understand the basic structure and operations of a computer network, making only the things you intend to be public on your server will be much easier.\nAside from a basic introduction to computer networking, there are two other things you’ll want to configure to make your server safe and accessible. The first is to host your server at a human-friendly URL, which you’ll learn how to configure in Chapter 13. The second is to add SSL/TLS to your server to secure the traffic going to and from your server. You’ll learn how to do that in Chapter 14.\nOnce you’ve finished these chapters, you’ll have a basic understanding of all the main topics in IT/Admin that are likely to come up as you try to administer a simple data science workbench or project hosting platform."
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-    "text": "Labs in this Section\nThere’s only one lab in this section in Chapter 9 on using Docker. Docker is a hot enough topic that I felt it was worth spending some more time on. In this chapter, you’ll take the Palmer Penguins mass prediction API and app and learn how to Docker-ize them.\nFor more details on what you’ll do in each chapter, see Appendix B."
+    "text": "Labs in this Section\nIn the first section of the book, the labs involved creating a DevOps-friendly data science project. In this section, the labs will revolve around actually putting that project into production.\nYou’ll start by standing up an AWS EC2 instance, configuring your local command line, and connecting to the server via SSH. Once you’ve done that, you’ll learn how to create users on the server and access the server as a particular user.\nAt that point, you’ll be ready to transition into data science work. You’ll add R, Python, RStudio Server, and JupyterHub to your server and get them configured for work. Additionally, you’ll deploy the Shiny App and API you created in the book’s first section onto the server.\nOnce the server itself is configured, you’ll need to configure the server’s networking to make it accessible and secure. You’ll learn how to open the proper ports and configure a proxy to access multiple services on the same server, and you’ll learn to configure DNS records so your server is available at a real URL and SSL so it can all be done securely.\nBy the time you’ve finished the labs in this section, you’ll be able to use your EC2 instance as a data science workbench and add your penguin mass prediction Shiny App to the Quarto website you created in the book’s first section.\nFor more details on what you’ll do in each chapter, see Appendix B."
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+    "text": "7.1 The cloud is rental servers\nAt one time, the only way to get servers was to buy physical machines and hire someone to install and maintain them. This is called running the servers on-prem (short for premises). There are some organizations, especially those with highly sensitive data, that still run on-prem servers.\nThe problem is that on-prem servers require a large up-front investment in server hardware and professional capacity. If your company has a use case that only requires a single server or one with uncertain payoff, it probably isn’t worth it to hire someone and buy a bunch of hardware.\nAround the year 2000, Amazon took all the server farms across the company and centralized them so teams would use this central server capacity instead of running their own. Over the next few years, Amazon execs (correctly) realized that other companies and organizations would value this ability to rent server capacity. They launched this “rent a server” business as AWS in 2006.\nThese days, the cloud platform business is enormous – collectively nearly a quarter of a trillion dollars. It’s also highly profitable. AWS was only 13% of Amazon’s revenue in 2021, but a whopping 74% of the company’s profits for that year.2\nAWS is still the biggest cloud platform by a considerable margin, but it’s far from alone. Approximately 2/3 of the market consists of the big three – AWS, Microsoft Azure, and Google Cloud Platform (GCP) with the final third made up of numerous smaller companies.3"
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-    "text": "6.1 Getting the command line you want\nThe reason customizing your command line is somewhat confusing is that the command line you interact with is actually two or three programs that sit on top of each other. You can mix-and-match options for each of them and configure them in a variety of ways.\n\n\n\n\n\n\nNotes on operating systems\n\n\n\nI’ve been using the command line in MacOS for many years, so I have strong opinions to share in this chapter.\nI haven’t used a Windows machine in many years. I’ve collected some recommendations here, but I can’t personally vouch for them the same way.\nI don’t include recommendations for Linux because Linux desktop users already have strong opinions on these topics and are probably already composing screeds that my opinions are wrong."
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+    "text": "7.2 Real (and fake) cloud benefits\nThe cloud arrived with an avalanche of marketing fluff. Over a decade after the cloud went mainstream, it’s clear that some of the purported benefits are real and some are less so. You can be a much more intelligent cloud consumer if you understand which is which.\nThe most important cloud benefit is flexibility. Moving to the cloud allows you to get a new server or re-scale an existing one in minutes, and you only pay for what you use, often on an hourly basis.4 The risk of incorrectly guessing how much capacity you’ll need is drastically reduced, making it way less risky to get started on a server.\nThe other big benefit of the cloud is that it allows IT/Admin teams to narrow their scope and focus. For most organizations, managing physical servers isn’t part of their core competency and outsourcing that work to a cloud provider is a great choice.\n\n\n\n\n\n\nNote\n\n\n\nOne other dynamic is the incentives of individual IT/Admins. As technical professionals, IT/Admins want evidence on their resumes that they have experience with the latest and greatest technologies, which are generally cloud services these days rather than managing physical hardware.\n\n\nAlong with these very real benefits, the cloud was supposed to enable big time savings relative to on-prem operations. For the most part, that hasn’t materialized.\nThe theory was that the cloud would enable organiations to scale their capacity to match need at any given moment. So even if the hourly price was higher, the organization would turn servers off at night or during slow periods and save money.\nIt turns out that dynamic server scaling loads takes a fair amount of engineering effort and only the most sophisticated IT/Admin organizations have implemented effective autoscaling. And even for the organizations that do autoscale, cloud providers are very good at pricing their products to capture a lot of those savings.\nSome large organizations with stable workloads have actually started doing cloud repatriations – bringing workloads back on-prem for significant cost savings. An a16z study found that for certain organizations, the total cost of repatriated workloads, including staffing, could be 1/3 to 1/2 the cost of using a cloud provider.5\nThat said, even if the cash savings aren’t meaningful, the cloud is a key enabler for many businesses. The ability to start small, focus on what matters, and scale up quickly is more than worth it.\nYou may be interested in buying a physical server or re-purposing an old computer just for fun. You’re in good company; I’ve run Ubuntu Server on more than one old laptop. But if you’re trying to spend more time getting important things done and less time playing, getting a server from the cloud is the way to go."
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-    "text": "6.2 The terminal\nThe terminal is the GUI where you’ll type in commands. The terminal program you use will dictate the colors and themes available for the window, how tabs and panes work, and the keyboard shortcuts you’ll use to manage them.\nSome programs you might use, like RStudio or VSCode have terminals built into them. If you do basically all your terminal work from one of these environments, you may not need another. But it can often be nice to have a standalone terminal program you like.\n\nMacOSWindows\n\n\nI’d recommend against using the built-in terminal app (called Terminal). It’s fine, but there are better options.\nMy personal favorite is the free iTerm2, which adds a bunch of niceties like better theming and multiple tabs.\n\n\nThe built-in terminal is the favorite of many users. There are a variety of alternatives you can try, but feel free to stick with the default."
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+    "text": "7.3 Understanding cloud services\nIn the beginning, cloud providers did just one thing – rent you a server. But they didn’t stop there. Instead, they started building layers and layers of services that abstract away more IT/Admin tasks.\nAt the end of the day, all cloud services boil down to “rent me an \\(\\text{X}\\)”. As a data scientist, you should start by decoding “What is the \\(\\text{X}\\)?”\nUnfortunately, cloud marketing materials aren’t usually oriented to the data scientist trying to decide whether to use the services, instead they’re oriented at your boss and your boss’s boss, who wants to hear about benefits of using the service. That can make it difficult to decode what \\(\\text{X}\\) is.\nIt’s helpful to keep in mind that, at the end of the day, every service that isn’t directly renting a server is just renting server that already has certain software pre-installed and configured.6\n\n\n\n\n\n\nLess of serverless computing\n\n\n\nYou might hear people talking about going serverless. There is no such thing as serverless computing. Serverless is a marketing term meant to convey that you don’t have to manage the servers. The cloud provider manages them for you, but they’re still there.\n\n\nCloud services are sometimes grouped into three layers to indicate whether you’re renting a basic computing service or something more complete.\nAn analogy to a more familiar layered object may serve to make things clear. Let’s say you’re throwing a birthday party for a friend. You’re planning to bring a chocolate layer cake with vanilla frosting topped with lavender rosettes and “Happy Birthday!” in teal.7\n\n\n\n\n\n\nBig Three Service Naming\n\n\n\nIn this next section, I’ll mention services for common tasks from the big three. AWS tends use cutesy names that have a tangential relationship to the task at hand. Azure and GCP name their offerings more literally.\nThis makes AWS names a little harder to learn, but much easier to recall once you’ve learned them. A table of all the services mentioned in this chapter is in Appendix C.\n\n\n\n7.3.1 IaaS Offerings\nInfrastructure as a service (IaaS, pronounced eye-ahzz) is the basic rent a server premise from the earliest days of the cloud.\nFrom a data science perspective, a IaaS offering might look like what we’re doing in the lab in this book – acquiring a server, networking, and storage from the cloud provider and assembling it into a data science workbench. This is definitely the best way to learn how to administer a data science environment and it’s the cheapest option, but it’s also the most time-consuming.\nThis would be like choosing to go to the grocery store, buy all the ingredients, and bake and decorate your friend’s cake from scratch.\nAlong with a server, you’ll rent storage and networking to make everything work properly.\nSome common IaaS services you’re likely to use include:\n\nRenting a server from AWS with EC2 (Elastic Cloud Compute), from Azure with Azure VMs, and from GCP with Google Compute Engine Instances.\nUnlike your laptop, rented servers don’t include a hard drive, so you’ll have to attach storage with AWS’s EBS (Elastic Block Store), Azure Managed Disk, or Google Persistent Disk.\nCreating and managing the networking where your servers sit with AWS’s VPC (Virtual Private Cloud), Azure’sVirtual Network, and GCP’s Virtual Private Cloud.\nManaging DNS records via AWS’s Route 53, Azure DNS, and Google Cloud DNS. (More on what this means in Chapter 13.\n\nWhile IaaS means the IT/Admins don’t have to be responsible for physical management of servers, they’re responsible for everything else, including keeping the servers updated and secured. For that reason, many organizations are moving away from IaaS towards something more managed these days.\n\n\n7.3.2 PaaS Offerings\nIn a PaaS (Platform as a Service) solution, you hand off management of the servers, but manage the applications you need via an API specific to that service. From a data science perspective, a PaaS setup might look like hosting a JupyterHub, RStudio, or Posit implementation in EKS, or running an ML API in Lambda.\nIn the cake baking world, PaaS would be like buying a pre-made cake and some tins of frosting and doing only the writing and rosettes yourself.\nOne PaaS service that already came up in the book is blob (Binary Large Object) storage. Blob storage allows you to store individual objects somewhere and recall them to any other machine that has access to the blob store. The major blob stores are AWS’s S3 (Simple Storage Service), Azure Blob Storage, and Google Cloud Storage.\nYou’re also likely to make use of cloud-based database, data lake, and data warehouse offerings. There are numerous different offerings, and the ones that you use will depend a lot on your use case and your organization. The ones I’ve seen used most frequently are RDS or Redshift from AWS, Azure Database, and Google BigQuery. This category also includes a number of offerings from outside the big three, most notably Snowflake and Databricks.\nDepending on your organization, you may also use services that run APIs or applications from containers or machine images like AWS’s ECS (Elastic Container Service), Elastic Beanstalk, or Lambda, Azure’s Container Apps or Functions, or GCP’s App Engine or Cloud Functions.\nIncreasingly, organizations are turning to Kubernetes as a way to host services. (More on that in Chapter 18.) Most organizations who do so use a cloud provider’s Kubernetes cluster as a service: AWS’s EKS (Elastic Kubernetes Service) or Fargate, Azure’s AKS (Azure Kubernetes Service), or GCP’s GKE (Google Kubernetes Engine).\nMany organizations are moving to PaaS solutions for hosting applications for internal use. It takes away the hassle of managing and updating actual servers. On the flipside, these offerings are somewhat less flexible than just renting a server, and some applications don’t run well in these environments.\n\n\n7.3.3 SaaS Offerings\nSaaS (Software as a Service) is where you just rent the end-user software for usage, often on the basis of seats or usage. You’re already used to consumer SaaS software like Gmail, Slack, and Office365.\nThe cake equivalent of SaaS would be just going to a bakery and buying a cake for your friend.\nDepending on your organization, you might use a SaaS data science offering like AWS’s SageMaker, Azure’s Azure ML, or GCP’s Vertex AI or Cloud Workstations.\nThe great thing about SaaS offerings is that you get immediate access to the end-user application and it’s usually trivial (aside from cost) to add more users. IT/Admin configuration is generally limited to hooking up integrations, most often authentication and/or data sources.\nThe tradeoff for this ease is that they’re generally more expensive and you’re at the mercy of the provider for configuration and upgrades.\n\n\n7.3.4 Common Services\nIrrespective of the particular services you want to use, there are a few basic services you’ll almost certainly have to interact with.\nRegardless of what you’re trying to do, if you’re working in the cloud, you have to make sure that the right people have the right permissions. In order to manage these permissions, AWS has IAM (Identity and Access Management), GCP has Identity Access Management, and Azure has Microsoft Entra ID, which was called Azure Active Directory until the summer of 2023. Your organization might integrate these services with a SaaS identity management solution like Okta or OneLogin.\nAdditionally, some cloud services are geographically specific. Each of the cloud providers has split the world into a number of geographic areas, which they all call regions.\nSome services are region-specific and can only interact with other services in that region by default. If you’re doing things yourself, I recommend just choosing the region where you live and putting everything there. Costs and service availability does vary somewhat across region, but it shouldn’t be materially different for what you’re trying to do.\nRegions are subdivided into availability zones (AZs). AZs are subdivisions of regions that are designed to be independent. Some organizations want to run services that span multiple availability zones to provide protection against outages in any particular geography. If you’re running something sophisticated enough to need multi-AZ configuration, you should really be working with a professional IT/Admin."
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-    "text": "6.3 The shell\nThe shell is the program that takes the commands you’re typing and runs them. It’s what matches the words you type to actual commands or programs on your system. Depending on which shell you choose, you’ll get different options for plugins and themes.\nThe shell runs anywhere you’ve got a running operating system. So your computer has one shell, your server would have a different one. Even a Docker Container has a shell available. That means that if you do a lot of work on a server, you may need to configure your shell twice – once locally and once on the server.\n\nMacOSWindows\n\n\nThe default shell for MacOS (and Linux) is called bash. I’d advise you to switch it out for zsh, which is the most popular bash alternative.1\nRelative to bash, zsh has a few advantages out of the box, like better auto-completion. It also has a huge ecosystem of themes to enhance visual appeal and functionality, and plugins that let your command line do everything from displaying your git status to controlling your Spotify playlist.\nAll so-called bash alternatives are just bash with some extra bells and whistles, so they’re very similar. So if you log into a server that’s running bash rather than zsh, you might be annoyed that some of your shortcuts don’t work, but you won’t be lost.\nI’d recommend looking up instructions for how to install zsh using Homebrew, which you should also install if you haven’t already.\n\n\nWindows comes with two shells built in, the Command Shell (cmd) and the PowerShell.\nThe Command Shell is older and has been superseded by PowerShell. If you’re just getting started, you absolutely should just work with PowerShell. If you’ve been using Command Shell on a Windows machine for a long time, most Command Shell commands work in PowerShell, so it may be worth switching over."
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+    "text": "7.4 Comprehension Questions\n\nWhat are two reasons you should consider going to the cloud? What’s one reason you shouldn’t?\nWhat is the difference between PaaS, IaaS, and SaaS? What’s an example of each that you’re familiar with?\nWhat are the names for AWS’s services for: renting a server, file system storage, blob storage"
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-    "text": "6.4 Make it look and work great\nNow that you’ve got your shell and terminal installed, let’s get it customized just for you. It is possible to directly customize both zsh and PowerShell. In most cases, you’ll want to use a configuration manager to manage your themes and plugins.\n\nMacOSWindows\n\n\nPrezto is my favorite configuration and plugin manager for zsh. OhMyZsh is popular and also very good. Feel free to choose either – but you can only use one.\nOnce you’ve installed Prezto, you’ve got (at least) three different places you could configure your command line – iTerm2 preferences, .zshrc, and .zpreztorc. I’d recommend leaving .zshrc alone, customizing the look of the window and the tab behavior in the iTerm2 preferences, and customizing the text theme and plugins via prezto in the .zpreztorc file.\nI tend to be a pretty light on customizations, but I’d recommend looking into git plugins and some of the advanced auto-completion and command history search functionality.\n\n\nMany people like customizing PowerShell with Oh My Posh."
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+    "text": "7.5 Introduction to Labs\nWelcome to the lab!\nThe point of these exercises is to get you hands on with running servers and get you practicing the things you’re learning in the rest of the book.\nIf you walk through the labs sequentially, you’ll end up with a working data science workbench. It won’t suffice for any enterprise-level requirements, but it’ll be secure enough for a hobby project or even a small team.\nFor this lab, we’re going to use services from AWS, as they’re the biggest cloud provider and the one you’re most likely to run into in the real world. Because we’ll be mostly using IaaS services, there are very close analogs from Azure and GCP should you want to use one of them instead."
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-    "text": "6.5 Comprehension Questions\n\nDraw a mental map that includes the following: terminal, shell, theme manager, operating system, my laptop"
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+    "text": "7.6 Lab: Getting started with AWS\nIn this first lab, we’re going to get you up and running with an AWS account and show you how to manage, start, and stop EC2 instances in AWS.\nThe server we’ll stand up will be from AWS’s free tier – so there will be no cost involved as long as you haven’t used up all your AWS free tier credits before now.\n\n\n\n\n\n\nTip\n\n\n\nThroughout the labs, I’ll suggest you name things in certain ways. You can do what you want, but I’ll be consistent with those names, so you can copy commands straight from the book if you use the same name.\nIf you want to follow along in that way, start by creating a standalone directory for this lab, named do4ds-lab.\n\n\n\n7.6.1 Step 1: Login to the AWS Console\nWe’re going to start by logging into AWS at https://aws.amazon.com.\n\n\n\n\n\n\nNote\n\n\n\nAn AWS account is separate from an Amazon account for ordering stuff online and watching movies. You’ll have to create one if you’ve never used AWS before.\n\n\nOnce you’ve logged in, you’ll be confronted by the AWS console. There are a ton of things here. Poke around if you want and then continue when you’re ready.\n\n\n7.6.2 Step 2: Stand up an EC2 instance\nThere are five attributes about your EC2 instance you’ll want to configure. If it’s not mentioned here, just stick with the defaults for now.\nIn particular, just stick with the default Security Group. We’ll get into what they are and how to configure them later.\n\n7.6.2.1 Name + Tags\nInstance name and tags are human-readable labels so you can remember what this instance is. Neither name nor tag are required, but I’d recommend you name the server something like do4ds-lab in case you stand up others later.\nIf you’re doing this at work, there may be tagging policies so that the IT/Admin team can figure out who servers belong to later.\n\n\n7.6.2.2 Image\nAn image is a snapshot of a system and serves as the starting point for your server. AWS’s are called AMIs (Amazon Machine Images). They range from free images of bare operating system to paid images that come bundled with software you might want.\nChoose an AMI that’s just the newest LTS Ubuntu operating system. As of this writing, that’s 22.04. It should say free tier eligible.\n\n\n7.6.2.3 Instance Type\nThe instance type identifies the capability of the machine you’re renting. An instance type is made up of a family and a size. The family is the category of server and is denoted by letters and numbers, so there are T2s and T3s, C4s, R5s, and many more.\nWithin each family, there are different sizes. Possible sizes vary by the family, but generally range from nano to multiples of xlarge like 24.xlarge.\nFor now, I’d recommend you get the largest server that is free tier eligible. As of this writing, that’s a t2.micro with 1 CPU and 1 Gb of memory.\n\n\n\n\n\n\nServer sizing for the lab\n\n\n\nA t2.micro with 1 CPU and 1 Gb of memory is a very small server. For example, your laptop probably has at least 8 CPUs and 16 Gb of memory.\nA t2.micro should be sufficient for finishing the lab, but you’ll need a substantially larger server to do any real data science work.\nLuckily, it’s easy to upgrade cloud server sizes later. More on how, as well as advice on sizing servers for real data science work in Chapter 11.\n\n\n\n\n7.6.2.4 Keypair\nThe keypair is the skeleton key to your server. We’ll get more into how to use and configure it in Chapter 8. For now, create a new keypair. I’d recommend naming it do4ds-lab-key. Download the .pem version and put it in your do4ds-lab directory.\n\n\n7.6.2.5 Storage\nBump up the storage to as much as you can get under the free tier, because why not? As of this writing, that’s 30 Gb.\n\n\n\n7.6.3 Step 3: Start the Server\nIf you followed these instructions, you should now be looking at a summary that lists the operating system, server type, firewall, and storage. Go ahead an launch your instance.\nIf you go back to the EC2 page and click on Instances you can see your instance as it comes up. When it’s up, it will transition to State: Running.\n\n\n7.6.4 Optional: Stop the Server\nWhenever you’re stopping for the day, you may want to suspend your server so you’re not using up your free tier hours or paying for it. You can suspend an instance in the state it’s in so it can be restarted later. Suspended instances aren’t always free, but they’re generally very cheap.\nWhenever you want to suspend your instance, go to the EC2 page for your server. Under the Instance State drop down in the upper right, choose Stop Instance.\nAfter a couple minutes the instance will stop. Before you come back to the next lab, you’ll need to start the instance back up so it’s ready to go.\nIf you want to completely delete the instance at any point, you can choose to Terminate Instance from that same Instance State dropdown."
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+    "text": "7.7 Lab: Put the penguins data and model in S3\nWhether or not you’re hosting your own server, most data scientists working at an organization that uses AWS will run into S3, AWS’s blob store.\nOne really common thing to store in S3 is an ML model. So we’re going to store the mass prediction model we created in Chapters Chapter 2 and Chapter 3 in an S3 bucket.\n\n7.7.1 Step 1: Create an S3 bucket\nTo start off with, you’ll have to create a bucket, most commonly from the AWS console. I’m naming mine do4ds-lab.\n\n\n7.7.2 Step 2: Push new models to S3\nLet’s change the code in our Quarto doc to push the model into S3 when the model rebuilds, instead of just saving it locally.\nThere are a variety of different ways to access an S3 bucket. The simplest way is by using the AWS CLI on the command line. There are also R and Python packages for interacting with S3 (and other AWS services). The most common are Python’s {boto3} package or R’s {paws} and {aws.s3}.\nRegardless of what tooling you’re using, you’ll generally configure your credentials in three environment variables – AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, and AWS_REGION. You can get the access key and secret access key from the AWS console and you should know the region.\nAs always, when you’re developing in Python or R, I’d recommend putting these into a .env or a config.yml file and loading them from there.\nSince we built the model using {vetiver}, it’s really easy to push the model to S3 just by changing the board type to board_s3 and making sure our credentials are defined in an environment variable.\nIt’ll look something like this.\n\n\nmodel.qmd\n\nfrom pins import board_s3\nfrom vetiver import vetiver_pin_write\n\nboard = board_s3(\"do4ds-lab\", allow_pickle_read=True)\nvetiver_pin_write(board, v)\n\nUnder the hood, {vetiver} is making use of standard R and Python tooling to access an S3 bucket.\nInstead of using credentials, you could configure an instance profile using IAM, so the entire EC2 instance has access to the S3 bucket without needing credentials. Configuring instance profiles is the kind of thing you should work with a real IT/Admin to do.\n\n\n7.7.3 Step 3: Pull the API model from S3\nYou’ll also have to configure the API to load the model from the S3 bucket. Luckily, this is very easy. Just update the script you used to build your Dockerfile so it pulls from the pin in the S3 bucket rather than the local folder.\nNow, the script to build the Dockerfile looks like this:\n---\ntitle: \"Prepare Dockerfile\"\nformat:\n  html:\n    code-fold: true\n---\n\n## Load Environment\n\n```{python}\nfrom dotenv import load_dotenv\n\nload_dotenv()\n\nfrom pins import board_s3\nfrom vetiver import vetiver_prepare_docker\n\nboard = board_s3(\"do4ds-lab\", allow_pickle_read=True)\nvetiver_prepare_docker(board, \"penguin_model\")\n```\n\n\n7.7.4 Step 4: Give GitHub Actions S3 credentials\nWe want our model building to correctly push to S3 even when it’s running in GitHub Actions, but GitHub doesn’t have our S3 credentials by default, so we’ll need to provide them.\nWe’re going to declare the variables we need in the Render and Publish step of the Action.\nOnce you’re done, that section of the publish.yml should look something like this.\n\n\n.github/workflows/publish.yml\n\non:\n  workflow_dispatch:\n  push:\n    branches: main\n\nname: Quarto Publish\n\njobs:\n  build-deploy:\n    runs-on: ubuntu-latest\n    permissions:\n      contents: write\n    steps:\n      - name: Check out repository\n        uses: actions/checkout@v2\n\n      - name: Set up Quarto\n        uses: quarto-dev/quarto-actions/setup@v2\n\n      - name: Install R\n        uses: r-lib/actions/setup-r@v2\n        with:\n          r-version: '4.2.0'\n          use-public-rspm: true\n\n      - name: Setup renv and install packages\n        uses: r-lib/actions/setup-renv@v2\n        with:\n          cache-version: 1\n        env:\n          RENV_CONFIG_REPOS_OVERRIDE: https://packagemanager.rstudio.com/all/latest\n\n      - name: Install Python and Dependencies\n        uses: actions/setup-python@v4\n        with:\n          python-version: '3.10'\n          cache: 'pip'\n      - run: pip install jupyter\n      - run: pip install -r requirements.txt\n\n      - name: Render and Publish\n        uses: quarto-dev/quarto-actions/publish@v2\n        with:\n          target: gh-pages\n        env:\n          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}\n          AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }}\n          AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }}\n          AWS_REGION: us-east-1\n\nNow, unlike the GITHUB_TOKEN secret, which GitHub Actions automatically provides to itself, we’ll have to provide these secrets to the GitHub interface.\n\n\n7.7.5 Lab Extensions\nYou might also want to put the actual data you’re using into S3. This can be a great way to separate the data from the project, as recommended in Chapter 2.\nPutting the data in S3 is such a common pattern that DuckDB allows you to directly interface with parquet files stored in S3."
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-    "text": "zsh is pronounced by just speaking the letters aloud, zee-ess-aitch. Some people might disagree and say it’s zeesh, but they’re not writing this book, are they?↩︎"
+    "text": "Yes, that is a Sound of Music reference.↩︎\nhttps://www.visualcapitalist.com/aws-powering-the-internet-and-amazons-profits/↩︎\nhttps://www.statista.com/chart/18819/worldwide-market-share-of-leading-cloud-infrastructure-service-providers/↩︎\nAlthough these days a huge amount of cloud spending is done via annual pre-commitments. The cloud providers offer big discounts for making an up-front commitment, which the organization then spends down over the course of the year.↩︎\nhttps://a16z.com/2021/05/27/cost-of-cloud-paradox-market-cap-cloud-lifecycle-scale-growth-repatriation-optimization/↩︎\nThere are also some wild services that do specific things, like let you rent you satellite ground station infrastructure or do Internet of Things (IoT) workloads. Those services are really cool, but so far outside the scope of this book that I’m fine with talking like they don’t exist.↩︎\nIf you’re planning my birthday party, this is the correct cake configuration.↩︎"
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-    "text": "7.1 Using bash\nThe philosophy behind bash and its derivatives says that you should be able to accomplish anything you want with small programs invoked via a bash command. Each command should do just one thing, and complicated things should be accomplished by composing commands – taking the output from one as the input to the next.\n\n\n\n\n\n\nNote\n\n\n\nI’m mostly targeting using Linux servers in this chapter, so you won’t see much about Windows PowerShell commands in this chapter. If you have a Windows machine and you want to use bash, you can with the increasingly powerful Windows Subsystem for Linux (WSL).\n\n\nCalling a command is as simple as typing the command on the command line and hitting enter.\nHelpfully, most bash commands are an abbreviation of the word for what the command does. Unhelpfully, the letters often seem somewhat random. For example, the command to list the contents of a directory is ls, which sorta makes sense. Over time the commands you use frequently will become second hand.\nBash commands can be modified with command arguments, flags, and flag arguments. Bash commands are always formatted as &lt;command&gt; &lt;flags + flag args&gt; &lt;command args&gt;. It’s nice that this structure is standard. The downside is that having the main argument come all the way at the end, after all the flags, can make it hard to mentally parse commands.\nCommand arguments provide details to the command. They come after the command with a space in between. For example, if I want to run ls on the directory /home/alex, I can run ls /home/alex on the command line.\nSome commands have default arguments. For example the default argument for the ls command is the current directory. So if I’m in /home/alex, I’d get the same thing from either ls or ls /home/alex.\nOptions or flags modify how the command operates and come between the command and arguments. Flags are denoted by having one or more dashes before them. For example, ls allows the -l flag, which displays the output as a list. So, ls -l /home/alex would get the files in /home/alex as a list.\nSome flags themselves have arguments. For example, the -D flag allows specifying a format for how the datetime is displayed from ls -l. So running ls -l -D %Y-%m-%dT%H:%M:%S /home/alex lists all the files in /home/alex with the date-time of the last update formatted in ISO-8601 format, which is always the correct format for dates.\nBecause there can be so many arguments and flags, bash commands can get long. It’s often nice to include one flag or argument per line to make it more readable. You can tell bash you want it to keep reading after a line break by ending the line with a space and a \\.\nFor example, here’s that long ls command more nicely formatted:\n\n\nTerminal\n\n&gt; ls -l \\\n  -D %Y-%m-%dT%H:%M:%S \\\n  /home/alex\n\nThere is also help available!\nAll of the flags and arguments for commands can be found in the program’s man page (short for manual). You can access the man page for any command with man &lt;command&gt;. You can scroll the man page with arrow keys and exit with q.\nIf you ever can’t figure out how to quit, ctrl + c will quit from most command line situations.\nFor the most part, you’ll write commands directly on the command line. It’s also possible to write and run bash scripts, which usually end in .sh. The advantage of writing bash scripts is that they can run basically anywhere. The disadvantage is that the ergonomics of scripting bash are terrible, but sometimes it’s worth it."
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+    "text": "8.1 Getting the command line you want\nAs you get started on the command line, you’ll soon realize that some customization is in order. Maybe the colors aren’t quite right, or you want shortcuts for commands you type a lot, or you want more information in the default display.\nSome people might argue that customizing your command line isn’t the best use of your time and energy. Those people are no fun. Having a command line that behaves exactly as you like will speed up your work and make you feel like a hacker.\nBut as you get started, you’ll soon find yourself neck deep in Stack Overflow posts on how to customize your .bashrc. Or wait, is it the .zshrc? Or…\nThe reason customizing your command line is somewhat confusing is that the command line you interact with is actually two or three programs that sit on top of each other. You can mix-and-match options for each of them and configure them in a variety of ways.\n\n\n\n\n\n\nNotes on operating systems\n\n\n\nI’ve been using the command line in MacOS for many years, so I have strong opinions to share in this chapter.\nI haven’t used a Windows machine in many years. I’ve collected some recommendations, but I can’t personally vouch for them the same way.\nI don’t include Linux recommendations because people who use Linux on their desktop have already gone deep down the customization rabbit hole and don’t need my help wasting their time."
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-    "text": "7.2 File paths\nYou’re probably used to clicking around your computer’s filesystem to find files and folders. On the command line, you have to traverse the filesystem via written commands, so getting comfortable reading and writing file paths is important.\n\n\n\n\n\n\nNote\n\n\n\nSince this chapter is just on tooling, I’m skipping a lot of background about the filesystem and how it’s structured.\nYou’ll find that material in Chapter 11 on Linux Administration.\n\n\nWhenever you’re on the command line, you are at a particular place in the filesystem called the working directory. File paths can be absolute so they operate the same irrespective of the current working directory. An absolute file path is easy to recognize because it starts with /.\nYou can also use a relative file path, which starts at the current working directory, .\nDepending on what you’re doing, absolute or relative paths might make more sense. Absolute file paths are useful when you want to access the same resource regardless of where a command is run, and relative file paths make more sense when you want the command to be contextual to the working directory.\nThe working directory’s parent is at ... So, for example, you could see everything in the parent directory of your current working directory with ls .. or its parent with ls ../... The users’s home directory is always easily accessible at ~.\nYou can get the full path to your working directory with the pwd command, which is an abbreviation for print working directory.\nAlong with being able to inspect directories, it’s useful to be able to change your working directory with the cd command, short for change directory. You can use either absolute or relative file paths with cd. So if you were in /home/alex and wanted to navigate to /home, either cd .. or cd /home would work.\nSome files or directories are hidden so they don’t appear in a normal ls. You know a file or directory is hidden because its name starts with .. Hidden files are usually configuration files that you aren’t manipulating in normal usage. These aren’t secret or protected in any way, they’re just skipped by ls for convenience.\nYou’ve already seen a couple in this book – your GitHub Action was configured in the .github directory and your Prezto configuration was done in the .zpreztorc file. You might also be familiar with .gitignore, .Rprofile, and .Renviron. If you want to display hidden files in a directory, you can use the -a flag (for all) with ls."
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+    "text": "8.2 The terminal\nThe terminal is the GUI where you’ll type in commands. The terminal program you use will dictate the colors and themes available for the window, how tabs and panes work, and the keyboard shortcuts you’ll use to manage them.\nSome programs you might use, like RStudio or VSCode have terminals built into them. If you do basically all your terminal work from one of these environments, you may not need another. But it can be nice to have a standalone terminal program you like.\n\nMacOSWindows\n\n\nI’d recommend against using the built-in terminal app (called Terminal). It’s fine, but there are better options.\nMy personal favorite is the free iTerm2, which adds a bunch of niceties like better theming and multiple tabs.\n\n\nThe built-in terminal is the favorite of many users. There are a variety of alternatives you can try, but feel free to stick with the default."
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-    "text": "7.3 Reading text files\nOn a server, a huge fraction of what you’ll be doing is reading configuration and log files from the server, so being comfortable with the commands to do so is essential.\nThere are a few different commands I frequently use for reading files:\n\ncat is the basic command to print a file, starting at the beginning.\nless prints a file, starting at the beginning, but only a few lines at a time.\nhead prints only the first few lines and exits. It is especially useful to peer at the beginning of a large file, like a csv file – so you can quickly preview the column heads and the first few values.\ntail prints a file going up from the end. This is especially useful for log files, as the newest logs are appended to the end of a file. This is such a common practice that “tailing a log file” is a common phrase.\n\nSometimes, you’ll want to use the -f flag (for follow) to tail a file with a live view as it updates.\n\n\nSometimes you want to search around inside a text file. You’re probably familiar with the power of regular expressions (regex) to search for specific character sequences in text strings. The Linux command grep is the main regex command.\nIn addition to searching in text files, grep is often useful in combination with other commands. For example, it’s often useful to put the output of ls into grep to search for a particular file in a big directory.\nThe Linux pipe operator, |, takes the output of the previous command and sends it into the next one. So if I was searching for a file whose name contained the word data, that might look something like ls ~/projects/my-project | grep data.\n\n\n\n\n\n\nCeci n’est pas une pipe?\n\n\n\nThe pipe should feel extremely familiar to R users.\nThe pipe from the {magrittr} package, %&gt;%, was introduced in 2013, and is a popular part of the {tidyverse}.1 The {magrittr} pipe was inspired by both the Unix (Linux) pipe and the pipe operator in the F# programming language.\nDue to its popularity, the pipe |&gt; was formally added to the base R language in R 4.1 in 2021."
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+    "text": "8.3 The shell\nThe shell is the program that takes the commands you’re typing and runs them. It’s what matches the words you type to actual commands or programs on your system. Depending on which shell you choose, you’ll get different options for plugins and themes.\nThe shell runs anywhere you’ve got a running operating system. So your computer has one shell and your server would have a different one. Even a Docker Container has a shell available. That means that if you do a lot of work on a server, you may need to configure your shell twice – once locally and once on the server.\n\nMacOSWindows\n\n\nThe default shell for MacOS (and Linux) is called bash. I’d advise you to switch it out for zsh, which is the most popular bash alternative.1 Bash alternatives are programs that extend bash with various bells and whistles.\nRelative to bash, zsh has a few advantages out of the box, like better auto-completion. It also has a huge ecosystem of themes to enhance visual appeal and functionality, and plugins that let your command line do everything from displaying your git status to controlling your Spotify playlist.\nI’d recommend looking up instructions for how to install zsh using Homebrew.\n\n\nWindows comes with two shells built in, the Command Shell (cmd) and the PowerShell.\nThe Command Shell is older and has been superseded by PowerShell. If you’re just getting started, you should just work with PowerShell. If you’ve been using Command Shell on a Windows machine for a long time, most Command Shell commands work in PowerShell, so it may be worth switching over."
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-    "text": "7.4 Manipulating files and directories\nYou’ll often need to manipulate files and directories. Here’s how.\nYou can copy a file or directory from one place to another using the cp command. cp leaves behind the old file or directory and adds the new one at the specified location. You can use the -r flag to recursively copy everything in a directory.\nYou can move a file with the mv command, which does not leave the old file behind.\nIf you want to remove a file entirely, you can use the rm command. There is also a version to remove a directory, rmdir.\n\n\n\n\n\n\nWarning\n\n\n\nBe very careful with the rm command.\nUnlike on your desktop there’s no recycle bin! Things that are deleted are instantly deleted forever.\n\n\nIf you want to make a directory, mkdir makes a directory. mkdir gets mad if it’s not creating the whole file path, so the -p flag can be handy to create only the parts of the path that don’t exist.\nSometimes it’s useful to operate on every file inside a directory. You can get every file that matches a pattern with the wildcard, *. You can also do partial matching with the wildcard to get all the files that match part of a pattern.\nFor example, let’s say I have a /data directory and I want to put a copy of only the .csv files inside into a new data-copy sub-directory. I could do the following:\n&gt; mkdir -p /data/data-copy\n&gt; cp /data/*.csv /data/data-copy"
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+    "text": "8.4 Configuration management\nNow that you’ve got your shell and terminal installed, you’ll want to customize. It is possible to directly customize both zsh and PowerShell. But the best way to configure them is to use a configuration manager for your themes and plugins.\n\nMacOSWindows\n\n\nPrezto is my favorite configuration and plugin manager for zsh. OhMyZsh is also popular and very good. Feel free to choose either, but you can only use one.\nOnce you’ve installed Prezto, you’ve got (at least) three different places you could configure your command line – the iTerm2 preferences, .zshrc, and .zpreztorc. I’d recommend leaving .zshrc alone, customizing the look of the window and the tab behavior in the iTerm2 preferences, and customizing the text theme and plugins via Prezto in the .zpreztorc file.\nI tend to be a pretty light on customization, but I’d recommend looking into git plugins and some of the advanced auto-completion and command history search functionality.\n\n\nMany people like customizing PowerShell with Oh My Posh."
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-    "text": "7.5 Moving things to and from the server\nIt’s very common to have a file on your server you want to move to your desktop or vice versa.\nIf you’re moving multiple files, it’s easier to combine them into a single object and move that.\nThe tar command turns a set of files or whole directory into a single archive file, usually with the file suffix .tar.gz. Creating an archive also does some compression. The amount depends on the content.\nIn my opinion, tar is a rare failure of bash to provide standalone commands for anything you need to do. tar is used to both create and unpack (extract) archive files. Telling it which one requires the use of several flags. You’ll basically never use tar without a bunch of flags and the incantation is hard to remember. I google it every time I use it. The flags you’ll use most often are in the cheatsheet below.\nOnce you’ve created an archive file, you can move it to or from a server with the scp command. scp – short for secure copy – is basically cp, but with an SSH connection in the middle.2\nSince scp establishes an SSH connection, you need to make the request to somewhere that is accepting SSH connections. Since your server is probably accepting SSH connections and your laptop probably (hopefully) is not. That means that whether you’re copying something to or from a server, you’ll run scp from a regular terminal on your laptop, not one that’s already SSH-ed into your server.\nRegular ssh options work with scp, like -i and -v."
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+    "text": "8.5 Text Editors\nIf you’re working on your command line a lot, you’ll probably be working inside text editors a fair bit. There are many, many options for text editors and people have strong preferences.\nMac OS’s default text editor is called TextEdit and it’s bad. Don’t use it. Windows users get Notepad, which is somewhat better than TextEdit, but still not the best option out there.\nIf you like, you can just edit text files inside your IDE of choice like VS Code or RStudio. Others may prefer a standalone text editor. The most popular these days are probably Sublime or Notepad++ (Windows Only).\nUnlike with the terminal, there’s no deep configuration here. Install one from the web, configure it as you like, and make sure it’s the default for opening .txt and other files you might want to edit in your system preferences."
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-    "text": "7.6 Writing text files\nThere will be many situations where writing into a text file will be handy. There are several ways to write into a text file without opening it to edit.\nYou may have some preexisting text you want to add to a file. You can do this with the &gt; command, which takes the output of a command on the left and writes it as a file. If the file you specify already exists, it will be overwritten. If you want to append the new text, rather than overwrite, &gt;&gt; appends to the end of the file.\nA common reason you might want to do this is to add something to the end of your .gitignore. For example, if you want to add your .Rprofile file to your .gitignore, you could do that with echo .Rprofile &gt;&gt; .gitignore. Note that echo is a command that just repeats the input as a character string. Otherwise .Rprofile would be treated as a command.\nThere are times when you want to make files or directories with nothing in them. The touch command makes a blank file at the specified file path. If you touch a preexisting file, it updates the time the file was last updated without actually making any changes.\n\n7.6.1 Text editors - vim and nano\nThere are two command line text editors you’ll probably encounter: nano and vi/vim.3 While they’re both powerful text editing tools, they can also be intimidating if you’ve never used them before.\nYou can open a file in either by typing nano &lt;filename&gt; or vi &lt;filename&gt;.\nAt this point many newbie command line users find themselves completely stuck, unable to do anything – even just exit and try again. But don’t worry, there’s a way out of this labyrinth!\nIn nano there will be some helpful-looking prompts at the bottom. You’ll see that once you’re ready to go, you can exit with ^x. But you’ll find yourself stymied when you try to exit with the caret character, ^, and an x.\nNever fear. On Windows, ^ is short for Ctrl and on Mac it’s for Command (⌘), so Ctrl + x or ⌘ + x will exit.\nWhere nano gives you helpful – if obscure – hints, a first experience in vim is the stuff of command line nightmares. Typed words don’t appear in your on the screen, but instead cause dizzying jumps around the page and words and lines of text disappear without a trace.\nThis is all because you always enter vim in the (poorly named) normal mode where you use the letter keys to navigate, type, and interact with vim itself. Normal mode exists because vim was created before keyboards uniformly had arrow keys. These days, vim still operates this way because people are used to it and because it minimizes how much your hands have to move on the keyboard.\nWhile I’ve never felt taxed from using the arrow keys, vim keybindings are worth spending some time learning. vim includes some powerful shortcuts for moving within and between lines and selecting and editing text. Most IDEs you might use, including RStudio, JupyterLab, and VSCode have vim modes. Learning some of the basics can make you way faster editing code files, plus you’ll feel really cool.\nHere I’m only going to teach you how to make changes, save, and exit without issue.\nWhen you’re in normal mode, pressing the i key activates insert mode, which will feel normal for those of us used to arrow keys. You can type and words will appear and you can navigate with the arrow keys.\nNow that you’ve figured out how to exit normal mode, you may wish never to return. But it’s the only way to save files and exit vim. You can do so with the escape key.\nIn order to do file operations, you type a colon, :, followed by the shortcut for what you want to do, and enter. The two most common commands you’ll use are save (write) with w and quit with q. You can combine these together, so you can save and quit in one command using :wq.\nSometimes you may want to exit without saving. If you’ve made changes and try to exit with :q, you’ll find yourself in an endless loop of warnings that your changes won’t be saved. You can tell vim you mean it with the exclamation mark, !, and exit using :q!."
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+    "text": "8.6 Secure server connections with SSH\nOne common IT/Admin task is remotely accessing a server from the command line on your machine. SSH – short for Secure (Socket) Shell – is a tool for making a secure connection to another computer over an unsecured network. It’s most often used to interact with a server’s command line from the command line of your computer.\nUsing SSH requires invoking the ssh command line interface from your computer (local host) with a username and the address of the remote host (server). For example, connecting to the server at server.example.com as the user alex\n\n\nTerminal\n\n&gt; ssh alex@server.example.com\n\nOnce you run this command, your terminal will open a session to the terminal of the server.\n\n8.6.1 Understanding SSH keys\nBefore any of this can work, you’ll have to configure your SSH keys, which come in a set called keypair. Each keypair consists of a public key and a private key. You’ll register your public key anywhere you’re trying to SSH to, like a server or git host, but your private key must be treated as a precious secret.\nWhen you use the ssh command, your local machine sends a request to open an SSH session to the remote and includes the private key with the request. The remote host verifies the private key with the public key and opens an encrypted connection.\n\nThis seems weird – how can you verify your secret identity with something that you can just spread around publicly? The answer is public key cryptography, which makes it easy to check whether a proffered private key is valid, but nearly impossible to fabricate a private key from a public key.\n\n\n\n\n\n\nNote\n\n\n\nI wish public and private keys were named differently. Calling the private key the key and the public key the lock makes the intent much clearer. But no one asked me.\n\n\nThe key to public key cryptography is mathematical operations that are easy in one direction but really hard to reverse. As a simple example, think of the number \\(91\\) and its prime factors. Do you know what the prime factors of \\(91\\) are offhand? I do not.\nIt’ll probably take you a few minutes to try a bunch, even if you use a calculator. But if I give you the numbers \\(7\\) and \\(13\\), it’s easy to verify that \\(7 * 13 = 91\\).\nIn this example, the number \\(91\\) would be the public key and the prime numbers \\(7\\) and \\(13\\) together would be the private key. This wouldn’t actually make for very good public key cryptography because it doesn’t take more than a few moments to figure out that \\(7\\) and \\(13\\) are prime factors of \\(91\\).\nIn real public key cryptography, the idea is similar, but the mathematical operations are more complex and the numbers much, much bigger. So much so that it’s basically impossible to break public SSH keys through guessing.\nBut that doesn’t make SSH foolproof. While it’s basically impossible to fabricate a private key, it’s totally possible to steal one. Your private key must be kept secret. The best practice is to never move it from the computer where it was created and to never share them.\nIn summary, do what you want with your public keys, but don’t share your private keys. Don’t share your private keys. Seriously, do not share your private keys."
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+    "text": "8.7 Practical SSH usage\nNow that you’ve got an understanding of how SSH works, the steps should be easy to remember.\n\nCreate an SSH keypair on any machine you’ll be SSH-ing from (local host).\nPut the public key anywhere you’ll be SSH-ing to (remote host).\nUse the ssh command to connect.\n\nIf you’re working on a server, you’ll probably create at least two keypairs. One on your personal computer to SSH to the server, and one on the server to access outside services that use SSH, like GitHub.\n\n8.7.1 Step 1: Create Keypair\nYou’ll create a keypair on any server you’re SSH-ing from.\nTo create an SSH keypair, you should just follow a tutorial online. The keypair will have two parts. The one that ends in .pub is – you guessed it – the public key.\nIn most cases, you’ll only create one private key on each machine. If you follow standard instructions for creating a key, it will use the default name, probably id_ed25519.2 Sticking with the default name is great because the ssh command will automatically use them. If you don’t use the default name, you’ll have to specify.\n\n\n\n\n\n\nNote\n\n\n\nRemember, you should never move your private key. If you think the answer to a problem you’re having is to move your private key, think again.\nInstead of moving your private key, create a new private key on the machine where you need to use SSH and register a second public key on the remote.\n\n\nSome organizations require that you have a unique key for each service you’re using to make it easier to swap keys in the event of a breach. If so, you won’t be able to use the default key names.\n\n\n8.7.2 Step 2: Register the public keys\nTo register a public key to SSH into a server, you’ll add the public key to the end of the user’s .ssh/authorized_keys file in their home directory. You’ll have to make sure the permissions on the authorized_keys file are correct. More on that in Chapter 9.\nIf you’re registering with a service, like GitHub.com, there’s probably a text box in the GUI to add an SSH key. Google for instructions on how to do it.\n\n\n8.7.3 Step 3: Use SSH\nTo use SSH, you type ssh &lt;user&gt;@&lt;host&gt;. There are also other commands that can use SSH under the hood, like git or scp.\n\n\n\n\n\n\nFor Windows users\n\n\n\nFor a long time, Windows didn’t support SSH out of the box, so SSH-ing from Windows required a separate utility called PuTTY. More recent versions of Windows support using SSH directly in PowerShell or in Windows Subsystem for Linux (WSL). If SSH isn’t enabled on your machine, Google for instructions.\n\n\nIf you have multiple SSH keys or didn’t use the default flag, you can specify a particular key with the -i flag.\nIf you’re using SSH a lot, I’d recommend setting up an SSH config file. An SSH config file allows you to create aliases that are shortcuts to SSH commands including users, hosts, and other details. So if you had a long SSH command like ssh -i my-ssh-key alex@server.example.com, you could shorten it to ssh alex-server or whatever you want.\nOne annoyance about SSH is that they block the terminal they’re using and will break when your computer goes to sleep. Many people also like using the tmux command line utility with SSH to help solve these issues.\ntmux is a terminal multiplexer, which allows you to manipulate terminal sessions from the command line, including putting sessions into the background and making sessions durable through sleeps and other operations. To be honest, I’m mentioning tmux because lots of people love it, but I’ve found the learning curve too steep for it to come into regular usage for me. Your mileage may vary.\nIf you ever run into trouble using SSH, it has one of my favorite debugging modes. Just add a -v to your command for verbose mode. If that’s not enough information, add another v for more verbosity, and if that’s not enough, just add another v for super verbose mode."
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-    "text": "7.8 Cheatsheet: Command Line\n\n7.8.1 General Command Line\n\n\n\n\n\n\n\nSymbol\nWhat it is\n\n\n\n\nman &lt;command&gt;\nOpen manual for command\n\n\nq\nQuit the current screen\n\n\n\\\nContinue bash command on new line\n\n\nctrl + c\nQuit current execution\n\n\n\n\n\n7.8.2 Linux Navigation\n\n\n\n\n\n\n\n\nCommand\nWhat it does/is\nNotes + Helpful options\n\n\n\n\n/\nSystem root or file path separator\n\n\n\n.\ncurrent working directory\n\n\n\n..\nParent of working directory\n\n\n\n~\nHome directory of the current user\n\n\n\nls &lt;dir&gt;\nList objects in a directory\n-l - format as list\n-a - all (include hidden files that start with .)\n\n\npwd\nPrint working directory\n\n\n\ncd &lt;dir&gt;\nChange directory\nCan use relative or absolute paths\n\n\n\n\n\n7.8.3 Reading Text Files\n\n\n\n\n\n\n\n\nCommand\nWhat it does\nNotes + Helpful options\n\n\n\n\ncat &lt;file&gt;\nPrint a file from the top.\n\n\n\nless &lt;file&gt;\nPrint a file, but just a little.\nCan be very helpful to look at a few rows of csv.\nLazily reads lines, so can be much faster than cat for big files.\n\n\nhead &lt;file&gt;\nLook at the beginning of a file.\nDefaults to 10 lines, can specify a different number with -n &lt;n&gt;.\n\n\ntail &lt;file&gt;\nLook at the end of a file.\nUseful for logs where the newest part is last.\nThe -f flag is useful to follow for a live view.\n\n\ngr ep &lt;expression&gt;\nSearch a file using regex.\nWriting regex can be a pain. I suggest testing expressions on regex101.com.\nOften useful in combination with the pipe.\n\n\n|\nThe pipe\n\n\n\n\n\n\n7.8.4 Manipulating Files\n\n\n\n\n\n\n\n\nCommand\nWhat it does/is\nNotes + Helpful Options\n\n\n\n\nrm &lt;path&gt;\nRemove\n-r - recursively remove everything below a file path\n-f - force - don’t ask for each file\nBe very careful, it’s permanent\n\n\nc p &lt;from&gt; &lt;to&gt;\nCopy\n\n\n\nm v &lt;from&gt; &lt;to&gt;\nMove\n\n\n\n*\nWildcard\n\n\n\nmkdir/rmdir\nMake/remove directory\n-p - create any parts of path that don’t exist\n\n\n\n\n\n7.8.5 Move things to/from server\n\n\n\n\n\n\n\n\nCommand\nWhat it does\nNotes + Helpful options\n\n\n\n\ntar\nCreate/extract archive file\nAlmost always used with flags.\nCreate is usually\ntar -czf &lt; archive name&gt; &lt;file(s)&gt;\nExtract is usually\ntar -xfv &lt;archive name&gt;\n\n\nscp\nSecure copy via ssh\nRun on laptop to server\nCan use most ssh flags (like -i and -v)\n\n\n\n\n\n7.8.6 Write files from the command line\n\n\n\n\n\n\n\n\nCommand\nWhat it does\nNotes\n\n\n\n\ntouch\nCreates file if doesn’t already exist.\nUpdates last updated to current time if it does exist.\n\n\n&gt;\nOverwrite file contents\nCreates a new file if it doesn’t exist\n\n\n&gt;&gt;\nConcatenate to end of file\nCreates a new file if it doesn’t exist\n\n\n\n\n\n7.8.7 Command Line Text Editors (Vim + Nano)\n\n\n\n\n\n\n\n\nCommand\nWhat it does\nNotes + Helpful options\n\n\n\n\n^\nPrefix for file command in nano editor.\nIts the ⌘ or Ctrl key, not the caret symbol.\n\n\ni\nEnter insert mode (able to type) in vim\n\n\n\nescape\nEnter normal mode (navigation) in vim.\n\n\n\n:w\nWrite the current file in vim (from normal mode)\nCan be combined to save and quit in one, :wq\n\n\n:q\nQuit vim (from normal mode)\n:q! quit without saving"
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+    "text": "8.8 Comprehension Questions\n\nDraw a mental map that includes the following: terminal, shell, theme manager, operating system, my laptop\nUnder what circumstances should you move or share your SSH private key?\nWhat is it about SSH public keys that makes them safe to share?"
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-    "text": "The title of this callout box is also the tagline for the {magrittr} package.↩︎\nIt’s worth noting that scp is now considered “insecure and outdated”. The ways it is insecure are rather obscure and not terribly relevant for most people. But if you’re moving a lot of data, you may want something faster. If so, I’d recommend more modern options like sftp and rsync. I probably wouldn’t bother if you’re only occasionally scp-ing small files to or from your server.↩︎\nvi is the original fullscreen text editor for Linux. vim is its successor (vim stands for vi improved). I’m not going to worry about the distinction.↩︎"
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+    "text": "8.9 Lab: Login to the server\nIn the last chapter we got your server up and running. In this lab, we’ll use the provided .pem key to log in for the first time.\n\n8.9.1 Step 1: Grab the server address\nFrom the EC2 page, you can click on the instance ID in blue to see all the details of about your server.\nCopy the Public IPv4 DNS address, which starts with \\(\\text{ec2-}\\) and ends with \\(\\text{amazonaws.com}\\). That little icon on the left of the address copies it. You’ll need it throughout the labs. If you lose it, come back here to get it.\n\n\n\n\n\n\nSet a Server Address Variable\n\n\n\nIn the rest of the labs in this book, I’m going to write the commands using the bash variable SERVER_ADDRESS. That means that if you create that variable, you’ll be able to just copy the commands out of the book.\nFor example, as I write this, my server has the address \\(\\text{ec2-54-159-134-39.compute-1.amazonaws.com}\\). So would set my server address variable on my command line with SERVER_ADDRESS=ec2-54-159-134-39.compute-1.amazonaws.com.\nIf you’re used to R or Python, where it’s best practice to put spaces around =, notice that assigning variables in bash requires no spaces around =.\n\n\n\n\n8.9.2 Step 2: Log on with the .pem key\nThe .pem key you downloaded when you set up the server is the private key for a pre-registered keypair that will let you SSH into your server as the admin user (named ubuntu on a Ubuntu system).\nThe .pem key is just an SSH key, so you can SSH to your server with\n\n\nTerminal\n\nssh -i do4ds-lab-key.pem \\\n  ubuntu@SERVER_ADDRESS\n\nWhen you first try this, you’re probably going to get an alert that looks something like this:\n\n\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\n\n\\@ WARNING: UNPROTECTED PRIVATE KEY FILE! \\@\n\n\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\n\nPermissions 0644 for 'do4ds-lab-key.pem' are too open.\n\nIt is required that your private key files are NOT accessible by others.\n\nThis private key will be ignored.\n\nLoad key \"do4ds-lab-key.pem\": bad permissions\n\nubuntu@ec2-54-159-134-39.compute-1.amazonaws.com: Permission denied (publickey).\nBecause the keypair is so powerful, AWS requires that you restrict the access pretty severely. Before you can use it to open the server, you’ll need to change the permissions. We’ll get into permissions in Chapter 9. Until then, you can just change the permissions by navigating to the right directory with the cd command and running chmod 600 do4ds-lab-key.pem.\nOnce you’ve done that, you should be able to login to your machine as the root user. When you want to exit an SSH session and get back to your machine, you can just type exit.\n\n\n8.9.3 Step 3: Create your own SSH key\nYou really shouldn’t use the AWS-provided .pem key to login to your server after the first time. It’s too powerful. Create a normal SSH key using the instructions earlier in this chapter. In the next lab, we’ll get that SSH key configured for your user on the server."
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-    "text": "8.1 Practical SSH usage\nNow that you’ve got an understanding of how SSH works, the steps should be easy to remember.\n\nCreate an SSH keypair on any machine you’ll be SSH-ing from (local host).\nPut the public key anywhere you’ll be SSH-ing to (remote host).\nUse the ssh command to connect.\n\n\n8.1.1 Step 1: Create Keypair\nYou’ll create a keypair on any server you’re SSH-ing from. Remember, you should never move your private key. If you think the answer to a problem you’re having is to move your private key, think again. You should create a new private key wherever you want to move it to.\nTo create an SSH keypair, you should just follow a tutorial online. There are many.\nCreating the keypair will result in two parts. The one that ends in .pub is – you guessed it – the public key.\nIn most cases, you’ll only create one private key on each machine. If you follow standard instructions for creating a key, it will use the default name, probably id_ed25519.3 If you’re only creating one key, I’d recommend sticking with the default name because the ssh command will atuomatically use your keys if they have the default name.\nYou may not be able to use the default names if your organization mandates a unique keypair for every service you’re reaching out to. There isn’t a cryptographic reason for this. It’s mostly to make it easier to swap out the keypair later if you need to.\n\n\n8.1.2 Step 2: Register the public keys\nTo register a public key on a server you control, you’ll add the public key to the end of the user’s .ssh/authorized_keys file in their home directory. You’ll have to make sure the permissions on the authorized_keys file are correct. More on that in Chapter 11.\nIf you’re registering with a service, like GitHub.com, find a guide to registering SSH keys and it will show you how to do so.\n\n\n8.1.3 Step 3: Use SSH\nTo use SSH, you type ssh &lt;user&gt;@&lt;host&gt;. There are also other commands that can use SSH under the hood, like git or scp.\n\n\n\n\n\n\nFor Windows users\n\n\n\nFor a long time, Windows didn’t support SSH out of the box, so SSH-ing from Windows required a separate utility called PuTTY. More recent versions of Windows support using SSH directly in PowerShell or in Windows Subsystem for Linux (WSL). If SSH isn’t enabled on your machine, google for instructions.\n\n\nIf you have multiple SSH keys or didn’t use the default flag, you can specify a particular key with the -i flag.\nIf you’re using SSH a lot, I’d recommend setting up an SSH config file. An SSH config file allows you to create aliases that are shortcuts to SSH commands including users, hosts, and other details. So if you had a long SSH command like ssh -i my-ssh-key alex@server.example.com, you could shorten it to ssh alex-server or whatever you want.\nMany people also like using tmux with SSH. tmux is a terminal multiplexer, which allows you to manipulate terminal sessions from the command line. SSH sessions block the terminal session they’re using and will break when your computer goes to sleep. tmux allows you to create sessions and make them durable through sleeps and other operations. To be honest, I’m including tmux because lots of people love it, but I’ve tried using it and found the learning curve too steep for it to come into regular usage. Your mileage may vary.\nLastly, if you ever run into trouble using SSH, it has one of my favorite debugging modes. Just add a -v to your command for verbose mode. If that’s not enough information, add another v for more verbosity, and if that’s not enough, just add another v for super verbose mode."
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+    "text": "zsh is pronounced by just speaking the letters aloud, zee-ess-aitch. Some people might disagree and say it’s zeesh, but they’re not writing this book, are they?↩︎\nThe pattern is id_&lt;encryption type&gt;. ed25519 is the standard SSH key encryption type as of this writing.↩︎"
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+    "text": "9.1 A brief history of Linux\nA computer’s OS defines how applications can interact with the underlying hardware. OSes dictate how files are stored and accessed, how applications are installed, how network connections work, and more.\nYour laptop probably runs MacOS or Windows. Neither of them is Linux. But Linux is dominant basically everywhere else. Because it’s an open source OS and in order to accommodate that huge variety of use cases and contexts, Linux comes in a wide variety of “flavors” that differ by technical attributes and licensing model. These flavors are called distros, short for distributions.\nBefore the early 1970s, the market for computer hardware and software looked nothing like it does now. Computers of that era had extremely tight linkages between hardware and software. For example, there was no Microsoft Word you could use on a Dell machine or an HP machine or an Apple machine.\nInstead, every hardware company was also a software company. If Example Corp’s computer did text editing, it was because Example Corp had written (or commissioned) text editing software specifically for their machine. If Example Corp’s machine could run a game, Example Corp had written that game just for their computer.\nThen, in the early 1970s, researchers funded by AT&T’s Bell Labs released Unix – the first operating system. Now, there was a piece of middleware that sat between the computer hardware and the end-user software.\nAfter the advent of the OS, the computer market started looking a lot more familiar to 2020s eyes. Hardware manufacturers could build machines that ran Unix and software companies could write applications that ran on Unix.\nThe one issue (for everyone but Bell Labs) was that they were paying Bell Labs a lot of money for licenses to Unix. So in the 1980s, programmers started writing Unix-like OSes. These so-called Unix clones behaved just like Unix, but didn’t include any actual Unix code.2\nIn 1991, Linus Torvalds – then a 21 year-old Finnish grad student – released an open source Unix clone called Linux via a amusingly nonchalant newsgroup posting, saying, “I’m doing a (free) operating system (just a hobby, won’t be big and professional like gnu)…Any suggestions are welcome, but I won’t promise I’ll implement them :-).”3\nObviously, the Linux project outgrew that modest newgroup post. At this point there are over 600 Linux distros, reflecting both the natural fragmentation of popular open source projects, as well as disparate requirements for an OS for your car’s infotainment system versus a smartphone versus the controller for your smart thermostat.\nLuckily, you don’t have to know hundreds of distros. For server use, most organizations standardize on one of a handful. The most common open source distros are Ubuntu or CentOS. Red Hat Enterprise Linux (RHEL) is the most common paid distro.4 Many organizations on AWS are using Amazon Linux, which is independently maintained by Amazon but was originally a RHEL derivative.5\nMost individuals who have a choice in the matter prefer Ubuntu. It’s definitely my personal preference. It’s a little simpler and easier to configure than the others.\n\n\n\n\n\n\nA note on Ubuntu Versioning\n\n\n\nUbuntu versions are numbered by the year and month they were released. Most people use the Long Term Support (LTS) releases, which are released in April of even years.\nUbuntu versions have fun alliterative names, so you’ll hear people refer to releases by name or version. As of this writing, most Ubuntu machines are running Bionic (20.04, Bionic Beaver) or Jammy (22.04, Jammy Jellyfish)."
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-    "text": "8.3 Cheatsheet: ssh\nssh &lt;user&gt;@&lt;host&gt;\n\n\n\n\n\n\n\n\nFlag\nWhat it does\nNotes\n\n\n\n\n-v\nVerbose, good for debugging.\nAdd more vs as you please, -vv or -vvv.\n\n\n-i\nChoose identity file (private key)\nNot necessary with default key names."
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+    "text": "9.2 Bash basics\nLinux is administered from the command line using bash or a bash alternative like zsh. The philosophy behind bash and its derivatives says that you should be able to accomplish anything you want with small programs invoked via a command. Each command should do just one thing, and complicated things should be accomplished by composing commands – taking the output from one as the input to the next.\nInvoking a command is done by typing the command on the command line and hitting enter. If you ever find yourself stuck in a situation you can’t seem to exit, ctrl + c will quit in most cases.\nHelpfully, most bash commands are an abbreviation of the word for what the command does. Unhelpfully, the letters often seem somewhat random.\nFor example, the command to list the contents of a directory is ls, which sorta makes sense. Over time, you’ll get very comfortable with the commands you use frequently.\nBash commands can be modified to behave the way you need them to.\nCommand arguments provide details to the command. They come after the command with a space in between. For example, if I want to run ls on the directory /home/alex, I can run ls /home/alex on the command line.\nSome commands have default arguments. For example the default argument for the ls command is the current directory. So if I’m in /home/alex, I’d get the same thing from either ls or ls /home/alex.\nOptions or flags modify how the command operates and come between the command and arguments. Flags are denoted by having one or more dashes before them. For example, ls allows the -l flag, which displays the output as a list. So, ls -l /home/alex would get the files in /home/alex as a list.\nSome flags themselves have flag arguments. For example, the -D flag allows specifying a format for how the datetime is displayed from ls -l. So running ls -l -D %Y-%m-%dT%H:%M:%S /home/alex lists all the files in /home/alex with the date-time of the last update formatted in ISO-8601 format, which is always the correct format for dates.\nBash commands are always formatted as &lt;command&gt; &lt;flags + flag args&gt; &lt;command args&gt;.\nIt’s nice that this structure is standard. It’s not nice that the main argument is all the way at the end, because it makes long bash commands hard to read. To make commands more readable, you can break the command over multiple lines and include one flag or argument per line. You can tell bash you want it to continue a command after a line break by ending the line with a space and a \\.\nFor example, here’s that long ls command more nicely formatted:\n\n\nTerminal\n\n&gt; ls -l \\\n  -D %Y-%m-%dT%H:%M:%S \\\n  /home/alex\n\nAll of the flags and arguments for commands can be found in the program’s man page (short for manual). You can access the man page for any command with man &lt;command&gt;. You can scroll the man page with arrow keys and exit with q.\nBash is a real – if ugly – programming language, so you can assign variables with &lt;var-name&gt;=&lt;value&gt; (no spaces allowed) and access them $&lt;var-name&gt;. The bash version of print is echo.\nFor example,\n\n\nTerminal\n\n&gt; MSG=\"Hello World!\"\n&gt; echo $MSG\nHello World!\n\nFor the most part, you’ll write commands directly on the command line. It’s also possible to write and run bash scripts that include conditionals, loops, and functions. Bash scripts usually end in .sh and are most often run with the sh command like sh my-script.sh.\nThe advantage of writing bash scripts is that they can run basically anywhere. The disadvantage of writing bash scripts is that bash is a truly ugly programming language that is hard to debug."
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-    "text": "SSH actually can be used between any two machines, provided at least one is accepting SSH connections. For data scientists, SSH is almost always use to connect from a local machine to a server.↩︎\nAnd prime numbers generally loom large in the operation.↩︎\nThe pattern is id_&lt;encryption type&gt;. ed25519 is the standard SSH key encryption type as of this writing.↩︎"
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+    "text": "9.3 Commands run on behalf of users\nWhenever a program is running in Linux, it is running as a particular user who can be identified by their username.\nOn any Unix-like system, the whoami command returns the username of the active user. So when I run whoami on my MacBook, I get:\n\n\nTerminal\n\n&gt; whoami                                                       \nalexkgold\n\nUsernames have to be unique on the system – but they’re not the true identifier for a user. A user is uniquely identified by their user id (uid), which maps to all the other user attributes like username, password, home directory, groups, and more. The uid for a user is assigned at the time the user is created and usually don’t need to be changed or specified manually.6\nEach human who accesses a Linux server should have their own account. In addition, many applications create service account users for themselves and run as those users. For example, installing RStudio Server will create a user with username rstudio-server. Then, when RStudio Server goes to do something – start an R session for example – it will do so as rstudio-server.\nUser uids start at 10,000 with those below 10,000 reserved for system processes. There’s also one special user – called the admin, root, sudo, or super user who gets the special uid 0.\nUsers belong to groups, which are collections of one or more users. Each user has exactly one primary group and can be a member of secondary groups.7 By default, each user’s primary group is the same as their username.\nLike a user has a uid, a group has a gid. User gids start at 100.\nYou can see a user’s username, uid, groups, and gid with the id command. On my MacBook, I’m a member of a number of different groups, with the primary group staff.\n\n\nTerminal\n\n&gt; id                                                                \nuid=501(alexkgold) gid=20(staff) groups=20(staff),12(everyone),61(localaccounts),79(_appserverusr),80(admin),81(_appserveradm),98(_lpadmin),701(com.apple.sharepoint.group.1),33(_appstore),100(_lpoperator),204(_developer),250(_analyticsusers),395(com.apple.access_ftp),398(com.apple.access_screensharing),400(com.apple.access_remote_ae)\n\nIf you ever need to add users to a server, the easiest way is with the useradd command. Once you have a user, you may need to change the password, which you can do at any time with the passwd command. Both useradd and passwd start interactive prompts, so you don’t need to do much more than run those commands.\nIf you ever need to alter a user – the most common task being to add a user to a group, you would use the usermod command with the -aG flag."
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-    "text": "9.1 Container lifecycle\nDocker is primarily concerned with the creation, movement, and running of containers. A container is a software entity that packages code and its dependencies down to the operating system. Containers make it possible to have completely different environments coexisting side by side on one physical machine.\n\n\n\n\n\n\nNote\n\n\n\nContainers aren’t the only way to run multiple virtual environments side-by-side – they’re just the most popular.\nDocker Containers also aren’t the only type of container, though they’re often treated that way. You may run across other kinds, like Apptainer (formerly Singularity), which is often used in high performance computing contexts.\n\n\nA Docker Image is an immutable snapshot of a container. When you want to run a container, you pull the image and run it as an instance, which is what you’ll actually interact with.\nImages are most often stored in registries, which are similar to git repositories. The most common registry is Docker Hub, which allows public hosting and private hosting of images in free and paid tiers. Docker Hub includes official images for operating systems and programming languages, as well as many, many community-contributed containers. Some organizations run their own private registries, usually using registry as a service offerings from cloud providers.2\nImages are built from Dockerfiles – the code that defines the image. Dockerfiles are usually stored in a git repository. It’s common to build images in a CI/CD pipeline so changes to the Dockerfile are immediately built and pushed to the registry.\nAll instances run on an underlying machine, called a host. A primary feature – also a liability – of using containers is that they are completely ephemeral. Unless configured otherwise, anything inside an instance when it shuts down vanishes without a trace.\nYou can control Docker Containers from the Docker Desktop app. If you’re going to be using Docker on a server, you’ll mostly be interacting via the command line interface (CLI). All Docker CLI commands are formatted as docker &lt;command&gt;.\nThe graphic below shows the different states for a container and the CLI commands to move from one to another.\n\n\n\n\n\n\n\nNote\n\n\n\nI’ve included docker pull on the graphic for completeness, but you’ll almost never run it. docker run auto-pulls the container(s) it needs.\n\n\nThere’s a cheatsheet for Docker CLI commands at the end of this chapter.\n\n9.1.1 Image Names\nIn order to build, push, pull, or run an image, you’ll need to know which image you’re talking about. Every image has a name that consists of an id and a tag.\n\n\n\n\n\n\nNote\n\n\n\nIf you’re using Docker Hub, container ids take the form &lt;user&gt;/&lt;container name&gt;, so I might have the container alexkgold/my-container. This should look familiar to GitHub users.\nOther registries may enforce similar conventions for ids, or they may allow ids in any format they want.\n\n\nTags are used to specify versions of variants of containers and come after the id and :. For example, the official Python docker image has versions for each version of Python like python:3 as well as variants for different operating systems and a slim version that saves space by excluding recommended packages.\nSome tags, usually used for versions, are immutable. For example, the rocker/r-ver container is a container that is built on Ubuntu and has a version of R built in. There’s a rocker/r-ver:4.3.1, which is a container with R 4.3.1.\nOther tags are relative to the point in time. If you don’t see a tag on a container name, it’s using the default latest. Other common relative tags refer to the current development state of the software inside like devel, release, or stable."
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+    "text": "9.4 Permissions dictate what users can do\nIn Linux, everything you can interact with is just a file. Every log – file. Every picture – file. Every application – file. Every configuration – file.\nSo determining whether a user can take an action is really a question of whether they have the right permissions on a particular file.\nBasic Linux permissions (called POSIX permissions) consist of a 3x3 matrix of read, write, and execute for the owner, the owning group, and everyone else. Read means the user can see the contents of a file, write means the user can save a changed version of a file, and execute means they can run the file as a program.\n\n\n\n\n\n\nNote\n\n\n\nThere are more complex ways to manage Linux permissions. For example, you might hear about Access Control Lists (ACLs). They’re beyond the scope of this book.\nThere is more information on different ways organizations manage users and what they’re allowed to do in Chapter 17, which is all about auth.\n\n\nFor example, here’s a set of permissions that you might have for a program if you wanted anyone to be able to run it, group members to inspect it, and only the owner to change it.\n\nDirectories also have permissions – read allows the user see what’s in the directory, write allows the user to alter what’s in the directory, and execute allows the user to enter the directory.\nFile permissions and directory permissions don’t have to match. For example, a user could have read permissions on a directory, so they could see the names of the files, but not actually have read permissions on any of the files, so they can’t look at the contents.\nWhen you’re working on the command line, you don’t get a little grid of permissions. Instead they’re expressed in one of two ways. The first is the string representation, which is a 10-character string that looks something like -rw-r–r--.\nThe first character indicates the type of file: most often - for normal (file) or d for a directory.\nThe next nine characters are indicators for the three permissions for the user, the group, and everyone else. There will be an r for read, a w for write, and an x for execute or - to indicate that they don’t have the permission.\nSo the permissions in the graphic would be -rwxr-x--x for a file and drwxr-x--x for a directory.\nThe best way to get these permissions is to run the ls -l command.\n\n\nTerminal\n\n&gt; ls -l                                                           \n-rw-r--r--  1 alexkgold  staff     28 Oct 30 11:05 config.py\n-rw-r--r--  1 alexkgold  staff   2330 May  8  2017 credentials.json\n-rw-r--r--  1 alexkgold  staff   1083 May  8  2017 main.py\ndrwxr-xr-x 33 alexkgold  staff   1056 May 24 13:08 tests\n\nEach line starts with the string representation of the permissions followed by the owner and group so you can easily understand who should be able to access that file or directory.\nAll of the files in this directory are owned by alexkgold. Only the owner (alexkgold) has write permission, but everyone has read permission. In addition, there’s a tests directory, with read and execute for everyone and write only for alexkgold.\nIn the course of administering a server, you will probably need to change a file’s permissions. You can do so using the chmod command.\nFor chmod, permissions are indicated as a three digit number, like 600, where the first digit is the permission for the user, the second for the group, and the third for everyone else. To get the right number, you sum the permissions as follows: 4 for read, 2 for write, and 1 for execute. You can check for yourself that any set of permissions is uniquely identified by a number between 1 and 7.8\nSo to implement the permissions from the graphic, you’d want the permission set 751 to give the user full permissions (4 + 2 + 1), read and execute (4 + 1) to the group, and execute only (1) to everyone else.\n\n\n\n\n\n\nNote\n\n\n\nIf you spend any time administering a Linux server, you almost certainly will at some point find yourself running into a problem and applying chmod 777 out of frustration to rule out a permissions issue.\nI can’t tell you not to do this – we’ve all been there. But if it’s something important, be sure you change it back once you’re finished figuring out what’s going on.\n\n\nIn some cases you might actually want to change the owner or group of a file. You can change users and groups with either names or ids. You can do so using the chown command. Changing users just uses the username and changing groups get prefixed with a colon.\nIn some cases, you might not be the correct user to take a particular action. If you want to change the user you are, you can use the su (switch user) command. You’ll be prompted for a password to make sure you’re allowed.\nThe admin or root user has full permissions on every file and there are some actions that only the root user can do. When you need to do root-only things, you usually don’t want to su to be the root user. It’s too powerful. Plus if you have user-level configuration, it all gets left behind.\nInstead, individual users can be granted the power to temporarily assume root privileges without changing to be the root user. This is accomplished by making them members of the admin group. If a user is a member of the admin group, they can prefix commands with sudo to run those commands with root privileges.\nThe name of the admin group varies by distro. In Ubuntu, the group is called sudo."
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-    "text": "9.2 Running Containers\nThe docker run command runs container images as an instance. You can run docker run &lt;image name&gt; to get a running container. However, most things you want to do with your instance require several command line flags.\nThere are a few flags that are useful to manage how your containers run and get cleaned up.\nThe -name &lt;name&gt; flag names an instance. It’s not required, but can be useful to give the instance a name you can remember or use in code. If you don’t provide a name, each instance gets a random alphanumeric id on start.\nThe -rm flag automatically removes the container after its done. If you don’t use the -rm flag, the container will stick around until you clean it up manually with docker rm. The -rm flag can be useful when you’re iterating quickly – especially because you can’t re-use names until you remove the container.\nThe -d flag will run your container in detached mode. This is useful when you want your container to run in the background and not block your terminal session. It’s useful when running containers in production, but you probably don’t want to use it when you’re trying things out and want to see logs streaming out as the container runs.\n\n9.2.1 Getting information in and out\nWhen a container runs, it is isolated from the host. This is a great feature – it means programs running inside the container can address the container’s filesystem and networking without worrying about the host outside. But it also means that using resources on the host requires explicit declarations as part of the docker run command.\nIn order to get data in or out of a container, you need to mount a shared volume (directory) between the container and host with the -v flag. You specify a host directory and a container directory separated by :. Anything in the volume will be available to both the host and the container at the file paths specified.\nFor example, maybe you’ve got a container that runs a job against data it expects in the /data directory. On your host machine, this data lives at /home/alex/data. You could make this happen with\n{bash filename=Terminal} docker run -v /home/alex/data:/data\nHere’s a diagram of how this works.\n\nSimilarly, if you have a service running in a container on a particular port, you’ll need to map the container port to a host port with the -p flag.\n\n\n9.2.2 Other runtime commands\nIf you want to see what containers you’ve got, docker ps lists them. This is especially useful to get instance ids if you didn’t bother with names.\nTo stop a running container docker stop does so nicely and docker kill terminates a container immediately.\nYou can view the logs from a container with docker logs.\nLastly, if you need to run a command inside a running instance, you can use docker exec. This is most commonly used to access the command line inside the container as if SSH-ing to a server with docker exec -it &lt;container&gt; /bin/bash.\nWhile it’s normal to SSH into a server to poke around, it’s somewhat of an anti-pattern to do the same in a container. In general you should prefer to review logs and adjust Dockerfiles and run commands rather than exec in."
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+    "text": "9.5 The Linux Filesystem is a tree\nRegardless of which Linux distro you’re running, understanding where to find things on your system is crucial.\nAll of the information available to a computer is indexed by its filesystem, which is made up of directories or folders, which are containers for other directories and for files.\nOn your laptop, you’re probably used to browsing the filesystem with your mouse. On your phone, the filesystem is completely obscured by apps, but it’s there.\nOn a Linux server, the only way to traverse the filesystem is with written commands. Having a good mental model for what the filesystem looks like is, therefore, really important.\nOn Linux, the entire filesystem is a tree (or perhaps an upside-down tree). Every directory is contained in by a parent directory, and may contain one or more children or sub-directories. The root directory, / is the base of the tree and is its own parent. A / in between two directories means that it’s a sub-directory.\n\nEvery directory is a sub-directory of / or a sub-directory of a sub-directory of / or…you get the picture. So the /home/alex file path defines a particular location, which is the alex sub-directory of /home, which is a sub-directory of the root directory, /.\n\n\n\n\n\n\nTip\n\n\n\nIt’s never necessary, but sometimes the tree-like layout for a directory is helpful. The tree utility can show you one. It doesn’t always come pre-installed, so you might have to install it.\n\n\nBecause the entire Linux filesystem is based at /, it doesn’t matter what physical or virtual disks you have attached to your system. They will fall somewhere under the main filesystem (often inside /mnt).\nThis will be familiar to MacOS users, because MacOS is based on an operating system called BSD that, like Linux, is a Unix clone.\nIf you’re familiar with Windows, the Linux filesystem may seem a little strange.\nIn Linux, each computer has exactly one filesystem, which is based at the root, /. Network shares or other types of volumes can be mounted somewhere on the filesystem, often below /mnt, but the fact that they’re on separate drives is obscured from the user.\nIn Windows, each physical or logical disk has its own filesystem with its own root. You’re probably familiar with C: as your main filesystem. Your machine may also have a D: drive. If you’ve got network share drives, they’re likely at M: or N: or P:.\nOne other difference is that Windows uses \\ to separate file path elements rather than /. This used to be a big deal, but newer versions of Windows accept file paths using /.\n\n9.5.1 Working with file paths\nWhenever a command runs, it runs at a particular path in the filesystem, called the working directory. You can get the absolute path to your working directory with the pwd command, which is an abbreviation for print working directory.\nWhen you want a command to run the same irrespective of where it’s run from, it’s best to use an absolute path, which is a path specified relative to the root. They operate the same irrespective of the current working directory. Absolute file paths are easy to recognize because they always start with /.\nSometimes it’s convenient to use a relative file path, which starts at the working directory, denoted by .. So, for example, if I want to access the data subdirectory of the working directory, that would be available at ./data.\nThe working directory’s parent is at ... So, you could see everything in the parent directory of your current working directory with ls .. or its parent with ls ../...\nAll accounts that represent actual humans should have a home directory, which usually livelive inside /home.\nThe home directory and all its contents are owned by the user to whom it belongs. The home directory is the user’s space to store the things they need, including user-specific configuration. When navigating the file system, the user can find their home directory is at ~.\nAlong with being able to inspect directories with ls, it’s useful to be able to change your working directory with the cd command, short for change directory. You can use either absolute or relative file paths with cd. So if you were in /home/alex and wanted to navigate to /home, either cd .. or cd /home would work.\nSome files or directories are hidden so they don’t appear in a normal ls. You know a file or directory is hidden because its name starts with .. Hidden files are usually configuration files that you aren’t manipulating in normal usage. These aren’t secret or protected in any way, they’re just skipped by ls for convenience. If you want to display all files in a directory, including hidden ones, you can use the -a flag (for all) with ls.\nYou’ve already seen a couple of hidden files in this book – your GitHub Action was configured in the .github directory and your Prezto configuration was done in the .zpreztorc file. You might also be familiar with .gitignore, .Rprofile, and .Renviron."
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-    "text": "9.3 Building Images from Dockerfiles\nA Dockerfile is a set of instructions that you use to build a Docker Image. If you know how to accomplish something from the command line, you shouldn’t have too much trouble building a Dockerfile to do the same.\nOne thing to consider when creating Dockerfiles is that the resulting image is immutable. That means anything you build into the image is forever frozen in time. So you’ll definitely want to set up the versions of R and Python and install system requirements. Depending on the purpose of your container, you may want to copy in code, data, and/or R and Python packages, or you may want to mount those in a volume at runtime.\nThere are many Dockerfile commands. You can review them all in the Dockerfile documentation, but here are the handful that are enough to build most images.\n\nFROM – specify the base image. Usually the first line of the Dockerfile.\nRUN – run any command as if you were sitting at the command line inside the container.\nCOPY – copy a file from the host filesystem into the container.\nCMD - Specify what command to run on the container’s shell when it runs, usually the last line of the Dockerfile.3\n\nEvery Dockerfile command defines a new layer.\nA great feature of Docker is that it only rebuilds the layers it needs to when you make changes. For example, take the following Dockerfile:\nFROM ubuntu:latest\n\nCOPY my-data.csv /data/data.csv\n\nRUN [\"head\", \"/data/data.csv\"]\nLet’s say I wanted to change the head command to tail. Rebuilding this container would be nearly instantaneous because the container would only start rebuilding after the COPY command.\nOnce you’ve created your Dockerfile, you build it into an image using docker build -t &lt;image name&gt; &lt;build directory&gt;. If you don’t provide a tag, the default tag is latest.\nYou can then push the image to DockerHub or another registry using docker push &lt;image name&gt;."
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+    "text": "9.6 Moving files and directories\nYou will frequently need to change where files are on your system, including copying, deleting, moving, and more.\nYou can copy a file or directory from one place to another using the cp command. cp leaves behind the old file or directory and adds the new one at the specified location. You can use the -r flag to recursively copy everything in a directory.\nYou can move a file with the mv command, which does not leave the old file behind. If you want to remove a file entirely, you can use the rm command. The -r (recursive) flag can be used with rm to remove everything within a directory and the -f (force) flag can skip rm double checking you really want to do this.\n\n\n\n\n\n\nWarning\n\n\n\nBe very careful with the rm command, especially with -rf.\nThere’s no recycle bin. Things that are deleted are instantly deleted forever.\n\n\nIf you want to make a directory, mkdir makes a file path. It can be used with relative or absolute file paths, and can include multiple layers of paths to create. For example, if you’re in /home/alex, you could mkdir project1/data to make a project1 directory and data sub-directory.\nThe mkdir command throws an error if you try to create a path that includes some directories that already exist – for example if project1 already existed in the example above. The -p flag can be handy to create only the parts of the path that don’t exist.\nSometimes it’s useful to operate on every file inside a directory. You can get every file that matches a pattern with the wildcard, *. You can also do partial matching with the wildcard to get all the files that match part of a pattern.\nFor example, let’s say I have a /data directory and I want to put a copy of only the .csv files inside into a new data-copy sub-directory. I could do the following:\n\n\nTerminal\n\n&gt; mkdir -p /data/data-copy\n&gt; cp /data/*.csv /data/data-copy\n\n\n9.6.1 Moving things to and from the server\nIt’s very common to have a file on your server you want to move to your desktop or vice versa. There are a few different ways to move files and directories.\nIf you’re moving multiple files, it’s easier to combine them into a single object and move that. The tar command turns a set of files or whole directory into a single archive file, usually with the file suffix .tar.gz. Creating an archive also does some compression. The amount depends on the content.\nIn my opinion, tar is a rare failure of bash to provide standalone commands for anything you need to do. tar is used to both create and unpack (extract) archive files. Telling it which one requires the use of several flags. You’ll basically never use tar without a bunch of flags and the incantation is hard to remember. I google it every time I use it. The flags you’ll use most often are in the cheatsheet in the appendix.\nYou can move files to or from a server with the scp command. scp – short for secure copy – is basically cp, but with an SSH connection in the middle.9\nSince scp establishes an SSH connection, you need to make the request to somewhere that is accepting SSH connections. That means that whether you’re copying something to or from a server, you’ll run scp from a regular terminal on your laptop, not one that’s already SSH-ed into your server.\nRegular ssh options work with scp, like -i and -v."
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-    "text": "9.4 Comprehension Questions\n\nDraw a mental map of the relationship between the following: Dockerfile, Docker Image, Docker Registry, Docker Container\nWhen would you want to use each of the following flags for docker run? When wouldn’t you?\n\n-p, --name, -d, --rm, -v\n\nWhat are the most important Dockerfile commands?"
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+    "text": "9.7 Pipes and redirection\nYou can always copy and paste command outputs or write them to a file, but it can also be helpful to just chain a few commands together. Linux provides a few handy operators you can use to make this easy.\nThe simplest operator is the pipe |, which just takes the output of one command and makes it the input for the next command.\nFor example, you might want to see how many files are in a directory. The wc -l (word count, lines) command counts lines, so you could do ls | wc -l since each file returned by ls is counted as a line.\n\n\n\n\n\n\nCeci n’est pas une pipe?\n\n\n\nThe pipe should feel extremely familiar to R users.\nThe pipe from the {magrittr} package, %&gt;%, was introduced in 2013, and is a popular part of the {tidyverse}.10 The {magrittr} pipe was inspired by both the Unix (Linux) pipe and the pipe operator in the F# programming language.\nDue to its popularity, the pipe |&gt; was formally added to the base R language in R 4.1 in 2021.\n\n\nThere are a few operators that write the output of the left hand side into a file.\nThe &gt; command takes the output of a command on the left and writes it as a new file. If the file you specify already exists, it will be overwritten.\nIf you want to append the new text, rather than overwrite, &gt;&gt; appends to the end of the file. I generally default to &gt;&gt;, because it’ll create a new file if one doesn’t exist, and I usually don’t mean to overwrite what’s there.\nA common reason you might want to do this is to add something to the end of your .gitignore. For example, if you want to add your .env file to your .gitignore, you could do that with echo .env &gt;&gt; .gitignore.11 Another great usage is to add a new public key to your .ssh/authorized_keys file.\nThere are times when you want to make files or directories with nothing in them. The touch command makes a blank file at the specified file path. If you touch a preexisting file, it updates the time the file was last updated without actually making any changes. This can be useful because some applications look at the timestamp on files to see if action is needed."
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-    "text": "9.5 Lab: Putting an API in a Container\nPutting an API into a container is popular way to host them. In this lab, we’re going to put the Penguin Model Prediction API from Chapter 2 into a container.\nIf you’ve never used Docker before, start by installing Docker Desktop on your computer.\nYou should feel free to write your own Dockerfile to put the API in a container. If you want to make it easy, the {vetiver} package, which you’ll remember auto-generated the API for us, can also auto-generate a Dockerfile. Look at the package documentation for details.\nI’m using this code to generate my Dockerfile\nfrom pins import board_folder\nfrom vetiver import prepare_docker\n\nboard = board_folder(\"/data/model\", allow_pickle_read=True)\nprepare_docker(board, \"penguin_model\", \"docker\")\nOnce you’ve generated your Dockerfile, take a look at it. Here’s the one for my model:\n\n\nDockerfile\n\n# # Generated by the vetiver package; edit with care\n# start with python base image\nFROM python:3.9\n\n# create directory in container for vetiver files\nWORKDIR /vetiver\n\n# copy  and install requirements\nCOPY vetiver_requirements.txt /vetiver/requirements.txt\n\n#\nRUN pip install --no-cache-dir --upgrade -r /vetiver/requirements.txt\n\n# copy app file\nCOPY app.py /vetiver/app/app.py\n\n# expose port\nEXPOSE 8080\n\n# run vetiver API\nCMD [\"uvicorn\", \"app.app:api\", \"--host\", \"0.0.0.0\", \"--port\", \"8080\"]\n\nThis auto-generated Dockerfile is very nicely commented, so its easy to follow.\n\n\n\n\n\n\nNote\n\n\n\nThis container follows the best practices from Chapter 2. We’d expect the model to be updated much more frequently than the container itself, so the model isn’t built into the container. Instead, the container knows how to fetch the model using the {pins} package.\n\n\nNow build the container using docker build -t penguin-model ..\nYou can run the container using\ndocker run --rm -d \\\n  -p 8080:8080 \\\n  --name penguin-model \\\n  penguin-model\nIf you go to http://localhost:8080 you’ll find that…it doesn’t work? Why? If you run the container attached (remove the -d from the run command) you’ll get some feedback that might be helpful.\nIn line 15 of the Dockerfile, we copied the app.py in to the container. Let’s take a look at that file to see if we can find any hints.\n\n\napp.py\n\nfrom vetiver import VetiverModel\nimport vetiver\nimport pins\n\n\nb = pins.board_folder('./model', allow_pickle_read=True)\nv = VetiverModel.from_pin(b, 'penguin_model', version = '20230422T102952Z-cb1f9')\n\nvetiver_api = vetiver.VetiverAPI(v)\napi = vetiver_api.app\n\nLook at that (very long) line 6. The API is connecting to a local directory to pull the model. Is your spidey sense tingling? Something about container filesystem vs host filesystem?\nThat’s right – we put our model at /data/model on our host machine. But the API inside the container is looking for /data/model inside the container, which doesn’t exist!\nThis is a case where we need to mount a volume into the container like so\ndocker run --rm -d \\\n  -p 8080:8080 \\\n  --name penguin-model \\\n  -v /data/model:/data/model \\\n  penguin-model-local\nAnd NOW you should be able to get your model up in no time.\n\n9.5.1 Lab Extension\nRight now, logs from the API just stay inside the container instance. But that means that the logs go away when the container does. That’s obviously bad if the container dies because something goes wrong.\nHow might you make sure that the container’s logs get written somewhere more permanent?"
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+    "text": "9.8 Comprehension Questions\n\nWhat are the parts of a bash command?\nWhere do commands run? How do you know where they’re going to run or specify a relative path?\nHow can you copy, move, or delete a file? What about to or from a server?\nCreate a mind map of the following terms: Operating System, Windows, MacOS, Unix, Linux, Distro, Ubuntu\nWhat are the 3x3 options for Linux file permissions? How are they indicated in an ls -l command?"
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-    "text": "9.6 Cheatsheet: Docker\n\n9.6.1 Docker CLI Commands\n\n\n\n\n\n\n\n\n\nStage\nCommand\nWhat it does\nNotes and helpful options\n\n\n\n\nBuild\ndocker build &lt;directory&gt;\nBuilds a directory containing a Dockerfile into an image.\n-t &lt;name:tag&gt; provide a name to the container. tag is optional, defaults to latest.\n\n\nMove\ndocker push &lt;image&gt;\nPush a container to a registry.\n\n\n\nMove\ndocker pull &lt;image&gt;\nPull a container from a registry.\nRarely used because run pulls the container if needed.\n\n\nRun\ndocker run &lt;image&gt;\nRun a container.\nSee flags in next table.\n\n\nRun\ndocker stop &lt;container&gt;\nStop a running container.\ndocker kill can be used if stop fails.\n\n\nRun\ndocker ps\nList containers.\nUseful to get running container id to do things to it.\n\n\nRun\ndocker exec &lt;container&gt; &lt;command&gt;\nRun a command inside a running container.\nBasically always used to open a shell in a container with docker exec -it &lt;container&gt; /bin/bash\n\n\nRun\ndocker logs &lt;container&gt;\nViews logs for a container.\n\n\n\n\n\n\n9.6.2 Flags for docker run\n\nReminder: Order for -p and -v is &lt;host&gt;:&lt;container&gt;\n\n\n\n\n\n\n\nFlag\nEffect\nNotes\n\n\n\n\n--name &lt;name&gt;\nGive a name to the running container.\nOptional. Will be auto-assigned if not provided.\n\n\n--rm\nRemove container when its stopped.\nDon’t use in production. You probably want to inspect failed containers.\n\n\n-d\nDetach container (don’t block the terminal).\nAlmost always used in production.\n\n\n-p &lt;port&gt;:&lt;port&gt;\nPublish port from inside container to outside.\nNeeded if you want to access an app or API running inside the container.\n\n\n-v &lt;dir&gt;:&lt;dir&gt;\nMount volume into the container.\n\n\n\n\n\n\n9.6.3 Dockerfile Commands\nThese are the commands that go in a Dockerfile when you’re building it.\n\n\n\n\n\n\n\n\nCommand\nPurpose\nExample\n\n\n\n\nFROM\nIndicate base container.\nFROM rocker/r-ver:4.1.0\n\n\nRUN\nRun a command when building.\nRUN apt-get update\n\n\nCOPY\nCopy from build directory into the container.\nCOPY . /app/\n\n\nCMD\nSpecify the command to run when the container starts.\nCMD quarto render ."
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+    "text": "9.9 Lab: Set up a user\nWhen you use your server’s .pem key, you login as the root user, but that’s too much power to acquire on a regular basis. Additionally, since your server is probably for multiple people, you’re going to want to create users for them.\nIn this lab, you’ll create a regular user for yourself and add an SSH key for them so you can directly log in from your personal computer.\n\n9.9.1 Step 1: Create a non-root user\nLet’s create a user using the adduser command. This will walk us through a set of prompts to create a new user with a home directory and a password. Feel free to add any information you want – or to leave it blank – when prompted.\nI’m going to use the username test-user. If you want to be able to copy/paste commands, I’d advise doing the same. If you were creating users based on real humans, I’d advise using their names.\n\n\nTerminal\n\n&gt; adduser test-user\n\nWe want this new user to be able to adopt root privileges so let’s add them to the sudo group with\n\n\nTerminal\n\n&gt; usermod -aG sudo test-user\n\n\n\n9.9.2 Step 2: Add an SSH key for your new user\nLet’s register an SSH key for the new user by adding the key from the last lab to the server user’s authorized_users file.\nFirst, you need to get your public key to the server using scp.\nFor me, the command looks like this\n\n\nTerminal\n\n&gt; scp -i ~/Documents/do4ds-lab/do4ds-lab-key.pem \\ \n  ~/.ssh/id_ed25519.pub \\\n  ubuntu@$SERVER_ADDRESS:/home/ubuntu\n\nNote that I’m copying the public key, but SSH access is still using the server’s .pem key because I don’t have another key registered yet.\nNow the public key is on the server, but it’s in the ubuntu user’s home directory. You’ll need to do the following:\n\nCreate .ssh/authorized_keys in test-user’s home directory.\nCopy the contents of the public key you uploaded into the authorized_keys file (recall &gt;&gt;).\nMake sure the .ssh directory and authorized_keys files are owned by test-user with 700 permissions on .ssh and 600 on authorized_keys.\n\nYou could do this all as the admin user, but I’d recommend switching to being test-user at some point with the su command.\n\n\n\n\n\n\nTip\n\n\n\nIf you run into trouble assuming sudo with your new user, try exiting SSH and coming back. Sometimes these changes aren’t picked up until you restart the shell.\n\n\nOnce you’ve done all this, you should be able to log in from your personal computer with ssh test-user@$SERVER_ADDRESS.\nNow that we’re all set up, you should store the .pem key somewhere safe and never use it to log in again."
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-    "text": "This was truer before the introduction of M-series chips for Macs. Chip architecture differences fall below the level that a container captures, and many popular containers wouldn’t run on new Macs. These issues are getting better over time and will probably fully disappear relatively soon.↩︎\nThe big three container registries are AWS Elastic Container Registry (ECR), Azure Container Registry, and Google Container Registry.↩︎\nYou may also see ENTRYPOINT, which sets the command CMD runs against. Usually the default /bin/sh -c to run CMD in the shell will be the right choice.↩︎"
+    "text": "The remainder are mostly Windows servers. There are a few other OSes you might encounter, like Oracle Solaris. There is a product called Mac Server, but it’s just a program for managing Mac desktops and iOS devices, not a server OS.\nThere are also versions on Linux that run on desktop computers. Despite the best efforts of many hopeful nerds, desktop Linux is pretty much only used by professional computer people.↩︎\nOr at least they weren’t supposed to. There’s an interesting history of lawsuits, especially around whether the BSD OS illegally included Unix code.↩︎\nMore in the History of Linux Wikipedia article.\nPedants will scream that the original release of Linux was just the operating system kernel, not a full operating system like Unix. Duly noted, now go away.↩︎\nRHEL and CentOS are related operating systems, but that relationship has changed a lot in the last few years. The details are somewhat complicated, but most people expect less adoption of CentOS in enterprise settings going forward.↩︎\nAs I’m writing this, Amazon Linux 2 is popular, but Amazon Linux 2023 (AL2023) was recently released. I’d expect AL2023 or it’s successor to be dominant by the time you read this.↩︎\nThe one exception to this is when you’ve got the same user accessing resources across multiple machines. Then the uids have to match. If you’re worrying about this kind of thing, it’s probably time to bring in a professional IT/Admin.↩︎\nDepending on your version of Linux, there may be a limit of 16 groups per user.↩︎\nClever eyes may realize that this is just the base-10 representation of a three-digit binary number.↩︎\nIt’s worth noting that scp is now considered “insecure and outdated”. The ways it is insecure are rather obscure and not terribly relevant for most people. But if you’re moving a lot of data, you may want something faster. If so, I’d recommend more modern options like sftp and rsync. I probably wouldn’t bother if you’re only occasionally scp-ing small files to or from your server.↩︎\nThe title of this callout box is also the tagline for the {magrittr} package.↩︎\nNote that echo is needed so that the .env gets repeated as a character string. Otherwise .env would be treated as a command.↩︎"
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-    "text": "Labs in this Section\nEach chapter in this section has a lab. This section is about building out the backend around the website we created in the first section of the book.\nIn this section you’ll stand up an EC2 instance to serve as a workbench, add tools to work in R or Python, and host your Dockerized model and Shiny app there. We’ll also add the Shiny app to the website you created and make sure all the plumbing gets hooked up.\nFor more details on what you’ll do in each chapter, see Appendix B."
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+    "section": "10.1 Linux app install + config",
+    "text": "10.1 Linux app install + config\nYou can install applications to Linux from a distro-specific repository, much like the app store for your phone or you can just download the application from the internet and install it locally.\nFor Ubuntu, the apt command is used for interacting with repositories of .deb files. For CentOS and RedHat, the yum command is used for installing .rpm files.\n\n\n\n\n\n\nNote\n\n\n\nThe examples below are all for Ubuntu, since that’s what we use in the lab for this book. Conceptually, using yum is very similar, though the exact commands differ somewhat.\n\n\nIn addition to actually installing packages, apt is also the utility for ensuring the lists of available packages you have are up to date with update and that all packages on your system are at their latest version with upgrade. When you find Ubuntu commands online, it’s common to see them prefixed with apt-get update && apt-get upgrade -y. The -y flag bypasses a manual confirmation step.\nPackages are installed with apt-get install &lt;package&gt;. Depending on which user you are, you may need to prefix the command with sudo.\nSometimes, you may want to install packages that aren’t in the repository for your distro. Doing that will generally involve downloading a file directly from a URL – usually with wget and then installing it from the file you’ve downloaded.\n\n10.1.1 Application configuration\nOnce you’ve installed an application, it will generally require some configuration like the default background color, the set of users allowed in, or the frequency something updates.\nOn your personal computer, you’d probably find the setting in a series of dropdown menus at the top of the screen. On a server, no such menu exists.\nFor applications running on your server, application behavior is usually configured through one or more config files. For applications hosted inside a Docker container, behavior is often configured with environment variables, sometimes in addition to config files.\n\n\n10.1.2 Where to find application files\nLinux applications often use several files located in different locations on the filesystem. Here are some of the ones you’ll use most frequently:\n\n/bin, /opt, /usr/local, /usr/bin - installation locations for software.\n/etc - configuration files for applications.\n/var - variable data, most commonly log files in /var/log or /var/lib.\n\nThis means that on a Linux server, the files for a particular application probably don’t all live in the same directory. Instead, you might run the application from the executable in /opt, configure it with files in /etc, and troubleshoot from logs in /var.\n\n\n10.1.3 Command line configuration with vim and nano\nObviously, if you’re administering applications on a server, you’ll need to spend a fair bit of time editing text files. But how? Unlike on your personal computer, where you click a text file to open and edit it, you’ll need to work with a command line text editor when you’re working on a server.\nThere are two command line text editors you’ll probably encounter: nano and vi/vim.1 While they’re both powerful text editing tools, they can also be intimidating if you’ve never used them before.\nYou can open a file in either by typing nano &lt;filename&gt; or vi &lt;filename&gt;.\nAt this point many newbie command line users find themselves completely stuck, unable to do anything – even just exit and try again. But don’t worry, there’s a way out of this labyrinth.\nIf you opened nano, there will be some helpful-looking prompts at the bottom. You’ll see that once you’re ready to go, you can exit with ^x. But the ^ isn’t actually the caret character. On Windows, ^ is short for Ctrl and on Mac it’s for Command (⌘), so Ctrl + x or ⌘ + x will exit.\nWhere nano gives you helpful – if obscure – hints, a first experience in vim is the stuff of command line nightmares. You’ll type words and they won’t appear onscreen. Instead, you’ll experience dizzying jumps around the page and words and lines of text will disappear without a trace.\nThis is because vim uses the letter keys not just to type, but also to navigate the page and interact with vim itself. You see, vim was created before keyboards uniformly had arrow keys.\nWhile they can be intimidating at first, vim keybindings are worth spending some time learning. Vim includes some powerful shortcuts for moving within and between lines and selecting and editing text. Most IDEs you might use, including RStudio, JupyterLab, and VSCode have vim modes.\nWhen you enter vim, you’re in the (poorly named) normal mode, which is for navigation only. Pressing the i key activates insert mode, which will feel normal for those of us used to arrow keys. Once in insert mode, you can type and words will appear and you can navigate with the arrow keys.\nYou can return to normal mode with the escape key.\nOnce you’ve escaped, you may wish never to return to normal mode, but it’s the only way to save files and exit vim. In order to do file operations, you type a colon, :, followed by the shortcut for what you want to do, and enter. The two most common commands you’ll use are save (write) with w and quit with q. You can combine these together, so you can save and quit in one command using :wq.\nSometimes you may want to exit without saving or you might’ve opened and changed a file you don’t actually have permission to edit. If you’ve made changes and try to exit with :q, you’ll find yourself in an endless loop of warnings that your changes won’t be saved. You can tell vim you mean it with the exclamation mark, !, and exit using :q!."
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+    "text": "10.2 Reading logs\nOnce your applications are up and running, you may run into issues. Or even if you don’t, you may want to take a look at how things are running.\nMost applications write their logs into somewhere inside the /var directory. Some things will get logged to the main log at /var/log/syslog. Other things may get logged to /var/log/&lt;application name&gt; or /var/lib/&lt;application name&gt;.\nIt’s important to get comfortable with the commands to read text files in order to be able to examine logs (and other files). The commands I use most commonly are:\n\ncat is the basic command to print a file, starting at the beginning.\nless prints a file, starting at the beginning, but only a few lines at a time.\nhead prints only the first few lines and exits. It is especially useful to peer at the beginning of a large file, like a csv file – so you can quickly preview the column heads and the first few values.\ntail prints a file going up from the end. This is especially useful for log files, as the newest logs are appended to the end of a file. This is such a common practice that “tailing a log file” is a common phrase.\n\nSometimes, you’ll want to use the -f flag (for follow) to tail a file with a live view as it updates.\n\n\nSometimes you want to search around inside a text file. You’re probably familiar with the power and hassle of regular expressions (regex) to search for specific character sequences in text strings. The Linux command grep is the main regex command.\nIn addition to searching in text files, grep is often useful in combination with other commands. For example, it’s often useful to put the output of ls into grep to search for a particular file in a big directory using the pipe."
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+    "text": "10.3 Running the right commands\nLet’s say you want to open Python on your command line. One option would be to type the complete path to a Python install every time. For example, I’ve got a version of Python in /usr/bin, so /usr/bin/python3 works.\nBut in most cases, it’s nice to just type python3 and have the right version open up.\n\n\nTerminal\n\n&gt; python3\nPython 3.9.6 (default, May  7 2023, 23:32:45) \n[Clang 14.0.3 (clang-1403.0.22.14.1)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n&gt;&gt;&gt; \n\nIn some cases, this isn’t optional. Certain applications will rely on others being available, like RStudio Server needing to find R. Or Jupyter Notebook finding your Python kernels.\nSo how does Linux know where to find those applications and files?\nIf you ever want to check which actual executable is being used by a command, you can use the which command. For example, on my system this is the result of which python3.\n\n\nTerminal\n\n&gt; which python3                                                    \n/usr/bin/python3\n\nThe operating system knows how to find the actual runnable programs on your system via the path. The path is a set of directories that the system knows to search when it tries to run a program. The path is stored in an environment variable, conveniently named PATH.\nYou can check your path at any time with echo $PATH. On my MacBook, this is what the path looks like.\n\n\nTerminal\n\n&gt; echo $PATH                                                      \n/opt/homebrew/bin:/opt/homebrew/sbin:/usr/local/bin:/System/Cryptexes/App/usr/bin:/usr/bin:/bin:/usr/sbin:/sbin\n\nWhen you install a new piece of software you’ll need to add it two the path. Say I was to install a new version of Python in /opt/python. That’s not on my PATH, so my system wouldn’t be able to find it.\nI can get it on the path in one of two ways – the first option would be to add /opt/python to my PATH every time a terminal session starts usually via a file in /etc or the .zshrc.\nThe other option is to create a symlink to the new application in a directory already on the PATH. A symlink does what it sounds like – creates a way to link to a file from a different directory without moving it. Symlinks are created with the ln command."
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-    "text": "10.1 Layers of cloud services\nWhile the basic premise of the cloud is rent a server, there are layers and layers of services on top of that basic premise. Depending on your organization’s needs, it may make sense to rent a very basic service, or a higher level one.\nLet’s talk about cakes to help make the levels clear. This year, I’m planning to bake and decorate a beautiful cake for my friend’s birthday. It’s going to be a round layer cake with white frosting, and it’s going to say “Happy Birthday!” in teal with giant lavender frosting rosettes.\nNow that I’ve decided what I’m making, I have a few different options for how I get there. If I’m a real DIY kind of person, I could buy all the ingredients from the grocery store and make everything from scratch. Or I could buy a cake mix – reducing the likelihood I’ll buy the wrong ingredients or end up with unnecessary leftovers. Or maybe I don’t want to bake at all – I could just buy a premade cake already covered in white frosting and just do the writing and the rosettes.\nThe choice of how much to DIY my friend’s birthday cake and how much to get from a bakery is very much akin to your choices when buying server capacity from the cloud.\nTODO: Image of getting cake w/ IaaS, PaaS, SaaS\nIn the US, a huge fraction of server workloads run on servers rented from one of the “big three clouds” – Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). There are also numerous smaller cloud providers, many of which target more specific use cases.\nIt’s totally possible to just rent the raw ingredients from these cloud providers – they’ll happily rent you the most basic cloud services like servers, networking, and storage and let you put them together yourself. This kind of cloud service – the equivalent of baking from scratch – is called Infrastructure as a Service (IaaS, pronounced eye-az).\nBut then I’m responsible for managing all of the reproducibility stack – I have to make sure the servers are up to date with new operating systems and security patches, while also ensuring there are modern versions of R and Python on the system, and making sure there are RStudio and Jupyter Notebooks present.\nBut just as you might not want to have to buy eggs, milk, and sugar just to end up with a pretty cake, IT/Admin organizations are increasingly taking advantage of the cloud equivalent of cake mixes and premade blank sheet cakes.\nIf I want to offload more of the work, I can think about a Platform as a Service (PaaS – pronounced pass) solution. This would give me the ability to somehow define an environment and send it somewhere to run without worrying about the underlying servers. For example, I might want to build a docker container with Python and Jupyter Notebook and host it somewhere that autoscales for the number of users and the amount of other resources needed.\nThere are a bunch of different entities you can run in this way, and services to match each. For example, if you want to run a general app, you can use something like AWS’s Elastic Beanstalk to run a user-facing app that dynamically scales (TODO: Azure/GCP equivalents), if you want to run a container, you might use XXXX, and if you want to get a Kubernetes cluster as a service, you might use XXXX. If you want to just run a function, there’s always AWS Lambda.\n\n\n\n\n\n\nCaution\n\n\n\nI am not recommending you run a data science workbench on a service like Elastic Beanstalk. This actually tends not to work very well, for reasons we’ll get into in a bit.\n\n\nIf I want to go one level more abstracted, I might want to go with a Software as a Service (SaaS - pronounced sass) solution. This would be something like one of the cloud providers hosted machine learning environment where you can train, deploy, and monitor machine learning models. AWS has SageMaker, Azure has Azure Machine Learning, and GCP has Vertex AI. And there are organizations that host popular data science tools like Posit.cloud and Saturn Cloud that you can use.\nSometimes you’ll hear people describe PaaS or SaaS solutions called “going serverless”.\nThe first thing to understand about serverless computing is that there is no such thing as serverless computing.\nEvery bit of cloud computation runs on a server - the question is whether you have to deal with the server or if you just deal with a preconfigured service.\nIn this book, we’ll be working exclusively with IaaS services – taking the most basic services and building up a working data science environment. Once you understand how these pieces fit together, you’ll be in a much better place if it turns out your organization wants to leverage more abstracted versions of those services."
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+    "text": "10.4 Running applications as services\nOn your personal computer, you probably have programs that start every time your computer does. Maybe this happens for Slack, Microsoft Teams, or Spotify. Such applications that execute on startup and run in the background waiting for some sort of input are called a daemon or a service.\nOn a server, most of the applications are configured to run as a service so they’re ready for users who may not have the permissions to start them. For example, on a data science workbench, you’d want JupyterHub and/or RStudio Server to run as a service.\nIn Linux, the tool to turn a regular application into a daemon is called systemd. Some applications automatically configure themselves with systemd when they’re installed. If your application doesn’t, or you want to alter the startup behavior, most applications have their systemd configuration in /etc/systemd/system/&lt;service name&gt;.service.\nDaemonized services are controlled using the systemctl command line tool.\n\n\n\n\n\n\nNote\n\n\n\nBasically all modern Linux distros have coalesced around using systemd and systemctl. Older systems may not have it installed by default and you may have to install it or use a different tool.\n\n\nThe systemctl command has a set of sub-commands that are useful for working with applications. Providing those commands looks like systemctl &lt;subcommand&gt; &lt;application&gt;. Often systemctl has to be run as sudo, since you’re working with an application for all users of the system.\nThe most useful systemctl commands include status for checking whether a program is running or not, start, stop, and restart for a stop followed by a start. Many applications also support a reload command, which reloads configuration settings without having to actually restart the process. Exactly which settings require a restart vs a reload varies from one application to another.\nIf you’ve changed a service’s systemd configuration, you can load changes with daemon-reload. You also can turn a service on or off for the next time the server starts with enable and disable.\n\n10.4.1 Running Docker containers as a service\nOne of the benefits of running Docker Containers is that they run basically anywhere, so it’s a popular way to quickly run an application on a server. To run them as a service, you’ll need to make sure Docker itself is daemonized and then ensure the container you care about comes up whenever Docker does by setting a restart policy for the container.\nHowever, many Docker services involve coordinating more than one container. If that’s the case, you’ll want to use a system that’s custom-built for managing multiple containers. The most popular are Docker Compose or Kubernetes.\nDocker Compose is a relatively lightweight system where you write a YAML file to describe the containers you need and the relationship between them. You can then use a single command to launch the entire set of Docker containers.\nDocker Compose is fantastic for prototyping systems of Docker containers and for running small-scale Docker-ized deployments on a single server. There are many great resources on Docker Compose online to learn more.\nKubernetes is designed for a similar purpose, but instead of running a handful of containers on one server, Kubernetes is a heavy-duty production system designed to schedule hundreds or thousands of Docker-based workloads across a cluster of many individual servers.\nIn general, I’d recommend sticking with Docker Compose for the work you’re doing. If you’re finding yourself needing the full might of Kubernetes to do what you want, you probably should be working closely with a professional IT/Admin"
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-    "text": "10.2 Common services for data science usage\nIf you’re not familiar with cloud provider terminology, it can be very hard to tell what service you might need from a cloud provider, and they don’t really help the matter. It’s very common (especially in AWS) to have many different services that fulfill similar needs, and it can be really hard to concretely tell the difference.\nMaking the issue even more difficult, many companies go out of their way to make their services sound grand and important and don’t just say, “this is a ___ you can rent”.\nIt’s helpful to keep in mind that at the very bottom, all you’re doing is renting servers and storage and managing networking and permissions for the servers and storage. Every other service is just a combination of server, storage, networking, and permissions that comes with software pre-installed or configured to make your life easier.4\nWe’re going to talk through some of the basic services that are offered by each of the three major cloud platforms.\n\n\n\n\n\n\nCloud service naming\n\n\n\nAzure and GCP tend to name their offerings pretty literally, while AWS chooses cutesy names that have, at best, a tangential relationship to the task at hand. I’m going to try to name the services for each of the purposes I’m talking about, but it’s worth noting that feature sets aren’t exactly parallel across cloud providers.\nThis makes AWS names a little harder to learn, but much easier to recall once you’ve learned them. In this section – contrary to standard practice – I’m going to use the common abbreviated names for AWS services and put the full name in parentheses as these are just trivia.\n\n\nRemember, at the bottom of all cloud services are servers and each of cloud service provider has a service that is “just rent me a server”. AWS has EC2 (Elastic Cloud Compute) and Azure has Azure VMs, and Google has Google Compute Engine.\nAlong with servers, there are two main kinds of storage you’ll rent. The first is file storage, where you’ll store things in a file directory like on your laptop. These are AWS’s EBS (Elastic Block Store), Azure Managed Disk, and Google Persistent Disk.\nThe major cloud providers all also have blob (Binary Large Object) storage. Blob storage allows you to store individual objects somewhere and recall them to any other machine that has access to the blob store. The major blob stores are AWS Simple Storage Service (S3), Azure Blob Storage, and Google Cloud Storage.\nThere are also two important networking services for each of the clouds – a way to make a private network and a way to do DNS routing. If you don’t know what these mean, there will be a lot more detail in Chapter 12. For now, it’s enough to know that private networking is done in AWS’s VPC (Virtual Private Cloud), Azure’s Virtual Network, and Google’s Virtual Private Cloud. DNS is done in AWS’s Route 53, Azure DNS, and Google Cloud DNS.\nOnce you’ve got all this stuff up and running, you need to make sure that permissions are set in the right way. AWS has IAM (Identity and Access Management), Azure has Azure Active Directory, and Google has Identity Access Management.\nNow, there are a variety of things you might want to do past these basic tasks of server, storage, networking, and access management. Here are a few more services you’ll likely hear about over time.\n\n\n\n\n\n\n\n\n\nService\nAWS\nAzure\nGCP\n\n\n\n\nKubernetes cluster\nEKS (Elastic Kubernetes Service)\nAKS (Azure Kubernetes Service)\nGKE (Google Kubernetes Engine)\n\n\nRun a function as an API\nLambda\nAzure Functions\nGoogle Cloud Functions\n\n\nDatabase\nRDS/Redshift5\nAzure Database\nGoogle Cloud SQL\n\n\nML Platform\nSageMaker\nAzure ML\nVertex AI"
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+    "section": "10.5 Managing R and Python",
+    "text": "10.5 Managing R and Python\nAs the admin of a data science server, Python and R are some of the most critical software you’ll manage.\nIn general, the easiest path to making many users happy is having a bunch of versions of R and Python installed side-by-side. That way you can allow users to upgrade their version of R or Python as it works for their project, not according to your upgrade schedule.\nI’ve seen this work best by installing R and Python into the /opt/python and /opt/R directory. Users can grab them from there to create project-specific virtual environments. You’ll need to make sure permissions are correct on /opt/python for this to work.\nNow, this isn’t what will happen if you just sudo apt-get install python or sudo apt-get install R, so you’ll have to be a little more clever. My favorite route (though I’m obviously biased) is to install Python and R from the pre-built binaries provided by Posit.\n\n10.5.1 Python-specific considerations\nPython is one of the world’s most popular programming languages for general purpose computing. This actually makes configuring Python harder.\nAlmost every system comes with a system version of Python. This is the version of Python that’s used by the operating system for various tasks. It’s almost always very old and you really don’t want to mess with it.\nSo in order to configure Python on your system, you have to install data science specific versions of Python, get them on the path, and get the system version of Python off the path. This is the source of much frustration trying to get Python up and running, both on servers and your personal computer.\nOn your personal computer, Conda is a great solution for this problem. Conda allows you to install a standalone version of Python in user-space. That means that even if your organization doesn’t let you have admin rights on your computer, you can install and manage versions of Python for development.\nFor the same reason, Conda isn’t a great choice for administering a data science server. You’re not a user – you’re an admin. And giving everyone on the server access to Python versions is generally easier without Conda.\nThis is why it’s a good idea to install data science Python versions into /opt/python. It’s easy to add that one directory to the path, and it’s completely distinct from where the system Python lives.\n\n\n10.5.2 R-specific considerations\nPeople pretty much only ever install R to do data science so it’s generally not a huge deal where you install R and get it on the path. If you want just one version of R, using apt-get install is fine.\nIf you want multiple versions, you’ll need to manually install to /opt/R or use rig, which is an R-specific installation manager. Currently, rig only supports Windows, Mac, and Ubuntu."
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-    "text": "10.3 Comprehension Questions\n\nWhat is the difference between PaaS, IaaS, and SaaS? What’s an example of each that you’re familiar with?\nWhat are the names for AWS’s services for: renting a server, file system storage, blob storage"
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+    "text": "10.6 Managing System Libraries\nAs an admin, you’ll also have to decide what to do about system packages, which are Linux libraries you install from a Linux repository or the internet.\nMany packages in Python and R don’t do any work themselves. Instead, they’re just language-specific interfaces to system packages. For example, any R or Python library that uses a JDBC database connector will need to make use of Java on your system. And many geospatial libraries make use of system packages like GDAL.\nAs the administrator, you’ll need to make sure you understand what system libraries are needed for the Python and R packages you’re using, and you’ll need to make sure they’re available and on the path.\nFor many of these libraries, it’s not a huge pain. You’ll just install the required library using apt or the system package manager for your distro. In some cases (especially Java), more configuration may be required to make sure that the package you need shows up on the path."
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-    "text": "10.4 Lab: Intro to AWS\nWelcome to the lab!\nThe point of these exercises is to get you hands on with running servers and get you practicing the things you’re learning in the rest of the book.\nIf you walk through the labs sequentially, you’ll end up with a working data science workbench. It won’t suffice for any enterprise-level requirements, but it’ll be secure enough for a hobby project or even a small team.\nThese days most people are using servers from a cloud provider. We’re going to use AWS, as they’re by far the biggest cloud provider and the one you’re most likely to run into in the real world.\nAt a high level, you can do all of this with any cloud provider. Feel free to try if you prefer Azure or GCP, but the details on how to get started and service names will be different.\nIn the lab for this chapter, we’re going to get you up and running with an AWS account and show you how to manage, start, and stop EC2 instances in AWS.\nThe server we’ll stand up will be from AWS’s free tier – so there will be no cost involved as long as you haven’t used up all your AWS free tier credits before now.\nFor AWS things, I’m going to tell you what to do…but not the exact buttons, as AWS frequently changes the interface and this will almost certainly be out-of-date by the time you read it. The high level steps won’t change though.\nThroughout the lab, we’re going to go step by step through getting things done. If you know how to do any of the steps, I’d recommend you at least skim the step for any important details.\n\n10.4.1 Stand up an EC2 instance\n\n10.4.1.1 Step 1: Login to the AWS Console\nWe’re going to start by logging into AWS.\n\n\n\n\n\n\nNote\n\n\n\nAn AWS account is separate from an Amazon account for ordering stuff online and watching movies. If you’ve never created an account for AWS in particular, you’ll have to make an account.\n\n\nStart by signing in at https://aws.amazon.com. You most likely haven’t created an IAM account and should just login as root.\nOnce you’ve logged in, you’ll be confronted by the AWS console. There are a ton of things here – feel free to poke around if you want – come back to continue when you’re ready.\n\n\n10.4.1.2 Step 2: Stand up an instance\nAWS’s most basic “rent a server by the hour” service is called EC2 (Elastic Cloud Compute).\nThere are five things we have to configure in the process of launching the server. I’ll give you advice on each of them. If I don’t mention it here, feel free to stick with defaults.\n\n10.4.1.2.1 Name + Tags\nThe first choice is instance name and tags. They aren’t required, but I’d recommend you name the server something like do4ds-lab so you can remember what this server is later.\n\n\n10.4.1.2.2 Image\nNext, you’ll have to choose the image. An image is a snapshot of a system and serves as the starting point for your server. Images can range from just a bare operating system to a running RStudio instance that’s paused in between two computations.\nAll clouds have the concept of images. AWS calls their’s Amazon Machine Images or AMIs. Some images are free and some are paid.\nSince we’re going to work on configuring the server from the ground up, we’re going to choose an AMI that’s just the operating system. For the lab, let’s use Ubuntu Server LTS 22.04 image. It should say free tier eligible.\n\n\n\n\n\n\nNote\n\n\n\nIf you want to use a different operating system, that’s fine. For the purpose of being able to follow along with this lab, I’d recommend using Ubuntu 22.04.\nIf you happen to be reading this after 2026 or so, there will be newer operating systems. A newer version of Ubuntu should work very similarly for the purposes of this lab.\n\n\n\n\n10.4.1.2.3 Instance Type\nYou’ll have to choose an Instance Type. In AWS, there are two components to instance type – the family and the size. The family is the category of server that you’re using. In AWS, families are denoted by letters and numbers, so there are T2s and T3s, C4s, R5s, and many more.\nWithin each family, there are different sizes. The sizes availble vary by the family, but generally range from nano to multiples of xlarge like 24xlarge.\nFor now, I’d recommend you get the largest server that is free tier eligible, which is a t2.micro with 1 CPU and 1 Gb of memory as of this writing.\n\n\n\n\n\n\nServer sizing for the lab\n\n\n\nA t2.micro with 1 CPU and 1 Gb of memory is a very small server. For example, your laptop probably has at least 8 CPUs and 8 Gb of memory.\nIf all you’re doing is walking through the lab, it should be sufficient, but if you actually want to do any data science work, you’ll need a substantially larger server.\nIf you want to pick a server for actual data science work, there’s lots of advice on how to choose in Chaper 15.\n\n\n\n\n10.4.1.2.4 Keypair\nNext, you’ll need to make sure you have a keypair. A keypair is a special kind of SSH key that’s only valid for a particular server.\nIf you aren’t sure what that means, I’d recommend you check out Chapter 6.\nEven if you have a keypair you already use, I’d suggest creating a new one and naming it do4ds-lab-key. Download the pem version of your key.\nI’ll use that name throughout the lab, so you can just copy commands straight from this book if you use the same name.\nI’d recommend creating a directory for this lab, perhaps something like do4ds-lab and putting your keypair there. If you’re not going to do that, just make sure you keep track of where you downloaded it.\n\n\n10.4.1.2.5 Storage\nFor storage, you should bump it up to something more than 8 Gb. As of this writing, you can get 30 Gb under the free tier. I’d recommend at least 16 Gb, but feel free to go bigger if you wish.\n\n\n\n10.4.1.3 Step 3: Start your Server\nIf you followed these instructions, the summary on the right side should look something like this:\n\n\n\n\n\nClick Launch Instance. AWS is now creating a virtual server just for you.\nIf you go back to the EC2 page and click on Instances you can see your instance as it comes up. You may need to remove the filter for State: Running since it’ll take a few moments to be Running.\n\n\n10.4.1.4 Step 4: Grab the address of your server\nIf you click on the actual instance ID in blue, you can see all the details of your server.\nWait for a few moments for the instance state to transition to Running.\nOnce the instance is up, you’ll be able to see the instance ID and public IP addresses, which were auto-assigned.\nCopy the Public IPv4 DNS address , which starts with ec2- and ends with amazonaws.com. That little icon on the left of the address copies it.\n\n\n\n\n\n\nSet a Server Address Variable\n\n\n\nIn the rest of the labs in this book, I’m going to write the commands using the bash variable SERVER_ADDRESS. That means that if you create that variable, you’ll be able to just copy the commands out of the book.\nFor example, as I write this, my server has the address ec2-54-159-134-39.compute-1.amazonaws.com. So would set my server address variable with SERVER_ADDRESS=ec2-54-159-134-39.compute-1.amazonaws.com.\nIf you’re used to R or Python, where it’s best practice to put spaces around =, notice that assigning variables in bash requires no spaces around =.\n\n\n\n\n10.4.1.5 Step 5: Stop the Server\nWhenever you’re stopping for the day, you may want to suspend your server so you’re not paying for it overnight or using up your free tier hours. You can suspend an instance in the state it’s in so it can be restarted later.\nIf you’re storing a lot of data with your instance, it may not be free – but it is quite cheap. In the free tier, a suspended instance should be free for some time.\nWhenever you want to suspend your instance, go to the EC2 page for your server. Under the Instance State drop down in the upper right, choose Stop Instance.\nAfter a couple minutes the instance will stop. Before you come back to the next lab, you’ll need to start the instance back up so it’s ready to go.\n\n\n\n\n\n\nNote\n\n\n\nIf you stop your server, the server address will change and you’ll have to use the new one. In Chapter 13, we’ll get into getting a stable IP address and URL for the server.\n\n\nIf you want to completely delete the instance at any point, you can choose to Terminate Instance from that same Instance State dropdown.\n\n\n\n10.4.2 Step 6: Put the penguins data and model in S3\nAs discussed in Chapter 3, we’re going to want to put our data and our model somewhere other than on our local machine.\nWhile this data doesn’t get updated, you might want to be able to update the data and the model periodically.\nA bucket is a great place to store non-tabular data like a model. AWS’s bucket storage is called S3. You’ll probably find yourself using it a lot. It can also store flat files to be used by DuckDB.\nFor the model, {vetiver} interfaces with another package called {pins} which makes it easy to store data in a variety of backends, including an s3 bucket.\nFirst, you’ll need to create an S3 bucket in the AWS console. Give it a name that’s descriptive and memorable – it will also have to be unique. I named mine do4ds-lab. You’ll have to choose the AWS region where your bucket is located – take note of this.\nNow, let’s change our code to write to the S3 bucket we created. Vetiver makes this very easy. All you have to do to move the model into S3 is to change the line that creates the bucket in your code so instead of using a board_temp, it uses board_s3.\n\n\nmodel.qmd\n\nfrom vetiver import VetiverModel\nv = VetiverModel(model, model_name='penguin_model', prototype_data=X)\n```\n\n\nThat line will now become\n\n\nmodel.qmd\n\nfrom vetiver import VetiverAPI\napp = VetiverAPI(v, check_prototype = True)\n```\n\nNow, if you try this line in your code, it won’t work. Why? Because of authentication. The bucket we’re using isn’t public and AWS needs to know that we’re actually allowed to access it.\nIn this case, we’re going to use environment variables to give access to the S3 bucket. If you play around a little, you’ll discover that {pins} does authentication via the s3fs package, which can do authentication in several different ways. We’re going to use environment variables because they work nicely locally and from GitHub Actions.\nThe 3 environment variables are AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, and AWS_REGION. You can get the access key and secret access key from the AWS console.\nOnce you’ve done that, create a file in the directory where your project is called .env. In that file you’ll put the access keys, along with the AWS region where you put your bucket.\nIt’ll look something like this6\n\n\n.env\n\nAWS_ACCESS_KEY_ID=AJAASJKD88ALLKAIS8A\nAWS_SECRET_ACCESS_KEY=0JAJSduasdjkASDLISjkasd8AD78\nAWS_REGION=us-east-1\n\nNow, add a block to the code that loads in the environment variables.\n\n\nmodel.qmd\n\n\nmodel_board = board_folder(\"/data/model\", allow_pickle_read = True)\nvetiver_pin_write(model_board, v)\n\nIf these variables are in the environment, the call to board_s3 should just work locally.\nWe have one more step to make this work so that the model can also be written from GitHub actions. GitHub Actions needs to know how to access those environment variables too.\nSo in the Render and Publish step, we’re going to declare those variables as well as environment variables.\nOnce you’re done, that section of the publish.yml should look something like this.\n\n\n.github/workflows/publish.yml\n\non:\n  workflow_dispatch:\n  push:\n    branches: main\n\nname: Quarto Publish\n\njobs:\n  build-deploy:\n    runs-on: ubuntu-latest\n    permissions:\n      contents: write\n    steps:\n      - name: Check out repository\n        uses: actions/checkout@v2\n\n      - name: Set up Quarto\n        uses: quarto-dev/quarto-actions/setup@v2\n\n      - name: Install R\n        uses: r-lib/actions/setup-r@v2\n        with:\n          r-version: '4.2.0'\n          use-public-rspm: true\n\n      - name: Setup renv and install packages\n        uses: r-lib/actions/setup-renv@v2\n        with:\n          cache-version: 1\n        env:\n          RENV_CONFIG_REPOS_OVERRIDE: https://packagemanager.rstudio.com/all/latest\n\n      - name: Install Python and Dependencies\n        uses: actions/setup-python@v4\n        with:\n          python-version: '3.10'\n          cache: 'pip'\n      - run: pip install jupyter\n      - run: pip install -r requirements.txt\n\n      - name: Render and Publish\n        uses: quarto-dev/quarto-actions/publish@v2\n        with:\n          target: gh-pages\n        env:\n          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}\n          AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }}\n          AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }}\n          AWS_REGION: us-east-1\n\nNow, unlike the GITHUB_TOKEN secret, which GitHub Actions automatically provides to itself, we’ll have to provide these secrets to the GitHub interface.As of this writing, you can provide them under the repository settings, secrets and variables, actions.\nThe other thing you’ll need to do is to update the API to use the S3 pin. Luckily, this is very easy. Just update the script you used to build your Dockerfile so it pulls from the pin in the S3 bucket rather than the local folder.\nNow, the script to build the Dockerfile looks like this:\n---\ntitle: \"Prepare Dockerfile\"\nformat:\n  html:\n    code-fold: true\n---\n\n## Load Environment\n\n```{python}\nfrom dotenv import load_dotenv\n\nload_dotenv()\n\nfrom pins import board_s3\nfrom vetiver import vetiver_prepare_docker\n\nboard = board_s3(\"do4ds-lab\", allow_pickle_read=True)\nvetiver_prepare_docker(board, \"penguin_model\")\n```\nThere are a variety of ways to put the data into S3 as well. I would recommend doing this if you are going to be working with data that will update. In fact, DuckDB allows you to directly interface with parquet files on S3."
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+    "text": "10.7 Comprehension Questions\n\nWhat are two different ways to install Linux applications and what are commands to do so?\nWhat does it mean to daemonize a Linux application? What programs and commands are used to do so?\nHow do you know if you’ve opened nano or vim? How would you exit them if you didn’t mean to?\nWhat are 4 commands to read text files?\nHow would you create a file called secrets.txt, open it with vim, write something in, close and save it, and make it so that only you can read it?"
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+    "text": "10.8 Lab: Installing Applications\nAs we’ve started to administer our server, we’ve mostly been doing very generic server administration tasks. Now let’s set up the applications we need to run a data science workbench and get our API and Shiny app set up for using in our portfolio.\n\n10.8.1 Step 1: Install Python\nLet’s start by installing a data science version of Python so we’re not using the system Python for data science purposes.\nIf you want just one version of Python, you can apt-get install a specific version. As of this writing, Python 3.10 is a relatively new version of Python, so we’ll install that one with\n\n\nTerminal\n\nsudo apt-get install python3.10-venv\n\nOnce you’ve installed Python, you can check that you’ve got the right version by running\n\n\nTerminal\n\npython3 --version\n\nThis method, using apt-get, is great when you just want one version of Python. But if you want multiple versions sitting side by side, you’ll need to do something else. I recommend installing using the instructions on the Posit website, which will involve downloading and installing from .deb files.\n\n\n10.8.2 Step 2: Install R\nSince we’re using Ubuntu, we can use rig. There are good instructions on downloading rig and using it to install R on the rlib/rig GitHub repo. Use those instructions to install the current R release on your server.\nOnce you’ve installed R on your server, you can check that it’s running by just typing R into the command line. If that works, you’re good to move on to the next step. If not, you’ll need to make sure R got onto the path.\n\n\n10.8.3 Step 3: Install JupyerHub + JupyterLab\nJupyterHub and JupyterLab are Python programs, so we’re going to run them from within a Python virtual environment. I’d recommend putting that virtual environment inside /opt/jupyterhub.\nHere are the commands to create and activate a jupyterhub virtual environment in /opt/jupyterhub:\n\n\nTerminal\n\nsudo python3 -m venv /opt/jupyterhub\nsource /opt/jupyterhub/bin/activate\n\nNow we’re going to actually get JupyterHub up and running inside the virtual environment we just created. JupyterHub produces docs that you can use to get up and running very quickly. If you have to stop for any reason, make sure to come back, assume sudo, and start the JupyterHub virtual environment we created.\nNote that because we’re working inside a virtual environment, you may have to use the jupyterhub-singleuser version of the binary.\n\n\n10.8.4 Step 4: Daemonize JupyterHub\nBecause JupyterHub is a Python process, not a system process, it won’t automatically get daemonized, so we’ll have to do it manually.\nWe don’t need it right now, but it’ll be easier to manage JupyterHub later on from a config file that’s in /etc/jupyterhub. In order to do so, activate the jupyterhub virtual environment, create a default JupyterHub config (Google for the command), and move it into /etc/jupyterhub/jupyterhub_config.py.\nNow let’s move on to daemonizing JupyterHub. To start, kill the existing JupyterHub process (consult the cheatsheet in Appendix C if you need help). Since JupyterHub wasn’t automatically daemonized, you’ll have to manually create the systemd file.\nHere’s the file I created in /etc/systemd/system/jupyterhub.service.\n\n\n/etc/systemd/system/jupyterhub.service\n\n[Unit]\nDescription=Jupyterhub\nAfter=syslog.target network.target\n\n[Service]\nUser=root\nEnvironment=\"PATH=/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/opt/jupyterhub/bin\"\nExecStart=/opt/jupyterhub/bin/jupyterhub -f /etc/jupyterhub/jupyterhub_config.py\n\n[Install]\nWantedBy=multi-user.target\n\nThere are two things here worth noticing. The first is the Environment line that adds /opt/jupyterhub/bin to the path – that’s where our virtual environment is.\nThe second is ExecStart line, which provides is the startup command and specifies that JupyterHub should use the config we just created, specified by -f /etc/jupyterhub/jupyterhub_config.py.\nNow, you’ll need to use systemctl to reload the daemon, start JupyterHub, and enable it.\n\n\n10.8.5 Step 5: Install RStudio Server\nYou can find the commands to install RStudio server on the Posit website. Make sure to pick the version that matches your operating system. Since you’ve already installed R, you can skip down to the “Install RStudio Server” step.\nUnlike JupyterHub, RStudio Server does daemonize itself right out of the box, so you can check and control the status with systemctl without any further work.\n\n\n10.8.6 Step 6: Run the penguin API from Docker\nFirst, you’ll have to make sure that Docker itself is available on the system. It can be installed from apt using apt-get install docker.io. You may need to adopt sudo privileges to do so.\nOnce Docker is installed, getting the API running is almost trivially easy using the command we used back in Chapter 6 to run our container.\n\n\nTerminal\n\nsudo docker run --rm -d \\\n  -p 8080:8080 \\\n  --name penguin-model \\\n  alexkgold/penguin-model\n\nThe one change you might note is that I’ve changed the port on the server to be 8080, since JupyterHub runs on 8000 by default.\nOnce it’s up, you can check that it’s running with docker ps.\n\n\n10.8.7 Step 7: Put up the Shiny app\nWe’re going to use Shiny Server to host our Shiny app on the server. Start by moving the app code to the server. I put mine in /home/test-user/do4ds-lab/app by cloning the Git repo.\nAfter that, you’ll need to:\n\nOpen R or Python and rebuild the package library with {renv} or {venv}.\nInstall Shiny Server using the instructions from the Admin Guide.\n\nNote that you can skip steps to install R and/or Python, as well as the {shiny} package as we’ve already done that.\n\nEdit Shiny Server’s configuration file to run the right app.\nStart and enable Shiny Server with systemctl.\n\n\n\n10.8.8 Lab Extensions\nThere are a few things you might want to consider before moving into the next chapter, where we’ll start working on giving this server a stable public URL.\nFirst, we haven’t daemonized the API. Feel free to try Docker Compose or setting a restart policy for the container.\nSecond, neither the API nor the Shiny app will automatically update when we make changes to them. You might want to set up a GitHub Action to do so. For Shiny Server, you’ll need to push the updates to the server and then restart Shiny Server. For the API, you’d need to configure a GitHub action to rebuild the container and push it to a registry. You’d then need to tell Docker on the server to re-pull and restart the container.\nFinally, there’s no authentication in front of our API. Now, the API has pretty limited functionality, so that’s not a huge worry. But if you had an API with more functionality that might be a problem. Additionally, someone could try to flood your API with requests to make it unusable. The most common way to solve this is to buy a product that hosts the API for you or to put an authenticating proxy in front of the API (Google for instructions for NGINX if you want to try it)."
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-    "text": "https://www.visualcapitalist.com/aws-powering-the-internet-and-amazons-profits/↩︎\nhttps://a16z.com/2021/05/27/cost-of-cloud-paradox-market-cap-cloud-lifecycle-scale-growth-repatriation-optimization/↩︎\nBy temporary workloads, I mean for example the need for a very large server to run a particular machine learning model. This is not the autoscaling failure case, because you’re not expecting this server to turn itself on and off. Instead, you’d stand it up – run it for a few hours, days, or weeks while you’re using it, and then manually turn it off. This is super easy with a cloud server and very difficult in an on-prem world.↩︎\nThere are also some wild services that do specific things, like let you rent you satellite ground station infrastructure or do Internet of Things (IoT) workloads. Those services are really cool, but so far outside the scope of this book that I’m fine with talking like they don’t exist.↩︎\nThere are many others. These are just the most popular I’ve seen for data science use cases.↩︎\nNot my real access key or secret access key. Never share them.↩︎"
+    "text": "vi is the original fullscreen text editor for Linux. vim is its successor (vim stands for vi improved). I’m not going to worry about the distinction.↩︎"
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-    "text": "11.1 Linux is an operating system with a long history\nA computer’s operating system (OS) defines how applications – like Microsoft Word, RStudio, and Minecraft – interact with the underlying hardware to actually do computation. OSes define how files are stored and accessed, how applications are installed and can connect to networks, and more.\nThese days, basically all computers run on one of a few different operating systems – Windows, MacOS, or Linux for laptops and desktops; Windows or Linux for servers, Android (a flavor of Linux) or iOS for phones and tablets, and Linux for other kinds of embedded systems (like ATMs and the chips in your car).\nWhen you stand up a server, you’re going to be choosing from one of a few versions of Linux. If you’re unfamiliar with Linux, the number of choices can seem overwhelming, so here’s a quick primer on the history of operating systems. Hopefully it’ll help it all make sense.\nBefore the early 1970s, the market for computer hardware and software looked nothing like it does now. Computers released in that era had extremely tight linking between hardware and software. There were no standard interfaces between hardware and software, so each hardware manufacturer also had to release the software to use with their machine.\nIn the early 1970s, Bell Labs released Unix – the first operating system.\nOnce there was an operating system, the computer market started looking a lot more familiar to 2020s eyes. Hardware manufacturers would build machines that ran Unix and software companies could write applications that ran on Unix. The fact that those applications would run on any Unix machine was a game-changer.\nIn the 1980s, programmers wanted to be able to work with Unix themselves, but didn’t necessarily want to pay Bell Labs for Unix, so they started writing Unix-like operating systems. Unix-like OSes or Unix clones behaved just like Unix, but didn’t actually include any code from Unix itself.1\nIn 1991, Linus Torvalds – then a 21 year-old Finnish grad student – released Linux, an open source Unix clone via a amusingly nonchalant newsgroup posting.2\nSince then, Linux has seen tremendous adoption. A large majority of the world’s servers run on Linux.3 Along with most of the world’s servers, almost all of the world’s embedded computers – in ATMs, cars and planes, TVs, and most other gadgets and gizmos – run on Linux. If you have an Android phone or a Chromebook – that’s Linux. Basically all of the world’s supercomputers use Linux.\nAs you might imagine, running Linux in so many different places has necessitated the creation of many different kinds of Linux. For example, a full-featured Linux server is going to require a very different operating system than the barebones operating system running on an ATM with extremely modest computational power.\nThese different versions are called distributions (distros for short) of Linux. They have a variety of technical attributes and also different licensing models.\nSome versions of Linux, like Ubuntu, are completely open source. Others, like Red Hat Enterprise Linux (RHEL), are paid. Most paid Linux OSes have closely-related free and open source versions – like CentOS and Fedora for RHEL.4\nMany organizations have a standard Linux distro they use – most often RHEL/CentOS or Ubuntu. Increasingly, organizations deploying in AWS are using Amazon Linux, which is independently maintained by Amazon but was originally a RHEL derivative. There are also some organizations that use SUSE (pronunced soo-suh), which has both open source and enterprise versions."
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+    "section": "11.1 The briefest intro to computational theory",
+    "text": "11.1 The briefest intro to computational theory\nYou’re probably aware that everything you’ve ever seen on a computer – from this book to your work in R or Python, your favorite internet cat videos, and Minecraft – it’s just 1s and 0s.\nBut the 1s and 0s aren’t actually the interesting part. The interesting part is that these 1s and 0s don’t directly represent a cat or a book. Instead, the 1s and 0s are binary representations of integers (whole numbers) and the only thing the computer does is add these integers.1\nOnce they’ve been added, they’re reinterpreted back into something meaningful. But the bottom line is that every bit of input your computer gets is turned into an addition problem, processed, and the results are reverted back into something we interpret as meaningful.\nSo, a computer is really just a factory that does addition problems. So as you’re thinking about how to size and scale a server, you’re really thinking about how to optimally design your factory.\nThere are three essential resources a server has – compute, memory, and storage. In this chapter, I’m going to share some mental models I find helpful about how to think of each and some recommendations for getting a data science server."
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-    "text": "11.2 A tiny intro to Linux administration\nWe’ll get into how to administer a Linux server just below, but before we get there, let’s introduce what you’ll be doing as a Linux server admin. There are three main things you’ll manage as a Linux server admin:\n\nSystem resources Each server has a certain amount of resources available. In particular, you’ve got CPU, RAM, and storage. Keeping track of how much you’ve got of these things and how they’re being used – and making sure no one is gobbling up all the resources – is an important part of system administration.\nNetworking Your server is only valuable if you and others can connect to it, so managing how your server can connect to the environment around it is an important part of Linux administration.\nPermissions Servers generally exist to allow a number of people to access the same machine. Creating users and groups – and managing what they’re allowed to do – is a huge part of server administration.\nApplications Generally you want to do something with your server, so being able to interact with applications that are running, debug issues, and fix things that aren’t going well is an essential Linux admin skill.\n\nWhen you log into a Linux server, you’ll be interacting exclusively via the command line, so all of the commands in this chapter are going to be terminal commands. If you haven’t yet figured out how to open the terminal on your laptop (and gotten it themed and customized so it’s perfect), I’d advise going back to Chapter 6 to get it all configured.5\n\n\n\n\n\n\nWindows, Mac, and Linux\n\n\n\nMacOS is based on BSD, a Unix clone, so any terminal commands you’ve used before on Mac will be very similar to Linux commands.\nWindows, on the other hand, is basically the only popular operating system that isn’t a Unix clone. Over time, the Windows command line has gotten more Unix-like, so the differences aren’t as big as they used to be, but there will be some differences in the exact commands that work on Windows vs Linux.\nThe most obvious difference is the types of slashes used in file paths. Unix-like systems use forward slashes / to denote file hierarchies, while Windows historically uses back slashes \\. These days Windows deals just fine with either."
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+    "text": "11.2 How computers compute\nThe addition assembly line itself – where the work actually gets done – is referred to as compute. It’s where 2+2 gets turned into 4, and where 345619912 + 182347910 gets turned into 527967822.\nThe main compute that all computers have is the central processing unit (CPU), which completes addition problems in a core.\nThe first attribute that determines the speed of compute is the number of cores, which is like the number of conveyor belts in the factory.\nThese days, most consumer-grade laptops have between 4 and 16 physical cores. Many have software capabilities that effectively double that number, so they can do between 4 and 32 simultaneous addition problems.\nThe second speed-determining attribute is how quickly a single addition problem gets completed by a single core. This is called the single core clock speed. You can think of this as how fast the conveyor belt moves.\nClock speeds are measured in operations per second or hertz (hz). The cores in your laptop probably max out between two and five gigahertz (GHz), which means between 2 billion and 5 billion operations per second.\nFor decades, many of the innovations in computing were coming from increases in single core clock speed, but those have fallen off a lot in the last few decades. The clock speeds of consumer-grade chips increased by approximately 10x during the 90s, by 2-3x in the 2000s, and somewhere between not at all and 1.5x in the 2010s.\nBut computers have continued getting a lot faster even as the increase in clock speeds has slowed. The increase has mostly come from increases in the number of cores, better software usage of parallelization, and faster loading and unloading of the CPU (called the bus)."
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-    "text": "11.3 The filesystem\nAll of the information available to a computer is indexed by its filesystem. The filesystem is made up of directories or folders, which are containers for other directories and files.\nOn your laptop, you’re probably used to browsing the filesystem with your mouse. On your phone, the filesystem is completely obscured by apps, but it’s there.\nWhen using the command line, the only way to traverse the filesystem is with written commands. Having a good mental model for what the filesystem looks like is, therefore, really important.\nOn Mac or Linux, the entire filesystem is a tree (or perhaps an upside-down tree). Every directory is contained in by a parent directory, and may contain one or more children or sub-directories. The root directory, / is the base of the tree and is its own parent. A / in between two directories means that it’s a sub-directory.\n\nEvery directory is a sub-directory of / or a sub-directory of a sub-directory of / or…you get the picture. So the /home/alex file path defines a particular location, which is the alex sub-directory of /home, which is a sub-directory of the root directory, /."
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+    "text": "11.3 Recommendation 1: Fewer, faster CPU cores\nR and Python are single-threaded. This means that unless you’re using special libraries for parallel processing, you’ll end up red-lining a single CPU core while the others just look on in silence.\nTherefore for most R and Python work, single core clock speed matters more than the number of cores, and fewer, faster cores are usually preferable to many slower\nYou’re probably not used to thinking about this tradeoff from buying a laptop or phone. The reality is that modern CPUs are pretty darn good and you should just buy the one that fits your budget.\nIf you’re standing up a server, you often do have an explicit choice between more slower cores and fewer faster ones, determined by the instance family.\nIf you’re running a multi-user server, the number of cores you need can be hard to estimate. If you’re doing non-ML tasks like counts and dashboarding or relatively light-duty machine learning I might advise the following:\n\\[\n\\text{n cores} = \\text{1 core per user} + 1\n\\]\nThe spare core is for the server to do its own operations apart from the data science usage. On the other hand, if you’re doing heavy-duty machine learning or parallelizing jobs across the CPU, you may need more cores than this rule of thumb."
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-    "text": "11.4 Windows folders and files\nEach Linux computer has exactly one filesystem. On Windows you can have multiple filesystems on the same machine, one for each physical or logical disk. You’re probably familiar with C: as your main filesystem. Your machine may also have a D: drive.\nIn Linux, network shares are mounted somewhere on the filesystem, often at /mnt, but the fact that they’re on separate drives is obscured from the user. On Windows, network share drives are mounted as a separate filesystem, often at M: or N: or P:.\nOne other difference is that Windows uses \\ to separate file path elements rather than /. This used to be a big deal, but newer versions of Windows accept file paths using /."
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+    "text": "11.4 How memory works\nYour computer’s random access memory (RAM) is its short term storage. You can think of RAM like the stock that’s sitting out on the factory floor ready to go right on an assembly line and the completed work that’s ready to be shipped.\nRAM is very fast to for your computer to access, so you can read and write to it very quickly. The downside is that it’s temporary. When your computer turns off, the RAM gets wiped.2\n\n\n\n\n\n\nNote\n\n\n\nMemory and storage are measured in bytes with metric prefixes.\nCommon sizes for memory these days are in gigabytes (billion bytes) and terrabytes (trillion bytes). Some enterprise data stores run on the scales of thousands of terrabytes (pettabytes) or even thousands of pettabytes (yottabytes).\n\n\nModern consumer-grade laptops come with somewhere between 4 and 16 Gb of memory."
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-    "text": "11.5 Managing who can do what\nWhenever you’re doing something in Linux, you’re doing that thing as a particular user.\nOn any Unix-like system, you can check your active user at any time with the whoami command. For example, here’s what it looks like on my MacBook.\n❯ whoami                                                       \nalexkgold\nwhoami returns the username of my user.\nUsernames have to be unique on the system – but they’re not the true identifier for a Linux user. A user is uniquely (and permanently) identified by their user id (uid). All other attributes (including username, password, home directory, groups, and more) are malleable, but uid is forever.\nMany of the users on a Linux server correspond to actual humans, but there are more users than that. Most programs that run on a Linux server run as a service account that represent the set of permissions allowed to that program.\nFor example, installing RStudio Server will create a user with username rstudio-server. Then, when rstudio-server goes to do something – start an R session for example – it will do so as rstudio-server.\n\n\n\n\n\n\nA few details on UIDs\n\n\n\nuids are just numbers from 0 to over 2,000,000,000. uids are assigned by the system at the time the user is created. You should probably keep uids below 2,000,000 or so if you are ever assigning uids manually – some programs can’t deal with uids any bigger.\n10,000 is the the lowest uid that’s available for use by a user account. Everything below that is reserved for predefined system accounts or application accounts.\n\n\nIn addition to users, Linux has a notion of groups. A group is a collection of users. Each user has exactly one primary group and can be a member of secondary groups.6 By default, each user’s primary group is the same as their username.\nLike a user has a uid a group has a gid. User gids start at 100.\nYou can see a user’s username, uid, groups, and gid with the id command.\n ❯ id                                                                \nuid=501(alexkgold) gid=20(staff) groups=20(staff),12(everyone),61(localaccounts),79(_appserverusr),80(admin),81(_appserveradm),98(_lpadmin),701(com.apple.sharepoint.group.1),33(_appstore),100(_lpoperator),204(_developer),250(_analyticsusers),395(com.apple.access_ftp),398(com.apple.access_screensharing),400(com.apple.access_remote_ae)\nOn my laptop, I’m a member of a number of different groups.\nThere’s one extra special user – called the admin, root, sudo, or super user. They get the ultra-cool uid 0. That user has permission to do anything on the system. You almost never want to actually log in as the root user. Instead, you make users and add them to the admin or sudo group so that they have the ability to temporarily assume those admin powers.\nThe easiest way to make users is with the useradd command. Once you have a user, you may need to change the password, which you can do at any time with the passwd command. Both useradd and passwd start interactive prompts, so you don’t need to do much more than run those commands.\n\n\n\n\n\n\n\nCommand\nWhat it does\n\n\n\n\nsu &lt;username&gt;\nChange to be a different user.\n\n\nwhoami\nGet username of current user.\n\n\nid\nGet full user + group info on current user.\n\n\npasswd\nChange password.\n\n\nuseradd\nAdd a new user.\n\n\n\n\n11.5.1 File Permissions\nEvery object in Linux is just a file. Every log – file. Every picture – file. Every program – file. Every system setting – file.\nSo determining whether a user can take a particular action is really a question of whether they have the right permissions on a particular file.\n\n\n\n\n\n\nNote\n\n\n\nThe question of who’s allowed to do what – authorization – is an extremely deep one. There’s a chapter all about authorization, how it differs from authentication, and the different ways your IT/Admins might want to manage it later in the book.\nThis is just going to be a high-level overview of basic Linux authorization.\n\n\nThere are three permissions you can have: read, write, and execute. Read means you’re allowed to see the contents of a file, write means you can save a changed version of a file, and execute means you’re allowed to run the file as a program.\nThe execute permission really only makes sense for some kinds of files - what would it mean to execute a csv file? But Linux doesn’t care – you can assign any combination of these three permissions for any file.\nHow are these permissions assigned? Every file has an owner and an owning group.\nSo you can think of permissions in Linux as being assigned in a 3x3 grid. The owner, the owning group, and everyone else can have permissions to read, write, or execute the file.\nTODO: change to graphic\n\n\n\n\nOwner\nGroup\nEveryone Else\n\n\n\n\nRead\n✅/❌\n✅/❌\n✅/❌\n\n\nWrite\n✅/❌\n✅/❌\n✅/❌\n\n\nExecute\n✅/❌\n✅/❌\n✅/❌\n\n\n\nTo understand better, let’s look at the permissions on an actual file.\nRunning ls -l on a directory gives you the list of files in that directory, along with their permissions. The first few columns of the list give you the full set of file permissions – though they can be a little tricky to read.\nSo, for example, here’s a few lines of the output of running ls -l on a python project I have.\n❯ ls -l                                                           \n-rw-r--r--  1 alexkgold  staff     28 Oct 30 11:05 config.py\n-rw-r--r--  1 alexkgold  staff   2330 May  8  2017 credentials.json\n-rw-r--r--  1 alexkgold  staff   1083 May  8  2017 main.py\ndrwxr-xr-x 33 alexkgold  staff   1056 May 24 13:08 tests\nThis readout has the file permissions (a series of ten characters), followed by a number7, then the file’s owner, and the file’s group. Let’s learn how to read these.\nThe file’s owner and group are the easiest to understand. In this case, I alexkgold own all the files, and the group of all the files is staff.\nThe ten-character file permissions are relative to that user and group.\nThe first character indicates the type of file: - for normal and d for a directory.\nThe next nine characters are indicators for the three permissions – r for read, w for write, and x for execute (or - for in place of any of those for not) – first for the user, then for the group, then for any other user on the system.\nSo, for example, my config.py file with permissions of rw-r-r-- indicates the user (alexkgold) can read and write the file, and everyone else – including in the file’s group staff – has read-only permission.\nIn the course of administering a server, you will probably need to change a file’s permissions. You can do so using the chmod command.\nFor chmod, permissions are indicated with only three numbers – one for the user, one for the group, and one for everyone else. The way this works is pretty clever – you just sum up the permissions as follows: 4 for read, 2 for write, and 1 for execute. You can check for yourself, but any set of permissions can be uniquely identified by a number between 1 and 7.8\nSo chmod 765 &lt;filename&gt; would give the user full permissions (4 + 2 + 1), read and write (4 + 2) to the group, and read and execute (4 + 1) to everyone else. This would be a strange set of permissions to give a file, but it’s a perfectly valid chmod command.\n\n\n\n\n\n\nNote\n\n\n\nIf you spend any time administering a Linux server, you almost certainly will at some point find yourself running into a problem and applying chmod 777 out of frustration to rule out a permissions issue.\nI can’t in good faith tell you not to do this – we’ve all been there. But if it’s something important, be sure you change it back once you’re finished figuring out what’s going on.\n\n\nIn some cases you might actually want to change the owner or group of a file. You can change users or groups with either names or ids. You can do so using the chown command. If you’re changing the group, the group name gets prefixed with a colon.\nIn some cases, you might not be the correct user to take a particular action. You might not want to change the file permissions, but instead to change who you are. In that case, you can switch users with the su command.\nSome actions are also reserved for the admin user. For example, let’s take a look at this configuration file:\n ❯ ls -l /etc/config/my-config                      \n-rw-r--r--  1 root  system  4954 Dec  2 06:37 config.conf\nAs you can see, all users can read this file to check the configuration settings. But this file is owned by root, and only the owner has write permissions. So I could run cat config.conf to see it. Or I could go into it with vim config.conf, but I’d find myself stuck if I wanted to make changes.\nSo if I want to change this configuration file, I’d need to temporarily assume my root powers to make changes. Instead of switching to be the root user, I would run sudo vim config.conf and open the file for editing with root permissions.\n\n\n\n\n\n\n\n\nCommand\nWhat it does\nHelpful options + notes\n\n\n\n\nc h m o d &lt; p ermissions&gt; &lt;file&gt;\nModifies permissions on a file.\nNumber indicates permissions for user, group, others: add 4 for read, 2 for write, 1 for execute, 0 for nothing.\n\n\nc h o w n &lt; user/group&gt; &lt;file&gt;\nChange the owner of a file.\nCan be used for user or group, e.g. :my-group.\n\n\nsu &lt;username&gt;\nChange active user.\n\n\n\nsudo &lt;command&gt;\nAdopt super user permissions for the following command."
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+    "text": "11.5 Recommendation 2: Get as much RAM as feasible\nIn most cases, R and Python have to load all of your data into memory. Thus, the size of the data you can use is limited to the size of your machine’s RAM.\nMost other limits of your machine will just result in things being slower than you’d really want, but trying to load too much data into memory will result in a session crash.\n\n\n\n\n\n\nNote\n\n\n\nIf you’re running into this limitation, go back and think about your project architecture as discussed in Chapter 2. Maybe you can load less data into memory.\n\n\nBecause your computer needs memory for things other than R and Python and because you’ll often be doing transformations that temporarily increase the size of your data, you need more memory than your largest data set.\nIn general, you’ll always want more RAM, but a pretty good rule of thumb is that you’ll be happy if:\n\\[\\text{Amount of RAM} \\ge 3 * \\text{max amount of data}\\]\nIf you’re thinking about running a multi-user server, you’ll need to take a step back to think about how many concurrent users you expect and how much data you expect each one to load."
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-    "text": "11.6 Installing Stuff\nThere are several different ways to install programs for Linux, and you’ll see a few of them throughout this book.\nJust as CRAN and PyPI are repositories for R and Python packages, Linux distros also have their own repositories. For Ubuntu, the apt command is used for accessing and installing .deb files from the Ubuntu repositories. For CentOS and RedHat, the yum command is used for installing .rpm files.\n\n\n\n\n\n\nNote\n\n\n\nThe examples below are all for Ubuntu, since that’s what we use in the lab for this book. Conceptually, using yum is very similar, though the exact commands differ somewhat.\n\n\nWhen you’re installing packages in Ubuntu, you’ll often see commands prefixed with apt-get update && apt-get upgrade y. This command makes your machine update the list of available packages it knows about on the server and upgrade everything to the latest version.\nPackages are installed with apt-get install &lt;package&gt;. Depending on which user you are, you may need to prefix the command with sudo.\nYou can also install packages that aren’t from the central package repository. Doing that will generally involve downloading a file directly from a URL – usually with wget and then installing it from the file you’ve downloaded – often with the gdebi command.\n\n\n\n\n\n\n\nCommand\nWhat it does\n\n\n\n\na p t - g e t update  && apt-get upgrade y\nFetch and install upgrades to system packages\n\n\napt-get install &lt;package&gt;\nInstall a system package.\n\n\nwget\nDownload a file from a URL.\n\n\ngdebi\nInstall local .deb file.\n\n\n\n\n11.6.1 Managing R and Python\nAs the admin of a data science server, managing R and Python installations is a central task you’ll have to do, as well as installing software on top of that like RStudio Server, JupyterHub, and/or Shiny Server. While R and Python are both open source data science languages, the way you’ll have to administer them are pretty different.\nPeople pretty much only ever install R to do data science. In contrast, Python is one of the world’s most popular programming languages for general purpose computing. Contrary to what you might think, this actually makes configuring Python harder than configuring R.\nThe reason is that your system comes with a version of Python installed, but we don’t want to use that version. Given the centrality of that version to normal server operations, we want to leave it alone. It turns out that installing one or more other versions of Python and then ignoring the system version of Python isn’t totally trivial to do. Then we’re going to want to create a standalone virtual environment that’s just for running JupyterHub so it doesn’t get messed up later.\nRStudio and R are system libraries. So when RStudio runs, it calls and owns the R process that you’ll use inside RStudio Server. In contrast, JupyterHub and JupyterLab are Python programs, so we install them inside a Python installation.\nTODO: diagram of relationships of system python, DS python, Jupyter Python."
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+    "text": "11.6 Understanding storage\nStorage, or hard disk/drive, is your computer’s place to put things for the long-term. It’s where applications are installed, and where you save things you want to keep.\nRelative to the RAM that’s right next to the factory floor, your computer’s storage is like the warehouse in the next building over. It’s slower to get things from storage than RAM, but it’s also permanent once its stored there.\nUp until a few years ago, storage was much slower than RAM. Those drives, called HDD drives, had a bunch of spinning magnetic disks with magnetized read/write heads that move among the disks to save and read data.\nWhile they spin very fast – 5,400 and 7,200 RPM are common speeds – there were still physical moving parts, and reading and writing data was very slow by computational standards.\nIn the last few years, solid-state drives (SSDs) have become more-or-less standard in laptops. SSDs, which are collections of flash memory chips with no moving parts are up to 15x faster than HDDs."
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-    "text": "11.7 Debugging and troubleshooting\nThere are three main resources you’ll need to manage as the server admin – CPU, RAM, and storage space. There’s more on all three of these and how to make sure you’ve got enough in Chapter 15.\nFor now, we’re just going to go over how to check how much you’ve got, how much you’re using, and getting rid of stuff that’s misbehaving.\n\n11.7.1 Storage\nA common culprit for weird server behavior is running out of storage space. There are two handy commands for monitoring the amount of storage you’ve got – du and df. These commands are almost always used with the -h flag to put file sizes in human-readable formats.\ndu, short for disk usage, gives you the size of individual files inside a directory. This can be helpful for finding your largest files or directories if you think you might need to clean up things. It’s particularly useful in combination with the sort command.\nFor example, here’s the result of running du on the chapters directory where the text files for this book live.\n ❯ du -h chapters | sort -h                                      \n 44K    chapters/sec2/images-servers\n124K    chapters/sec3/images-scaling\n156K    chapters/sec2/images\n428K    chapters/sec2/images-traffic\n656K    chapters/sec1/images-code-promotion\n664K    chapters/sec1/images-docker\n1.9M    chapters/sec1/images-repro\n3.4M    chapters/sec1\n3.9M    chapters/sec3/images-auth\n4.1M    chapters/sec3\n4.5M    chapters/sec2/images-networking\n5.3M    chapters/sec2\n 13M    chapters\nSo if I were thinking about cleaning up this directory, I could see that my images-networking directory in sec2 is the biggest single bottom-level directory. If you find yourself needing to find big files on your Linux server, it’s worth spending some time with the help pages for du. There are lots of really useful options.\ndu is useful for identifying large files and directories on a server. df, for disk free, is useful for diagnosing issues that might be a problem for a directory. If you’re struggling to write into a directory – perhaps getting out of space errors, df can help you diagnose.\ndf answers the question – given a file or directory, what device is it mounted on and how full is that device?\nSo here’s the result of running the df command on that same chapters directory.\n ❯ df -h chapters                                                    \nFilesystem     Size   Used  Avail Capacity iused      ifree %iused  Mounted on\n/dev/disk3s5  926Gi  163Gi  750Gi    18% 1205880 7863468480    0%   /System/Volumes/Data\nSo you can see that the chapters folder lives on a disk called /dev/disk3s5 that’s a little less than 1Tb and is 18% full – no problem. On a server this can be really useful to know, because it’s quite easy to switch a disk out for a bigger one in the same spot.\n\n\n\n\n\n\n\n\nC o mmand\nWhat it does\nH e lpful o p tions\n\n\n\n\ndu\nCheck size of f iles.\nMost l ikely to be used d  u  - h &lt;d  i r &gt;  | s o r t -h [^3 -2-l in u x - a d m i n-9]\nAlso u seful to c o mbine with h ead.\n\n\ndf\nCheck s t orage space on d e vice.\n-h\n\n\n\n\n\n11.7.2 Monitoring processes\nEvery program your computer runs is a process. For example, when you type python on the command line to open a REPL, that’s a process. Running more complicated programs usually involves more than one process.\nFor example, running RStudio involves (at minimum) one process for the IDE itself and one for the R session that it uses in the background. The relationships between these different processes is mostly hidden from you – the end user.\nAs a server admin, finding runaway processes, killing them, and figuring out how to prevent the them from happening again is a pretty common task. Runaway processes usually misbehave by using up the entire CPU, filling up the entire machine’s RAM.\nLike users and groups have ids, each process has a numeric process id (pid). Each process also has an owner – this can be either a service account or a real user. If you’ve got a rogue process, the pattern is to try to find the process and make note of its pid. Then you can immediately end the process by pid with the kill command.\nSo, how do you find a troublesome process?\nThe top command is a good first stop. top shows the top CPU-consuming processes in real time. Here’s the top output from my machine as I write this sentence.\nPID    COMMAND      %CPU TIME     #TH    #WQ  #PORT MEM    PURG   CMPRS PGRP\n0      kernel_task  16.1 03:56:53 530/10 0    0     2272K  0B     0B    0\n16329  WindowServer 16.0 01:53:20 23     6    3717  941M-  16M+   124M  16329\n24484  iTerm2       11.3 00:38.20 5      2    266-  71M-   128K   18M-  24484\n29519  top          9.7  00:04.30 1/1    0    36    9729K  0B     0B    29519\n16795  Magnet       3.1  00:39.16 3      1    206   82M    0B     39M   16795\n16934  Arc          1.8  18:18.49 45     6    938   310M   144K   61M   16934\n16456  Messages     1.7  06:58.27 4      1    603   138M   2752K  63M   16456\n1      launchd      1.7  13:41.03 4/1    3/1  3394+ 29M    0B     6080K 1\n573    diagnosticd  1.4  04:31.97 3      2    49    2417K  0B     816K  573\n16459  zoom.us      1.3  66:38.37 30     3    2148  214M   384K   125M  16459\n16575  UniversalCon 1.3  01:15.89 2      1    131   12M    0B     2704K 16575\nIn most instances, the first three columns are the most useful. You’ve got the name of the command and how much CPU they’re using. Right now, nothing is using very much CPU. If I were to find something concerning – perhaps an R process that is using 500% of CPU – I would want to take notice of its pid to kill it with kill.\n\n\n\n\n\n\nSo much CPU?\n\n\n\nFor top (and most other commands), CPU is expressed as a percent of single core availability. So, on a modern machine (with multiple cores), it’s very common to see CPU totals well over 100%. Seeing a single process using over 100% of CPU is rarer.\n\n\nThe top command takes over your whole terminal. You can exit with Ctrl + c.\nAnother useful command for finding runaway processes is ps aux.9 It lists all processes currently running on the system, along with how much CPU and RAM they’re using. You can sort the output with the --sort flag and specify sorting by cpu with --sort -%cpu or by memory with --sort -%mem.\nBecause ps aux returns every running process on the system, you’ll probably want to pipe the output into head.\nAnother useful way to use ps aux is in combination with grep. If you pretty much know what the problem is – often this might be a runaway R or Python process – ps aux | grep &lt;name&gt; can be super useful to get the pid.\nFor example, here are the RStudio processes currently running on my system.\n &gt; ps aux | grep \"RStudio\\|USER\"                                                                                      [10:21:18]\nUSER               PID  %CPU %MEM      VSZ    RSS   TT  STAT STARTED      TIME COMMAND\nalexkgold        23583   0.9  1.7 37513368 564880   ??  S    Sat09AM  17:15.27 /Applications/RStudio.app/Contents/MacOS/RStudio\nalexkgold        23605   0.5  0.4 36134976 150828   ??  S    Sat09AM   1:58.16 /Applications/RStudio.app/Contents/MacOS/rsession --config-file none --program-mode desktop \n\n\n\n\n\n\nTip\n\n\n\nThe grep command above looks a little weird because I used a little trick. I wanted to keep the header in the output, so the regex I used matches both the header line (USER) and the thing I actually care about (RStudio).\n\n\n\n\n\n\n\n\n\n\nCommand\nWhat it does\nHelpful options\n\n\n\n\ntop\nSee what’s running on the system.\n\n\n\nps aux\nSee all system processes.\nConsider using --sort and pipe into head or grep\n\n\nkill\nKill a system process.\n-9 to force kill immediately\n\n\n\n\n\n11.7.3 Managing networking\nNetworking is a complicated topic, which we’ll approach with great detail in Chapter 12. For now, it’s important to be able to see what’s running on your server that is accessible from the outside world on a particular port.\nThe main command to help you see what ports are being used and by what services is the netstat command. netstat returns the services that are running and their associated ports. netstat is generally most useful with the -tlp flags to show programs that are listening and the programs associated.\nTODO: get netstat example\n\n\n\n\n\n\n\n\nCommand\nWhat it does\nHelpful options\n\n\n\n\nnetstat\nSee ports and services using them.\nUsually used with -tlp\n\n\n\nSometimes you know you’ve got a service running on your machine, but you just can’t seem to get the networking working. It can be useful to access the service directly without having to deal with networking. You can do this with port forwarding, also called tunneling.\nSSH port forwarding allows you to take the output of a port on a remote server, route it through SSH, and display it as if it were on a local port. For example, let’s say I’ve got RStudio Server running on my server. Maybe I don’t have networking set up yet, or I just can’t get it working. If I’ve got SSH to my server working properly, I can double check that the service is working as I expect and the issue really is somewhere in the network.\nI find that the syntax for port forwarding completely defies my memory and I have to google it every time I use it. For the kind of port forwarding you’ll use most often in debugging, you’ll use the -L flag.\nssh -L &lt;local port&gt;:&lt;remote ip&gt;:&lt;remote port&gt; &lt;ssh hostname&gt;\nWhen you’re doing ssh forwarding, local is the place you’re ssh-ed into (aka your server) and the remote is another location – usually your laptop.\nSince the “remote” is my laptop, I almost always want to use localhost as the remote IP, and I usually want to use the same port remotely and locally – unless the local service is on a reserved port.\nSo let’s say I’ve got RStudio Server running on my server at my-ds-workbench.com on port 3939. Then I could run ssh -L 3939:localhost:3939 my-user@my-ds-workbench.com. With this command, I can bypass networking and just access whatever is at port 3939 on my server (hopefully RStudio Workbench!) by just going to localhost:3939 in my laptop’s browser.\n\n\n11.7.4 Understanding PATHs\nTODO: add note on symlinks\nLet’s say you want to open R on your command line. Once you’ve got everything properly configured, you can just type R and have it open right up.\n ❯ R                                                       \n\nR version 4.2.0 (2022-04-22) -- \"Vigorous Calisthenics\"\nCopyright (C) 2022 The R Foundation for Statistical Computing\nPlatform: x86_64-apple-darwin17.0 (64-bit)\n\nR is free software and comes with ABSOLUTELY NO WARRANTY.\nYou are welcome to redistribute it under certain conditions.\nType 'license()' or 'licence()' for distribution details.\n\n  Natural language support but running in an English locale\n\nR is a collaborative project with many contributors.\nType 'contributors()' for more information and\n'citation()' on how to cite R or R packages in publications.\n\nType 'demo()' for some demos, 'help()' for on-line help, or\n'help.start()' for an HTML browser interface to help.\nType 'q()' to quit R.\n\n&gt;\nBut how does the operating system know what you mean when you type R? If you’ve been reading carefully, you’ve realized that running the command means opening a particular runnable file, and R isn’t a file path on my system.\nYou can actually just type the complete filename of a runnable binary into your command line. For example, on my MacBook, my version of R is at /usr/bin/local/R, so I could open an R session by typing that full path. Sometimes it can be handy to be precise about exactly which executable you’re opening (I’m looking at you, multiple versions of Python), so you may want to use full paths to executables.\nIf you ever want to check which actual executable is being used by a command, you can use the which command. For example, on my system this is the result of which R.\n ❯ which R                                                    \n/usr/local/bin/R\nMost of the time you don’t want to have to bother with full paths for executables. You want to just type R on the command line and have R open. Moreover, there are cases where functionality relies on another executable being able to find R and run it – think of running RStudio Server, which starts a version of R under the hood.\nThe operating system knows how to find the actual runnable programs on your system via something called the path. When you type R into the command line, it searches along the path to find a version of R it can run.\nYou can check your path at any time by echoing the PATH environment variable with echo $PATH. On my MacBook, this is what the path looks like.\n ❯ echo $PATH                                                      \n/opt/homebrew/bin:/opt/homebrew/sbin:/usr/local/bin:/System/Cryptexes/App/usr/bin:/usr/bin:/bin:/usr/sbin:/sbin\nLater, when we get into running versions of programs that aren’t the system versions, we may have to append locations to the path so that we can run them easily."
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+    "text": "11.7 Recommendation 3: Get lots of storage, it’s cheap\nAs for configuring storage on your server – get a lot – but don’t think about it too hard, because it’s cheap and easy to upgrade. Storage is cheap enough these days that it is almost always more cost efficient to buy more storage rather than making a highly-paid professional spend their time trying to figure out how to move things around.\n\n\n\n\n\n\nNote\n\n\n\nIf the IT/Admins at your organization want you to spend a lot of time deleting things from storage that’s usually a red flag that they aren’t thinking much about how to make the overall organization work more smoothly.\n\n\nIf you’re running a multi-user server, the amount of storage you need depends a lot on your data and your workflows.\nIf you’re not running particularly large data, or most of your data won’t be saved into the server’s storage (generally a good thing), a reasonable rule of thumb is to choose\n\\[\n\\text{Amount of Storage} = \\text{1Gb} * \\text{n users}\n\\]\nIf you’re not saving large data files, the amount of space each person needs on the server is small. Code is very small and it’s rare to see R and Python packages take up more than a few dozen Mb per data scientist.\n\n\n\n\n\n\nNote\n\n\n\nIf you’re working with a professional IT admin, they may be concerned about the storage implications of having package copies for each person on their team if you’re following best practices for running environments as code from Chapter 1. I’ve heard this concern a lot from IT/Admins thinking ahead about running their server and almost never of a case where it’s actually been a problem.\n\n\nIf, on the other hand, you will be saving a lot of data, you’ve got to take that into account. In some organizations, each data scientist will save dozens of flat files of a Gb or more for each of their projects.\nIf you’re operating in the cloud, this really isn’t an important choice. As you’ll see in the lab, upgrading the amount of storage you have is a trivial operation, requiring at most a few minutes of downtime. Choose a size you guess will be adequate and add more if you need."
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-    "text": "11.8 Comprehension Questions\n\nCreate a mind map of the following terms: Operating System, Windows, MacOS, Unix, Linux, Distro, Ubuntu\nWhen you initially SSH-ed into your server using ubuntu@$SERVER_ADDRESS, what user were you and what directory did you enter? What about when you used test_user@$SERVER_ADDRESS?\nWhat are the 3x3 options for Linux file permissions? How are they indicated in an ls -l command?\nHow would you do the following?\n\nFind and kill the process IDs for all running rstudio-server processes.\nFigure out which port JupyterHub is running on.\nCreate a file called secrets.txt, open it with vim, write something in, close and save it, and make it so that only you can read it."
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+    "text": "11.8 GPUs are special-purpose compute\nAll computers have a CPU. There are also specialized chips where the CPU can offload particular tasks, the most common of which is the graphical processing unit (GPU). GPUs are architected for tasks like editing photo or videos, rendering video game graphics, some kinds of machine learning, and (yes) Bitcoin mining.\nA GPU is an addition factory just like a CPU, but with the opposite architecture. CPUs have only a handful of cores, but those cores are fast. A GPU takes the opposite approach, with many (relatively) slow cores.\nWhere a consumer-grade CPU has 4-16 cores, mid-range GPUs have 700-4,000 cores, with each one running at only about 1% to 10% the single core clock speed speed of a CPU core.\nThe choice of whether you need a GPU to do your work will really depend on what you’re doing and your budget.\nFor the tasks GPUs are good at, the overwhelming parallelism ends up being more important than the speed of any individual core, and GPU computation can be dramatically faster."
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-    "text": "11.9 Lab: A working Data Science Workbench\nIn the last chapter’s lab, we set up a bare Ubuntu server in AWS. In this chapter, we’re going to make that server into a data science workbench. By the end of this chapter, you’ll have a functional data science workbench - though it won’t yet be accessible to the outside world.\n\n11.9.0.1 Step 1: Log on with the .pem key\nThe .pem key you downloaded when you set up the server is the skeleton key – it will automatically let you in with complete admin privileges. We’re going to use the .pem key to get started on the server, but be extremely careful with the power of the .pem key.\nBecause the keypair is so powerful, AWS requires that you restrict the access pretty severely. If you try to use the keypair without first changing the permissions, you’ll be unable to, and you’ll get a warning that looks something like this:\n\n\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\n\n\\@ WARNING: UNPROTECTED PRIVATE KEY FILE! \\@\n\n\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\\@\n\nPermissions 0644 for 'do4ds-lab-key.pem' are too open.\n\nIt is required that your private key files are NOT accessible by others.\n\nThis private key will be ignored.\n\nLoad key \"do4ds-lab-key.pem\": bad permissions\n\nubuntu\\@ec2-54-159-134-39.compute-1.amazonaws.com: Permission denied (publickey).\nBefore we can use it to open the server, we’ll need to change the permissions so that only the user can use it. We’re going to give the key 600 permissions. If you recall from above, that means that the user can read and write the file and no one else can access.\nOn my machine, changing the key goes like this:\n\n\nTerminal\n\ncd ~/Documents/do4ds-lab\nchmod 600 do4ds-lab-key.pem\n\nIn your terminal type the following\n\n\nTerminal\n\nssh -i do4ds-lab-key.pem \\\n  ubuntu@$SERVER_ADDRESS\n\nType yes when prompted, and you’re now logged in to your server!\n\n\n\n\n\n\nSSH on Windows\n\n\n\nFor a long time, Windows didn’t come with a built in SSH client, so you had to use PuTTY to do SSH from a Windows machine. Microsoft brought a native SSH client to Windows 10 in 2015, and it has been enabled by default since 2018.\nIf you run into any trouble using SSH commands on Windows, double check that you’ve enabled the OpenSSH Client.\n\n\n\n\n11.9.1 Step 2: Create a non-root user\nThe first thing we’re going to do is create a user so that you can login without running as root all the time. In general, if you’ve got a multitenant server, you’re going to want users for each actual human who’s accessing the system.\nI’m going to use the username test-user. If you want to be able to copy/paste commands from the online book, I’d advise doing the same. If you were creating users based on real humans, I’d advise using their names.\nLet’s create a user using the adduser command. This will walk us through a set of prompts to create a new user with a home directory and a password. Feel free to add any information you want – or to leave it blank – when prompted.\n\n\nTerminal\n\nsudo adduser test-user\n\nWe want this new user to be able to adopt root privileges. Remember that the way that is determined is whether the user is part of the sudo group. Here’s the command you’ll need to make it so.\n\n\nTerminal\n\nsudo usermod -aG sudo test-user\n\n\n\n11.9.2 Step 3: Add an SSH Key for your user\nThe first thing you should do is check if you have an SSH key on your laptop. You’ll need to open a different terminal window or tab than the one that’s SSH-ed into your server and try ls ~/.ssh.\nIf you’ve got one already, I’d recommend just using that key so you don’t have to mess around with multiple keys. If you don’t have one, google how to create an SSH key and do it on your laptop. If you’re not really sure what an SSH key is, I’d recommend re-reading Chapter 8.\nOnce you’ve got an SSH key, we’re going to add it to the authorized_users for our user on the server.\nFirst, you need to get your public key to the server. I recommend using scp.10\nYou’ll need to check that your SERVER_ADDRESS variable is still set using echo $SERVER_ADDRESS. If it’s not set, you’ll have to re-set it to be the public IPv4 from your server.\nFor me, the command looks like this\n\n\nTerminal\n\nscp -i ~/Documents/do4ds-lab/do4ds-lab-key.pem ~/.ssh/id_ed25519.pub ubuntu@$SERVER_ADDRESS:/home/ubuntu \n\nYou may need to change the file paths to either your server’s pem key or your SSH key if they’re not in the same locations as mine.\nNow our public key is on the server, but it’s in the ubuntu user’s home directory. We’re going to add it as an authorized key for the test-user so that we can SSH in as that user.\nLet’s go back to the tab that’s open to the SSH connection to our server.\nHere are the commands to do so:\n\n\nTerminal\n\nsu test-user #change user\ncd ~ # move to home directory\nmkdir -p .ssh # create .ssh directory\nsudo mv /home/ubuntu/id_ed25519.pub ./.ssh # move key into .ssh \nsudo chown test-user:test-user ~/.ssh/id_ed25519.pub # take ownership of key\nchmod 700 .ssh # Lock directory from other users\ncat .ssh/id_ed25519.pub &gt; .ssh/authorized_keys #add public key to end of authorized_keys file\nchmod 600 .ssh/authorized_keys #set permissions\n\nNow we’re all set up with SSH, and you can log in as a normal user from your laptop just using ssh test-user@$SERVER_ADDRESS.\nIf you want to set up an SSH config for this server, I’d advise waiting until we’ve got a permanent URL for it in the next chapter.\nNow that we’re all set up, you should store the pem key somewhere safe and never use it to log in again.\nWhen you ever want to exit SSH and get back to your machine, you can just type exit.\n\n\n\n\n\n\nTip\n\n\n\nIf you run into trouble assuming sudo with your new user, try exiting SSH and coming back. Sometimes these changes aren’t picked up until you restart the shell.\n\n\n\n\n11.9.3 Step 4: Install R\nEverything until now has been generic server administration. Now let’s get into some data-science-specific work – setting up R and Python.\nThere are a number of ways to install R on your server including installing it from source, from the system repository, or using R-specific tooling.\nYou can use the system repository version of R, but then you just get whatever version of R happens to be current when you run sudo apt-get install R. My preferred option is to use rig, which is an R-specific installation manager.\n\n\n\n\n\n\nNote\n\n\n\nAs of this writing, rig only supports Ubuntu. If you want to install on a different Linux distro, you will have to install R a different way.\n\n\nThere are good instructions on downloading rig and using it to install R on the rlib/rig GitHub repo. Use those instructions to install the current R release on your AWS server.\nOnce you’ve installed R on your server, you can check that it’s running by just typing R into the command line. If that works, you’re good to move on to the next step.\n\n\n11.9.4 Step 5: Install Python\nIt’s very likely that the version of Python on your system is old. Generally we’re going to want to install a newer Python for doing data science work, so let’s start there. As of this writing, Python 3.10 is a relatively new version of Python, so we’ll install that one.\nLet’s start by actually installing Python 3.10 on our system. We can do that with apt.\n\n\nTerminal\n\nsudo apt-get install python3.10-venv\n\nOnce you’ve installed Python, you can check that you’ve got the right version by running\n\n\nTerminal\n\npython3 --version\n\n\n\n11.9.5 Step 5: Installing RStudio Server\nOnce R is installed, let’s download and install RStudio Server.\nI’m not going to reproduce the commands here because the RStudio Server version numbers change frequently and you probably want the most recent one.\nYou can find the exact commands on the Posit website. Make sure to pick the version that matches your operating system. Since you’ve already installed R, you can skip down to the “Install RStudio Server” step.\nOnce you’ve installed, you can check the status with sudo systemctl status rstudio-server. If there’s a line that says Active: active (running), you’re good to go!\n\n\n11.9.6 Step 6: Installing JupyerHub + JupyterLab\nBecause python is so crucial to the operation of your system are python programs, we’re going to want to create a standalone virtual environment for running JupyterHub.\nHere are the commands to create and activate a jupyterhub virtual environment\n\n\nTerminal\n\nsudo python3 -m venv /opt/jupyterhub\nsource /opt/jupyterhub/bin/activate\n\nNow we’re going to actually get JupyterHub up and running inside the virtual environment we just created. JupyterHub produces docs that you can use to get up and running very quickly. If you have to stop for any reason, make sure to come back, assume sudo, and start the JupyterHub virtual environment we created.\nHere were the installation steps that worked for me:\n\n\nTerminal\n\nsudo su\napt install npm nodejs\nnpm install -g configurable-http-proxy\npython3 -m pip install jupyterhub jupyterlab notebook\n\nln -s /opt/jupyterhub/bin/jupyterhub-singleuser /usr/local/bin/jupyterhub-singleuser # symlink in singleuser server, necessary because we're using virtual environment\n\njupyterhub\n\nIf all went well, you’ll now have JupyterHub up and running on port 8000!\n\n11.9.6.1 Running JupyterHub as a service\nAs I mentioned above, JupyterHub is a Python process, not a system process. This is ok, but it means that we’ve got to remember the command to start it if we have to restart it, and that it won’t auto restart if it were to fail for any reason.\nA program that runs in the background on a machine, starting automatically, and controlled by systemctl is called a daemon. Since we want JupyterHub to be a daemon, we’re got to add it as a system daemon, which isn’t hard.\nWe don’t need it right now, but it’ll be easier to manage JupyterHub later on from a config file that’s in /etc/jupyterhub.\nLet’s create a default config file and move it into the right place using\n\n\nTerminal\n\nsudo su\nsource /opt/jupyterhub/bin/activate\njupyterhub --generate-config\nmkdir -p /etc/jupyterhub\nmv jupyterhub_config.py /etc/jupyterhub\n\nNow we’ve got to daemon-ize JupterHub. There are two steps – create a file describing the service for the server’s daemon, and then start the service.\nTo start with, end the existing JupyterHub process. If you’ve still got that terminal open, you can do so with ctrl + c. If not, you can use your ps aux and grep skills to find and kill the JupyterHub processes.\nOn Ubuntu, adding a daemon file uses a tool called systemd and is really straightforward.\nFirst, add the following to /etc/systemd/system/jupyterhub.service. If you’re reading this book in hard copy, you can go to the online version to copy/paste or get this file on the book’s Git repo at TODO.\n\n\n/etc/systemd/system/jupyterhub.service\n\n[Unit]\nDescription=Jupyterhub\nAfter=syslog.target network.target\n\n[Service]\nUser=root\nEnvironment=\"PATH=/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/opt/jupyterhub/bin\"\nExecStart=/opt/jupyterhub/bin/jupyterhub -f /etc/jupyterhub/jupyterhub_config.py\n\n[Install]\nWantedBy=multi-user.target\n\nHopefully this file is pretty easy to parse. Two things to notice – the Environment line adds /opt/jupyterhub/bin to the path – that’s where our virtual environment is.\nSecond, the ExecStart line is the startup command and includes our -f /etc/jupyterhub/jupyterhub_config.py – this is the command to start JupyterHub with the config we created a few seconds ago.\nNow we just need to reload the daemon tool so it picks up the new service it has available and start JupyterHub!\n\n\nTerminal\n\nsystemctl daemon-reload\nsystemctl start jupyterhub\n\nYou should now be able to see that JupyterHub is running using systemctl status jupyterhub and can see it again by tunneling to it.\nTo set JupyterHub to automatically restart when the server restarts, run systemctl enable jupyterhub.\n\n\n\n11.9.7 Step 7: Running a Plumber API in a Container\nIn addition to running a development workbench on your server, you might want to run a data science project. If you’re running a Shiny app, Shiny Server is easy to configure along the lines of RStudio Server.\nHowever, if you put an API in a container like we did in Chapter 9, you might want to deploy that somewhere on your server as a running container.\nThe first step is to install docker on your system with sudo apt-get install docker.io. You can check that you can run docker with docker ps. You may need to adopt sudo privileges to do so.\nOnce we have docker installed, getting the API running is almost trivially easy using the command we used back in Chapter 9 to run our container.\n\n\nTerminal\n\nsudo docker run --rm -d \\\n  -p 8080:8080 \\\n  --name penguin-model \\\n  alexkgold/penguin-model\n\nThe one change you might note is that I’ve changed the port on the server to be 8080, since we already have JupyterHub running on 8000.\nOnce it’s up, you can check that it’s running with docker ps.\nThis is why people love docker – it’s wildly easy to get something simple running. But getting Docker hardened for production takes a bit more work.\nThe first thing to notice is that there’s no auth on our API. Anyone can hit this API as much as they want if they have the URL. Needless to say, this is not a security best practice unless you intend to host a public service.\nThe other issue is that we haven’t daemonized the API. If we restart the server or the container dies for any reason, it won’t auto-restart.\nIt’s not generally a best practice to daemon-ize a docker container by just putting the run command into systemd. Instead, you should use a container management system that is designed specifically to manage running containers, like Docker Compose or Kubernetes. Getting deeper into those systems is beyond the scope of this book.\n\n\n11.9.8 Step 8: Putting up the Shiny app\nInstall Shiny Server using the instructions from the Admin Guide. Note that you don’t need to install R, as we’ve already done that, and you don’t need to install {shiny}, as we’re going to use {renv}.\nTODO\nEdit /etc/shiny-server/shiny-server.conf to run the right app – may have to edit user.\n\n\n/etc/shiny-server/shiny-server.conf\n\n# Instruct Shiny Server to run applications as the user \"shiny\"\nrun_as test-user;\n\n# Define a server that listens on port 3838\nserver {\n  listen 3838;\n\n  # Define a location at the base URL\n  location / {\n\n    # Host the directory of Shiny Apps stored in this directory\n    site_dir /home/test-user/do4ds-lab/app;\n\n    # Log all Shiny output to files in this directory\n    log_dir /var/log/shiny-server;\n\n    # When a user visits the base URL rather than a particular application,\n    # an index of the applications available in this directory will be shown.\n    directory_index off;\n  }\n}\n\nStart Shiny Server\n\n\n11.9.9 Step 8: Check it all out\nJust knowing that all of our services are running isn’t nearly as fun as actually trying them out.\nWe don’t have a stable public URL for the server yet, so we can’t just access it from our browser. This is a perfect use case for an SSH tunnel.\nTODO: picture of server w/ RStudio on 8787, JupyterHub on 8000, and Palmer Penguin container on 8080.\nIf you recall, the command for an SSH tunnel from a remote server to localhost is to do ssh -L &lt;remote port&gt;:localhost:&lt;local port&gt; &lt;user&gt;@&lt;server&gt;.\nWe’ve got three services running on our server, RStudio Server at 8787, JupyterHub on 8000, and our Plumber API on 8080. You can try each of them out by subbing those in for the remote port and putting them at a local port. I’d recommend just using the same one.\nFor example, by running ssh -L 8787:localhost:8787 test-user@$SERVER_ADDRESS, I can visit RStudio Server in my browser at localhost:8787 and login with the username test-user and password I set on the server."
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+    "section": "11.9 Recommendation 4: Get a GPU, maybe",
+    "text": "11.9 Recommendation 4: Get a GPU, maybe\nThe tasks that most benefit from GPU computing are training highly parallel machine learning models like deep learning or tree-based models. If you do have one of these use cases, GPU computing can massively speed up your computation – making models trainable in hours instead of days.\nIf you are planning to use cloud resources for your computing, GPU-backed instances are quite pricey, and you’ll want to be careful about only putting those machines up when you’re using them.\nBecause GPUs are expensive, I generally wouldn’t bother with GPU-backed computing unless you’ve already tried without and find that it takes too long to be feasible.\nIt’s also worth noting that using a GPU won’t happen automatically. The tooling has gotten good enough that it’s usually pretty easy to set up, but your computer won’t train your XGBoost models on your GPU unless you tell it to do so."
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-    "text": "Or at least they weren’t supposed to. There’s an interesting history of lawsuits around the BSD operating system including Unix code. BSD is a Unix clone that was the predecessor of MacOS.↩︎\nCheck out the History of Linux Wikipedia article for the posting.\nPedants will scream that the original release of Linux was just the operating system kernel, not a full operating system like Unix. Duly noted, now go away.↩︎\nThe remainder are almost entirely Windows servers. There are a few other Unix-like systems that you might encounter, like Oracle Solaris. There is no MacOS server. There is a product called Mac Server, but it’s just a program for managing Mac desktops and iOS devices.↩︎\nCentOS (short for Community ENTerprise Operating System) is an open source operating system maintained by Red Hat. The relationship between RHEL and CentOS is changing. The details are somewhat complicated, but most people expect less adoption of CentOS in enterprise settings going forward.↩︎\nMy goal here is to be useful not precise, so I’m intermingling bash commands and Linux system commands because they’re useful. If you know the difference and are pedantic enough to care, this list isn’t for you anyway.↩︎\nDepending on your version of Linux, there may be a limit of 16 groups per user.↩︎\nYou can generally ignore the number, which is the number of links to the file.↩︎\nClever eyes may realize that this is just the base-10 representation of a three-digit binary number.↩︎\nThis is another one where you’ll almost never use ps without aux.↩︎\nAlternatively, you could open a file of the right name and just copy/paste the contents of your public key in there. Either way works.↩︎"
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+    "section": "11.10 Assessing RAM + CPU usage",
+    "text": "11.10 Assessing RAM + CPU usage\nOnce you’ve chosen your server size and gotten up and running, you’ll want to be able to monitor RAM and CPU for problems.\nAny program that is running is called a process. For example, when you type python on the command line to open a REPL, that starts a single Python process. If you were to start a second terminal session and run python again, you’d have a second Python process.\nComplicated programs often involve multiple interlocking processes. For example, running the RStudio IDE involves (at minimum) one process for the IDE itself and one for the R session that it uses in the background. The relationships between these different processes is mostly hidden from you – the end user.\nAs an admin, you may want to inspect the processes running on your system at any given time. The top command is a good first stop. top shows the top CPU-consuming processes in real time along with a number of other facts about them.\nHere’s the top output from my machine as I write this sentence.\n\n\nTerminal\n\nPID    COMMAND      %CPU TIME     #TH    #WQ  #PORT MEM    PURG   CMPRS PGRP\n0      kernel_task  16.1 03:56:53 530/10 0    0     2272K  0B     0B    0\n16329  WindowServer 16.0 01:53:20 23     6    3717  941M-  16M+   124M  16329\n24484  iTerm2       11.3 00:38.20 5      2    266-  71M-   128K   18M-  24484\n29519  top          9.7  00:04.30 1/1    0    36    9729K  0B     0B    29519\n16795  Magnet       3.1  00:39.16 3      1    206   82M    0B     39M   16795\n16934  Arc          1.8  18:18.49 45     6    938   310M   144K   61M   16934\n\nIn most instances, the first three columns are the most useful. The first column is the unique process id (pid) for that process. You’ve got the name of the process (COMMAND) and how much CPU its using. You’ve also got the amount of memory used a few columns over. Right now, nothing is using very much CPU.\nThe top command takes over your whole terminal. You can exit with Ctrl + c.\n\n\n\n\n\n\nSo much CPU?\n\n\n\nFor top (and most other commands), CPU is expressed as a percent of single core availability. So, on a modern machine with multiple cores, it’s very common to see CPU totals well over 100%. Seeing a single process using over 100% of CPU is rarer.\n\n\nAnother useful command for finding runaway processes is ps aux. It lists a snapshot of all processes running on the system, along with how much CPU or RAM they’re using. You can sort the output with the --sort flag and specify sorting by cpu with --sort -%cpu or by memory with --sort -%mem.\nBecause ps aux returns every running process on the system, you’ll probably want to pipe the output into head. In addition to CPU and Memory usage, ps aux gets you who launched the command and the PID.\nFor example, here are the RStudio processes currently running on my system.\n\n\nTerminal\n\nUSER               PID  %CPU %MEM      VSZ    RSS   TT  STAT STARTED      TIME COMMAND\nalexkgold        23583   0.9  1.7 37513368 564880   ??  S    Sat09AM  17:15.27 /Applications/RStudio.app/Contents/MacOS/RStudio\nalexkgold        23605   0.5  0.4 36134976 150828   ??  S    Sat09AM   1:58.16 /Applications/RStudio.app/Contents/MacOS/rsession --config-file none --program-mode desktop \n\nOne of the times you’ll be most interested in the output of top or ps aux is when something is going rogue on your system and using more resources than you intended. If you have some sense of who started the runaway process or what it it, it can be useful to pipe the output of ps aux into grep.\nFor example, the command to get the output above was ps aux | RStudio.\nIf you’ve got a rogue process, the pattern is to try to find the process and make note of its pid. Then you can immediately end the process by pid with the kill command.\nIf I were to find something concerning – perhaps an R process that is using 500% of CPU – I would want to take notice of its pid to kill it with kill."
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-    "section": "12.1 TCP/IP and the mail",
-    "text": "12.1 TCP/IP and the mail\nLet’s start by imagining you have a penpal, who lives in an apartment building across the country.1\nLet’s say you’ve got some juicy gossip to share with your penpal. Because this gossip is so juicy, you’re not going to put it on a postcard. You’d write your letter, put it inside an envelope, address the letter to the right spot, and put it in the mail.\nYou trust the postal service to take your letter, deliver it to the correct address, and then your friend will be able to read your letter.\nThe process of actualy getting data from one computer to another is governed by the TCP/IP protocol and is called packet switching.2\nWhen a computer has data to send to another computer, it takes that information and packages it up into a bundle called a packet.3\nThe data in the packet is like the contents of your letter.\nJust as the postal service defines permissible envelope sizes and address formats, the TCP/IP protocol defines what a packet has to look like from the outside, including what constitutes a valid address.\nA uniform resource locator (URL) is the way to address a specific resource on a network.\nA full URL includes 4 pieces of information: \\[\\overbrace{\\text{https://}}^\\text{protocol}\\overbrace{\\text{example.com}}^\\text{address}\\overbrace{\\text{:443}}^\\text{port}\\overbrace{\\text{/}}^\\text{resource}\\]\nThe protocol starts the URL. It is separated from the rest of the URL by ://.\nEach of the rest of the pieces of the URL is needed to get to a specific resource and has a real-world analog.\nThe address is like the street address of your penpal’s building. It specifies the host where your data should go.4\nA host is any entity on a network that can receive requests and send responses. So a server is a common type of host on a network, but so is a router, your laptop, and a printer.\nThe port is like your friend’s apartment. It specifies which service on the server to address.\nLastly, the resource dictates what resource you want on the server. It’s like the name on the address of the letter, indicating that you’re writing to your penpal, not their mom or sister.\nThis full URL may look a little strange to you. You’re probably used to just putting a standalone domain like \\(google.com\\) into your browser when you want to go to a website. That’s because https, port 443, and / are all defaults, so modern browsers don’t make you specify them.\nBut what if you make it explicit? Try going to https://google.com:443/. What do you get?"
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+    "text": "11.11 Examining at storage usage\nA common culprit for weird server behavior is running out of storage space. There are two handy commands for monitoring the amount of storage you’ve got – du and df.\nThese commands are almost always used with the -h flag to put file sizes in human-readable formats.\ndf, for disk free, shows the capacity left on the device where the directory sits.\nFor example, here’s the result of running the df command on the chapters directory on my laptop that includes this chapter.\n\n\nTerminal\n\n&gt; df -h chapters\nFilesystem     Size   Used  Avail Capacity iused      ifree %iused  Mounted on\n/dev/disk3s5  926Gi  227Gi  686Gi    25% 1496100 7188673280    0%   /System/Volumes/Data\n\nSo you can see that the chapters folder lives on a disk called /dev/disk3s5 that’s a little less than 1Tb and is 25% full – no problem. On a server this can be really useful to know, because it’s quite easy to switch a disk out for a bigger one in the same spot.\nIf you’ve figured out that a disk is full, it’s usually most cost effective to just buy a bigger disk. But sometimes something weird happens. Maybe there are a few exceptionally big files, or you think unnecessary copies are being made.\nIf so, the du command, short for disk usage, gives you the size of individual files inside a directory. It’s particularly useful in combination with the sort command.\nFor example, here’s the result of running du on the chapters directory where the text files for this book live.\n\n\nTerminal\n\n&gt; du -h chapters | sort\n12M chapters\n1.7M    chapters/sec1/images\n1.8M    chapters/sec1\n236K    chapters/images\n488K    chapters/sec2/images-traffic\n5.3M    chapters/sec2/images-networking\n552K    chapters/sec2/images\n6.6M    chapters/sec2\n892K    chapters/append/images-append\n948K    chapters/append\n\nSo if I were thinking about cleaning up this directory, I could see that my sec1/images directory is my biggest single directory. If you find yourself needing to find big files on your Linux server, it’s worth spending some time with the help pages for du. There are lots of really useful options."
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-    "section": "12.2 Ports get you to the right service",
-    "text": "12.2 Ports get you to the right service\nA port is a location on a server where a network connection is possible. It’s like the apartment number for the mail. Each port has a unique number 1 to just over 65,000. By default, the overwhelming majority of the ports on the server are closed for security reasons.\nYour computer automatically opens ports to make outgoing connections, but if you want to allow someone to make inbound connections – like to access RStudio or a Shiny app on a server – you need to manually configure and open a port.\nAny program that is running on a server and that you intend to be accessible from the outside is called a service. For example, we set up RStudio, JupyterHub, and a Plumber API as services in the lab in Chapter 11. Each service lives on a unique port on the server.\nSince each service running on a server needs a unique port, it’s common to choose a somewhat random relatively high-numbered port. That makes sure it’s unlikely that the port will conflict with another service running on the server.\nFor example RStudio Server runs on port 8787 by default. According to JJ Allaire, there’s no special meaning to this port. It was chosen because it was easy to remember and not 8888, which some other popular projects had taken.\nThere’s a cheatsheet of commonly used ports at the end of the chapter."
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+    "section": "11.12 Running out of Resources",
+    "text": "11.12 Running out of Resources\nIf you recognize that you’re running out of resources on your current server, you may want to move to something bigger. There are two main reasons servers run out of room.\nThe first reason is because people are running big jobs. This can happen at any scale of organization. There are data science teams of one who have use cases that necessitate terrabytes of data.\nThe second reason is because you have a lot of people using your server. This is generally a feature of big data science teams, irrespective of the size of the workloads.\nEither way, there are two basic options for how to scale your data science workbench. The first is vertical scaling, which is just a fancy way of saying get a bigger server. The second option is horizontal scaling, which means running a whole fleet of servers in parallel and spreading the workload across them.\nAs a data scientist, you shouldn’t be shy about vertically scaling if your budget allows it. The complexity of managing a t3.nano with 2 cores and 0.5 Gb of memory is exactly the same as a C5.24xlarge with 96 cores and 192 Gb of memory. In fact, the bigger one may well be easier to manage, since you won’t have to worry about running low on resources.\nThere are limits to the capacity of vertical scaling. As of this writing, AWS’s general-use instance types max out at 96-128 cores. That can quickly get eaten up by 50 data scientists with reasonably heavy computational demands.\nOnce you’re thinking about horizontal scaling, you’ve got a distributed service problem on your hand, which is inherently difficult. You should almost certainly get an IT/Admin professional involved. See Chapter 18 for more on how to talk to them about it.\n\n11.12.1 AWS Instances for data science\nAWS offers a variety of different EC2 instance types split up by family and size. The family is the category of EC2 instance. Different families of instances are optimized for different kinds of workloads.\nHere’s a table of common instance types for data science purposes:\n\n\n\n\n\n\n\nInstance Type\nWhat it is\n\n\n\n\nt3\nThe “standard” configuration. Relatively cheap. Sizes may be limited.\n\n\nC\nCPU-optimized instances, aka faster CPUs\n\n\nR\nHigher ratio of RAM to CPU\n\n\nP\nGPU instances, very expensive\n\n\n\nWithin each family, there are different sizes available, ranging from nano to multiples of xl. Instances are denoted by &lt;family&gt;.&lt;size&gt;. So, for example, when we put our instance originally on a free tier machine, we put it on a t2.micro.\nIn most cases, going up a size doubles the amount of RAM, the number of cores, and the cost. So you should do some quick math before you stand up a C5.24xlarge or a GPU-based P instance. If your instance won’t be up very long, it may be fine, but make sure you take it down when you’re done lest you rack up a huge bill."
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+    "section": "11.13 Comprehension Questions",
+    "text": "11.13 Comprehension Questions\n\nThink about the scenarios below – which part of your computer would you want to upgrade to solve the problem?\n\nYou try to load a big csv file into pandas in Python. It churns for a while and then crashes.\nYou go to build a new ML model on your data. You’d like to re-train the model once a day, but it turns out training this model takes 26 hours on your laptop.\nYou design an visualization Matplotlib , and create a whole bunch in a loop, you want to parallelize the operation. Right now you’re running on a t2.small with 1 CPU.\n\nDraw a mind map of the following: CPU, RAM, Storage, Operations Per Second, Parallel Operations, GPU, Machine Learning\nWhat are the architectural differences between a CPU and a GPU? Why does this make a GPU particularly good for Machine Learning?\nHow would you do the following:\n\nFind all running Jupyter processes that belong to the user alexkgold.\nFind the different disks attached to your server and see how full each one is.\nFind the biggest files in each user’s home directory."
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+    "section": "11.14 Lab: Changing Instance Size",
+    "text": "11.14 Lab: Changing Instance Size\nIn this lab, we’re going to upgrade the size of our server. And the best part is that because we’re in the cloud, it’ll take only a few minutes.\n\n11.14.1 Step 1: Confirm current server size\nFirst, let’s confirm what we’ve got available. You can check the number of CPUs you’ve got with lscpu in a terminal. Similarly, you can check the amount of RAM with free -h. This is just so you can prove to yourself later that the instance really changed.\n\n\n11.14.2 Step 2: Change the instance type and bring it back\nNow, you can go to the instance page in the AWS console. The first step is to stop (not terminate!) the instance. This means that changing instance type does require some downtime for the instance, but it’s quite limited.\nOnce the instance has stopped, you can change the instance type under Actions &gt; Instance Settings. Then start the instance. It’ll take a few seconds to start the instance.\n\n\n11.14.3 Step 3: Confirm new server size\nSo, for example, I changed from a t2.micro to a t2.small. Both only have 1 CPU, so I won’t see any difference in lscpu, but running free -h before and after the switch reveals the difference in the total column:\ntest-user@ip-172-31-53-181:~$ free -h\n               total        used        free      shared  buff/cache   available\nMem:           966Mi       412Mi       215Mi       0.0Ki       338Mi       404Mi\nSwap:             0B          0B          0B\ntest-user@ip-172-31-53-181:~$ free -h\n               total        used        free      shared  buff/cache   available\nMem:           1.9Gi       225Mi       1.3Gi       0.0Ki       447Mi       1.6Gi\nSwap:             0B          0B          0B\nI got twice as much RAM!\nThere are some rules around being able to change from one instance type to another, but this is a superpower if you’ve got variable workloads or a team that’s growing. Once you’re done with your larger server, it’s just as easy to scale it back down.\n\n\n11.14.4 Step 4: Upgrade storage (maybe)\nIf you want more storage, it’s similarly easy to resize the EBS volume attached to your server.\nI wouldn’t recommend doing it for this lab, because you can only automatically adjust volume sizes up, so you’d have to manually transfer all of your data if you ever wanted to scale back down.\nIf you do resize the volume, you’ll have to let Linux know so it can resize the filesystem with the new space available. AWS has a great walk through called Extend a Linux filesystem after resizing the volume that I recommend you follow."
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+    "text": "This was proved in Alan Turing’s 1936 paper on computability. If you’re interested in learning more, I recommend The Annotated Turing: A Guided Tour Through Alan Turing’s Historic Paper on Computability and the Turing Machine by Charles Petzold for a surprisingly readable walkthrough.↩︎\nYou probably don’t experience this personally. Modern computers are pretty smart about dumping RAM onto the hard disk before shutting down, and bringing it back on startup, so you usually won’t notice this happening.↩︎"
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-    "section": "12.3 Assigning addresses",
-    "text": "12.3 Assigning addresses\nThe proper address of a server on a network is defined by the Internet Protocol (IP) and is called an IP Address. IP addresses are mapped to human-friendly domains like \\(google.com\\) with the Domain Name Service (DNS).\n\n\n\n\n\n\nNote\n\n\n\nIn this chapter, we’re going to set DNS aside and talk exclusively about IP Addresses.\nChapter 13 is all about DNS.\n\n\nEvery host on the internet has a public IP address.\nA public IP address is an IP address that is valid across the entire internet. That means that each public IP address is unique across the entire internet. You can think of a public IP address like the public street address of a building.\nBut many hosts are not publicly accessible on the internet. Many are housed in private networks. A private network is one where the hosts aren’t directly accessible to the public. You can think of a host in a private network like a building inside a gated community. You may still be able to get there from the public, but you can’t just walk up to the building from the street. Instead you need to come in through the specific gates that have been permitted and approach only on the roads that are allowed.\nTODO: Image of public IPs like street address, private like cul-de-sac\nThere are many different kinds of private networks. Some are small and enforced by connection to a physical endpoint, like the private network your WiFi router controls that houses your laptop, phone, TV, Xbox, and anything else you allow to connect to your router. In other cases, the network is a software network. Many organizations have virtual private networks (VPNs). In this case, you connect to the network via software. There may be resources you can only connect to inside your VPN and there also might be limitations about what you can go out and get.\nThere are a few different reasons for this public/private network split. The first is security. If you’ve got a public IP address, anyone on the internet can come knock on your virtual front door. That’s actually not so bad. What’s more problematic is that they can go all the way around the building looking for an unlocked side door. Putting your host inside a private network is a way to ensure that people can only approach the host through on the pathways you intend.\nThe second reason is convenience.\nPrivate networks provide a nice layer of abstraction for network addresses.\nYou probably have a variety of network-enabled devices in your home, from your laptop and phone to your TV, Xbox, washing machine, and smart locks. But from the outside, your house has only one public IP address – the address of the router in your home. That means that your router has to keep track of all the devices you’ve got, but they don’t need to register with any sort of public service just to be able to use the internet.\nAs we’ll get into in Chapter 13, keeping track of IP Addresses is best left to machines. If you’re managing a complex private network, it’s really nice to give hostnames to individual hosts. A nice feature of a private hostname compared to a public address is that you don’t have to worry if the hostname is unique across the entire internet – it just has to be unique inside your private network.\n\n12.3.1 Firewalls, allow-lists, and other security settings\nOne of the most basic ways to keep a server safe is to not allow traffic from the outside to come in. Generally that means that in addition to keeping the server ports themselves closed, you’ll also have a firewall up that defaults to all ports being closed.\nIn AWS, the basic level of protection for your server is called the security group. If you remember, we used a default security group in launching your server. When you want to go add more services to your server, you’ll have to open additional ports both on the server and in the security group.\nIn addition to keeping particular ports closed, you can also set your server to only allow incoming traffic from certain IP addresses. This is generally a very coarse way to do security, and rather fragile. For example, you could configure your server to only accept incoming requests from your office’s IP address, but what if someone needs to access the server from home or the office’s IP address is reassigned?\nOne thing that is not a security setting is just using a port that’s hard to guess. For example, you might think, “Well, if I were to put SSH on port 2943 instead of 22, that would be safer because it’s harder to guess!” I guess so, but it’s really just an illusion of security. There are ways to make your server safer. Choosing esoteric port numbers really isn’t it."
+    "section": "12.1 Understanding digital addresses",
+    "text": "12.1 Understanding digital addresses\nYou already use digital addresses all the time in the form of a URL (Uniform Resource Locator).1 A URL fully specifies the network location of a resource and looks like this:\n\\[\\overbrace{\\text{https://}}^\\text{protocol}\\underbrace{\\text{google.com}}_\\text{domain}\\overbrace{\\text{:443}}^\\text{port}\\underbrace{\\text{/}}_\\text{path}\\]\nThis may look a little strange. You’re probably used to using just the domain and maybe a path in your web browser like \\(\\text{google.com}\\) or \\(\\text{google.com/maps}\\). The reason is that you’re usually fine with the default protocol and port, so you may never have realized they’re there.2\nHere’s what each of those four parts are:\n\nThe application layer protocol (often just called the protocol) specifies what type of traffic this is. It’s like agreeing that your letter will be in English or Arabic or Dutch.\nThe domain is a human-readable way of providing the digital street address of the server. We’ll get into the actual address later in the chapter.\nThe port specifies where on the server to direct the traffic. It’s the digital equivalent of the apartment number.\nThe path is a human-friendly way of specifying who you intend the message to go to. It’s like the name of person you’re addressing on your letter.\n\nAs a cloud server admin, most of the networking you’ll do is to ensure someone can just use a domain with a path and access the resources they need from your server."
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-    "text": "12.4 How packets are routed\nThe way packets travel from one computer to another is called routing. A router is a hardware or software device that route packets.\nYou can think of routers and public networks as existing in trees. Each router knows about the IP addresses downstream of it and also the single upstream default address.5\nTODO: diagram of routers in trees\nFor example, the router in your house just keeps track of the actual devices that are attached to it. So if you were to print something from your laptop, the data would just go to your router and then to your printer.\nOn the other hand, when you look at a picture on Instagram, that traffic has to go over the public network. The default address for your home’s router is probably one owned by your internet service provider (ISP) for your neighborhood. And that router’s default address is probably also owned by your ISP, but for a broader network.\nSo your packet will get passed upstream to a sufficiently general network and then back downstream to the actual address you’re trying to reach.\nMeanwhile, your computer just waits for a response. Once the server has a response to send, it comes back using the same technique. Obviously a huge difference between sending a letter to a penpal and using a computer network is the speed. Where sending a physical letter takes a minimum of days, sending and receiving packets over a network is so fast that the delay is imperceptible when you’re playing a multiplayer video game or collaborating on a document online."
+    "section": "12.2 Finding the right digital address",
+    "text": "12.2 Finding the right digital address\nA domain is the human-readable way of addressing a resource on the internet. But it’s not actually the digital street address of any particular server (host). Instead, hosts are actually identified with an IP Address. When that IP address is valid across the entire internet, it’s a public IP address.\n\n\n\n\n\n\nNote\n\n\n\nIP Addresses are mapped to domains via the Domain Name Service (DNS), which you’ll learn about in Chapter 13\n\n\nNetwork traffic arrives in the form of packets, which are routed to the correct IP address in a process called packet switching. You don’t need to understand any more about packet switching than that it reliable gets packets to the right IP Address.3\nOnce the traffic arrives at the server, it has to get to the right service by getting to the right port. Every computer has just over 65,000 ports. Each port is uniquely identified by a number, and there’s a 1-1 mapping between listening services and open ports. Since you’re probably running no more than a handful of services, the overwhelming majority of the ports are closed at any given time.4\nBy default, HTTP traffic goes to port \\(80\\) and HTTPS traffic goes to port \\(443\\). So if there’s just one service, you would configure the application to listen on port \\(80\\) and/or \\(443\\). Then, when people come in, they’d automatically get to the right service.\nBut sometimes you’ve got multiple services on the server. In that case, each one will need to run on a unique port. However, you don’t want to force users to remember, for example, that they access JupyterHub on port \\(8000\\). Instead, you want them just to know that it’s on \\(\\text{/jupyter}\\).\nA proxy is a piece of software that can be used to map paths to another location. Common proxies you might hear about include the open source NGINX and Apache and the paid F5, which is the developer of NGINX. Depending on the configuration, the proxy can be on the same server or a different one.\nIf you’re using a proxy, you’d put each of the server’s services on a different port and use the proxy to redirect incoming traffic to the right place based on the subpath.\nNow, if you were just to put something on port \\(80\\) on your EC2 instance and try to access it from the web, it still wouldn’t work. That’s because there’s a firewall sitting in front of your EC2 instance, which blocks traffic to all but certain ports. In AWS, the default firewall is the security group.\nIn addition to blocking traffic to arriving at certain ports, firewalls can be restricted to allow access only from certain IP Addresses. This can be used, for example, to only allow access from your office to a server. Unless a particular server will only ever be accessed by other servers with known IP addresses, this is a brittle way to configure security and I generally don’t recommend it.\n\n\n\n\n\n\nTip\n\n\n\nIf you think you’ve configured a service correctly and you just can’t seem to access it, one of the first things to check is whether you’ve got the port open in the security group.\nOne symptom that may indicate a security group issue is if you try to go to your service and it just hangs with no response before eventually timing out.\n\n\n\nOnce the traffic makes it to the right server, through the firewall and proxy, and to the right port, it has to communicate using the right application layer protocol. We’ve been talking exclusively about the HTTP and HTTPS application layer protocols, because web traffic arrives as a series of HTTP GET requests, but there are many other application layer protocols, each with its own default port.\nFor example, you’ve already seen a lot about SSH in this book, which is an application layer protocol for allowing secure login and communication over an unsecured network. SSH defaults to port \\(22\\).\nOther important protocols that you might see in this book or elsewhere are SFTP for file transfers, SMTP for emails, LDAP(S) for auth, and websockets, which are used by Shiny and Streamlit."
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-    "text": "12.5 How to recognize an IP address\nYou’ve probably seen IPv4 addresses many times. They’re four blocks of 8-bit fields (numbers between 0 and 255) with dots in between, so they look something like 65.77.154.233.\nIf you do the math, you’ll realize there are “only” about 4 billion of these. While we can stretch those 4 billion IP addresses to many more devices since most devices only have private IPs, we are indeed running out of public IPv4 addresses.\nThe good news is that smart people started planning for this a while ago. In the last few years, adoption of the new IPv6 standard has started. IPv6 addresses are eight blocks of hexadecimal (0-9 + a-f) digits separated by colons, with certain rules that allow them to be shortened, so 4b01:0db8:85a3:0000:0000:8a2e:0370:7334 or 3da4:66a::1 are both examples of valid IPv6 addresses.\nIPv6 will coexist with IPv4 for a few decades and we’ll eventually switch entirely to IPv6. There’s no worry about running out of IPv6 addresses any time soon, because the total quantity of IPv6 addresses is a number with 39 zeroes.\n\n12.5.1 Reserved IP Addresses\nMost IPv4 addresses are freely available to be assigned, but there are a few that you’ll see in particular contexts and it’s useful to know what they are.\nThe first IP address you’ll see a lot is 127.0.0.1, also known as localhost or loopback. This is the way a machine refers to itself.\nFor example, if you open a Shiny app in RStudio Desktop, the app will pop up in a little window along with a notice that says\nListening on http://127.0.0.1:6311\nThat http://127.0.0.1 is indicating that your computer is serving the Shiny app to itself on the localhost address.\nThere are also a few blocks of addresses that are reserved for use on private networks, so they’re never assigned in public.\n\n\n\n\n\n\n\nCode\nMeaning\n\n\n\n\n127.0.0.1\nlocalhost or loopback – the machine that originated the request\n\n\n192.168.x.x\n172.16.x.x.x\n10.x.x.x\nProtected address blocks used for private IP addresses.\n\n\n\nYou don’t really need to remember these, but it’s very likely you’ve seen an address like 192.168.0.1 or 192.168.1.1 if you’ve ever tried to configure a router or modem for your home wifi.\nNow you know why."
+    "section": "12.3 Recognizing IP addresses",
+    "text": "12.3 Recognizing IP addresses\nIf you’ve seen an IP address before, it probably was an IPv4 address, which are four blocks of 8-bit fields (numbers between \\(0\\) and \\(255\\)) with dots in between, so they look like \\(64.56.223.5\\).\nIf you do the math, you’ll realize there are “only” about 4 billion of these. There are so many things on the public internet that we are running out of IPv4 addresses. The good news is that smart people started planning for this a while ago and the adoption of the new IPv6 standard started a few years ago.\nIPv6 addresses are eight blocks of hexadecimal (\\(\\text{0-9}\\) and \\(\\text{a-f}\\)) digits separated by colons, with certain rules that allow them to be shortened, so \\(\\text{4b01:0db8:85a3:0000:0000:8a2e:0370:7334}\\) or \\(\\text{3da4:66a::1}\\) are both examples of valid IPv6 addresses. There’s no worry about running out of IPv6 addresses any time soon, because the total quantity of IPv6 addresses is a number with 39 zeroes.\nIPv6 will coexist with IPv4 for a few decades and we’ll eventually switch entirely to IPv6.\nThere are a few special IPv4 addresses it’s worth knowing. You’ll probably see \\(127.0.0.1\\) a lot, which is also known as \\(\\text{localhost}\\) or loopback. This is the way a machine refers to itself.\nFor example, if you open a Shiny app in RStudio Desktop, the app will pop up in a little window along with a notice that says\nListening on http://127.0.0.1:6311\nThat means that the Shiny app is running on the same computer and is available on port \\(6311\\). You can open that location in your browser to view the app as it runs.\nThere are also a few blocks of IPv4 addresses – those that start with \\(192.168\\), \\(172.16\\), and \\(10\\) that are reserved for use on private networks, so they’re never assigned in public."
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-    "text": "12.6 Basic network troubleshooting\nNetworking can be difficult to manage because there are so many layers where it can go awry. Let’s say you’ve configured a service on your server, but you just can’t seem to access it.\nThe ping command can be useful for checking whether your server is reachable on the network. For example, here’s what happens when I ping the domain where this book sits.\n&gt; ping -o do4ds.com                                                                        \nPING do4ds.com (185.199.110.153): 56 data bytes\n64 bytes from 185.199.110.153: icmp_seq=0 ttl=57 time=13.766 ms\n\n--- do4ds.com ping statistics ---\n1 packets transmitted, 1 packets received, 0.0% packet loss\nround-trip min/avg/max/stddev = 13.766/13.766/13.766/0.000 ms\nThis looks great – it sent 1 packet to the server and got one back. That’s exactly what I want. Seeing an unreachable host or packet loss would be an indication that my networking probably isn’t configured correctly somewhere between me and the server. I generally like to use ping with the -o option for sending just one packet – as opposed to continuously trying.\nIf ping fails, it means that my server isn’t reachable. The things I’d want to check is that I have the URL for the server correct, that DNS is configured correctly (see Chapter 13), that I’ve correctly configured any firewalls to have the right ports open (Security Groups in AWS), and that any intermediate networking devices are properly configured (see more on proxies in Chapter 17).\nIf ping succeeds but I still can’t access the server, curl is good to check. curl actually attempts to fetch the website at a particular URL. It’s often useful to use curl with the -I option so it just returns a simple status report, not the full contents of what it finds there.\nFor example, here’s what I get when I curl CRAN from my machine.\n &gt; curl -I https://cran.r-project.org/                                                         \n \nHTTP/1.1 200 OK\nDate: Sun, 15 Jan 2023 15:34:19 GMT\nServer: Apache\nLast-Modified: Mon, 14 Nov 2022 17:33:06 GMT\nETag: \"35a-5ed71a1e393e7\"\nAccept-Ranges: bytes\nContent-Length: 858\nVary: Accept-Encoding\nContent-Type: text/html\nThe important thing here is that first line. The server is returning a 200 HTTP status code, which means all is well. For more on HTTP status codes and how to interpret them, see Chapter 2.\nIf ping succeeds, but curl does not, it means that the server is up at the expected IP address, but the service is not accessible. At that point, you might check whether the right ports are accessible – it’s possible to (for example) have port 443 or 80 accessible on your server, but not the port you actually need for your service. You also might check on the server itself that the service is running and that it is running on the port you think it is.\nIf you’re running inside a container, you should check that you’ve properly configured the port inside container to be forwarded to the outside."
+    "section": "12.4 Basic network administration",
+    "text": "12.4 Basic network administration\nNetworking can be difficult to manage because there are so many layers. It will frequently happen that you think a service is configured, but you just can’t seem to access it. Here are some basic tools for network debugging.\n\n12.4.1 Browser devtools\nOne of the most useful tools for debugging networking issues can be found in the menus of your web browser. It has developer tools that allow you to inspect the network traffic going back and forth between your machine and a remote.\nThis can be really handy if things are going slowly or if you’re not sure why the page isn’t loading. By inspecting the status codes of different HTTP calls and the time they take, you can develop a pretty good idea of where things might be getting stuck.\n\n\n12.4.2 SSH tunneling/port forwarding\nWhen you start a new EC2 instance in AWS, the default security group opens only port \\(22\\), so only SSH traffic is allowed.\nSo far, you’ve seen SSH used to access the command line on that remote server, but SSH can actually be used to access any port in a process called tunneling or port forwarding.\nWhen you tunnel, you make a port on the remote host available at the same port on \\(\\text{localhost}\\) on your machine. The most common usage is to use your browser to look at what’s available at a specific port on a server via HTTP without configuring the host to accept HTTP traffic on that port.\nYou can create an SSH tunnel to a remote host with\n\n\nTerminal\n\nssh -L &lt;remote port&gt;:localhost:&lt;local port&gt; &lt;user&gt;@&lt;server&gt;\n\nI find that the syntax for port forwarding completely defies my memory and I have to google it every time I use it.5\nSo, for example, if your server were running at \\(64.56.223.5\\) and you has the SSH user test-user, you might forward JupyterHub on port \\(8000\\) with ssh -L 8000:localhost:8000 test-user@64.56.223.5. Once the tunnel is established, you could access JupyerHub in your browser on \\(\\text{localhost:8000}\\).\n\n\n12.4.3 Checking what ports are open\nSometimes you can just forget what ports are open on your machine and for what purposes. Or you want to double check that a configuration change took. In that case, you want to use the netstat command to get the services that are running and their associated ports.\nFor this use, netstat is generally most useful with the -tlp flags to show programs that are listening and the programs associated.\n\n\n12.4.4 Checking if a host is accessible\nThe ping command can be useful for checking whether your server is reachable on the network. For example, the server where this book lives is at \\(185.199.110.153\\). So I can ping that domain to check if it’s accessible.\n&gt; ping -o 185.199.110.153\n\nPING 185.199.110.153 (185.199.110.153): 56 data bytes\n64 bytes from 185.199.110.153: icmp_seq=0 ttl=58 time=23.322 ms\n\n--- 185.199.110.153 ping statistics ---\n1 packets transmitted, 1 packets received, 0.0% packet loss\nround-trip min/avg/max/stddev = 23.322/23.322/23.322/nan ms\nThe -o flag tells ping to try just once as opposed to pinging continuously. The fact that I transmitted and received one packet means that everything is working properly.\nSeeing an unreachable host or packet loss would be an indication that my networking probably isn’t configured correctly somewhere between me and the server. That means it’s time to check that the server is actually up, followed by firewalls (security groups) and proxies. You can also use ping with a domain, so it can also be used to see if DNS is working properly.\nIf ping succeeds but a particular resource is inaccessible, curl is can be useful. curl actually attempts to fetch the website at a particular URL. It’s often useful to use curl with the -I option so it just returns a simple status report, not the full contents of what it finds there.\nFor example, here’s what I get when I curl the website for this book.\n&gt; curl -I https://do4ds.com                                         \n\nHTTP/2 200\nserver: GitHub.com\ncontent-type: text/html; charset=utf-8\nlast-modified: Tue, 04 Jul 2023 16:23:38 GMT\naccess-control-allow-origin: *\netag: \"64a4478a-79cb\"\n...\nThe important thing here is that first line. The server is returning a 200 HTTP status code, which means all is well. If you get something else, take a look at the http code cheatsheet in Appendix C.\nIf ping succeeds, but curl does not, it means that the server is up, but the path or port is incorrect. If you’re running inside a container, you should check that you’ve properly configured the port inside container to be forwarded to the outside."
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-    "text": "12.7 Comprehension Questions\n\nWhat are the 4 components of a URL? What’s the significance of each?\nWhat are the two things a router keeps track of? How does it use each of them?\nAre there any inherent differences between public and private IP addresses?\nWhat is the difference between an IP address and a port?\nLet’s say you’ve got a server at 54.33.115.12. Draw a mind map of what happens when you try to SSH into the server. Your explanation should include the terms: IP Address, port, 22, default address, router, sever."
+    "section": "12.5 Comprehension Questions",
+    "text": "12.5 Comprehension Questions\n\nWhat are the 4 components of a URL? What’s the significance of each?\nAre there any inherent differences between public and private IP addresses?\nDraw a mind map of trying to access the following in your browser. Include the following terms: URL, domain, IP Address, port, path, \\(80\\), \\(443\\), 8000, proxy, server, HTTP, HTTPS, status code, protocol\n\nA Shiny app on a server at \\(\\text{http://my-shiny.com}\\) where Shiny Server is sitting on port \\(80\\).\nJupyterHub on a server at \\(\\text{https://example.com/jupyter}\\) where Jupyter is on port \\(8000\\)."
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     "title": "12  Intro to Computer Networks",
-    "section": "12.8 Lab: Making it accessible in one place",
-    "text": "12.8 Lab: Making it accessible in one place\nRight now, the only way to get to the various services on our server is only possible via an SSH tunnel. That’s fine for you as you’re working with it – but doesn’t work well if you want to share with other folks.\nNow, you could just open up the different ports each service is on and have people access them there – RStudio on 8787, JupyterHub on 8000, and the API on 8080. But that’s not really ideal. That would mean your users would have to remember and use those ports.\n\n\n\n\n\n\nTip\n\n\n\nIf you do want to try it to prove to yourself that this “works”, go to your server’s Security Group settings and add custom TCP rules allowing access to ports 8787, 8000, and 8080 from anywhere. If you visit $SERVER_ADDRESS:8787 you should get RStudio, similarly with JupyterHub at $SERVER_ADDRESS:8000, and the API at $SERVER_ADDRESS:8080.\nOk, now close those ports back up so we can do this the right way.\n\n\nSo instead, we want all the traffic to come in one front door and for users to use convenient subpaths to reach the services. The tool to accomplish this kind of rerouting is called a proxy.\nIn our case, we’re just going to run a software proxy on our server that reroutes traffic to different ports on our server. We’re going to use Nginx – a very popular open source proxy.\nTODO: Image of proxy\nProxies are an advanced networking topic. Most enterprise networks make extensive uses of proxies. For the data science workbench you’re configuring, you may also need to use a proxy because some open source tooling doesn’t support configuring SSL/HTTPS and don’t permit authentication.\nLet’s get it configured.\n\n12.8.1 Step 1: Configure Nginx\nThe first thing we’re going to do is to configure Nginx on our server. Configuring Nginx is pretty straightforward – you install Nginx, put the configuration file into place, and restart the service to pick up the changes. The hard part is figuring out the right configuration. I’ve tested these steps, and they should work for you the first time. But if they don’t, you’re about to learn about the pain of proxy debugging.\nHere are the steps to configure your proxy on your server:\n\nSSH into your server.\nInstall Nginx with sudo apt install nginx.\nSave a backup of the default nginx.conf, cp /etc/nginx/nginx.conf /etc/nginx/nginx-backup.conf.6\nEdit the Nginx configuration with sudo vim /etc/nginx/nginx.conf and replace it with:\n\n\n\n/etc/nginx/nginx.conf\n\nuser www-data;\nworker_processes auto;\npid /run/nginx.pid;\ninclude /etc/nginx/modules-enabled/*.conf;\n\nevents {\n\tworker_connections 768;\n\t# multi_accept on;\n}\n\nhttp {\n\n map $http_upgrade $connection_upgrade {\n    \t\tdefault upgrade;\n    \t\t''      close;\n  }\n\n  server {\n    listen 80;\n\n    location /rstudio/ {\n      # Needed only for a custom path prefix of /rstudio\n      rewrite ^/rstudio/(.*)$ /$1 break;\n\n      # Use http here when ssl-enabled=0 is set in rserver.conf\n      proxy_pass http://localhost:8787;\n\n      proxy_http_version 1.1;\n      proxy_set_header Upgrade $http_upgrade;\n      proxy_set_header Connection $connection_upgrade;\n      proxy_read_timeout 20d;\n\n      # Not needed if www-root-path is set in rserver.conf\n      proxy_set_header X-RStudio-Root-Path /rstudio;\n\n      # Optionally, use an explicit hostname and omit the port if using 80/443\n      proxy_set_header Host $host:$server_port;\n    }\n\n    location /jupyter/ {\n      # NOTE important to also set bind url of jupyterhub to /jupyter in its config\n      proxy_pass http://127.0.0.1:8000;\n\n      proxy_redirect   off;\n      proxy_set_header X-Real-IP $remote_addr;\n      proxy_set_header Host $host;\n      proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;\n      proxy_set_header X-Forwarded-Proto $scheme;\n\n      # websocket headers\n      proxy_set_header Upgrade $http_upgrade;\n      proxy_set_header Connection $connection_upgrade;\n    }\n\n    location /penguins/ {\n      proxy_pass http://127.0.0.1:8555/;\n      proxy_set_header Host $host;\n    }\n  }\n}\n\n\n\nTest that your configuration is valid sudo nginx -t.\nStart Nginx with sudo systemctl start nginx. If you see nothing all is well.\n\nIf you need to change anything, update the config and then restart with sudo systemctl restart nginx.\n\n\n12.8.2 Step 2: Open port 80\nNow, if you try to go to your server, your browser will spin for a while and nothing will happen. That’s because the AWS security group still only allows SSH access on port 22. We need to add a rule that will allow HTTP access on port 80.\nOn the AWS console page for your instance, find the Security section and click into the security group for your instance. You want to add a new inbound HTTP rule that allows access on port 80 from anywhere. Make sure not to get rid of the rule that allows SSH access on 22. You still need that one too.\nOnce you do this, you should be able to visit your server address and get the default Nginx landing page.\n\n\n12.8.3 Step 3: Configure RStudio Server and JupyterHub to be on a subpath\nComplex web apps like RStudio and JupyterHub frequently reroute people back to themselves. In general, they assume that they’re on the root path /. That’s not true in this case, so we’ve got to let them know about the subpath where they’re actually located.\nConfiguring RStudio Server is already done. The X-RStudio-Root-Path line in the Nginx configuration adds a header to each request coming through the proxy that tells RStudio Server that it’s on the /rstudio path.\nJupyter needs an explicit update to its own configuration to let it know that it’s on a subpath. Luckily it’s a very simple change. You can edit the Jupyter configuration with\n\n\nTerminal\n\nsudo vim /etc/jupyterhub/jupyterhub_config.py\n\nFind the line that reads # c.JupyterHub.bind_url = 'http://:8000'.\n\n\n\n\n\n\nTip\n\n\n\nYou can search in vim from normal mode with / &lt;thing you're searching for&gt;. Go to the next hit with n.\n\n\nDelete the # to uncomment the line and add the subpath on the end. If you’re using the /jupyter subpath and the default 8000 port, that line will read c.JupyterHub.bind_url = 'http://:8000/jupyter'.\nJupyterHub should pick up the new config when it’s restarted with\n\n\nTerminal\n\nsudo systemctl restart jupyterhub\n\n\n\n12.8.4 Step 4: Try it out!\nNow we should have each service configured on a subpath. RStudio Server at /rstudio, JupyterHub at /jupyter, and our machine learning API at /penguins. For example, with my server at ec2-54-159-134-39.compute-1.amazonaws.com, I can get to RStudio Server at http://ec2-54-159-134-39.compute-1.amazonaws.com/rstudio.\n\n\n\n\n\n\nNote\n\n\n\nAs of this writing, the machine learning API serves itself off of /__docs__/, so you actually won’t be able to access anything interesting at /penguins. Instead, you’ll find the API at /penguins/__docs__/.\nThis should be fixed before final publication of this book.\n\n\nNote that right now, this server is on HTTP, which is not a best practice. In fact, it’s such a bad practice that your browser will probably autocorrect the url to start with https and it won’t work. You’ll have to manually correct it to http. Don’t leave it like this for long – make sure to make sure to configure https in Chapter 14 before doing anything real on this server.\n\n\n12.8.5 Lab Extensions\nIf you’ve gone to the bare URL for your server, you’ve probably noticed that it’s just the default Nginx landing page, which is not very attractive.\nYou might want to create a landing page with links to the subpath by serving a static html page off of /. Or maybe you want one of the services at / and the others at a different subpath.\nIf you want to change the subpaths, the location lines in the nginx.conf define the subpaths where the services will be available. By changing those locations, you can change the paths where the services live or you could add another that serves a static web page.\nYou also could add a different service at a different path. Note that the proxy_path lines define the port where the service is running on the server. Depending on the service you’re configuring, there may be other configuration you’ll have to do, but that will vary on a service-by-service basis.\n\n\n12.8.6 Cheatsheet: Special Ports\nAll ports below 1024 are reserved for common server tasks, so you can’t assign services to low-numbered ports.\nThere are also three common ports that will come up over and over. These are handy because if you’re using the relevant service, you don’t have to indicate if it’s using the default port.\n\n\n\nProtocol\nDefault Port\n\n\n\n\nHTTP\n80\n\n\nHTTPS\n443\n\n\nSSH\n22"
+    "section": "12.6 Lab: Making it accessible in one place",
+    "text": "12.6 Lab: Making it accessible in one place\nIn this lab, we’re going to set up a proxy to be able to access all of our services over HTTP.\nBut first, you might want to try out accessing the various services where they are.\nYou could either try SSH tunneling to them and seeing them on localhost or you could apply custom TCP rules to your security group to temporarily allow access directly to the services. If you want to try, here’s a reminder of where everything is:\n\n\n\nService\nPort\n\n\n\n\nJupyterHub\n\\(8000\\)\n\n\nRStudio\n\\(8787\\)\n\n\nPenguin model API\n\\(8080\\)\n\n\nShiny App\n\\(3838\\)\n\n\n\nIf you’re through playing and ready to get everything configured, let’s go ahead. If you changed your security group rules, change them back.\n\n12.6.1 Step 1: Configure Nginx\nHonestly, configuring proxies is a somewhat advanced networking topic, and in most cases you’d just put one service per server. But if you want to be able to save money and run everything on one server, you’ll want a proxy.\nConfiguring Nginx is pretty straightforward – you install Nginx, put the configuration file into place, and restart the service to pick up the changes. The hard part is figuring out the right configuration. Configuring proxies can be quite painful, as the configuration is very sensitive to seemingly meaningless syntax issues.\nHere are the steps to configure your proxy on your server for JupyterHub and RStudio Server:\n\nSSH into your server.\nInstall Nginx with sudo apt install nginx.\nSave a backup of the default nginx.conf, cp /etc/nginx/nginx.conf /etc/nginx/nginx-backup.conf.6\nEdit the Nginx configuration with sudo vim /etc/nginx/nginx.conf and replace it with:\n\n\n\n/etc/nginx/nginx.conf\n\nuser www-data;\nworker_processes auto;\npid /run/nginx.pid;\ninclude /etc/nginx/modules-enabled/*.conf;\n\nevents {\n\tworker_connections 768;\n\t# multi_accept on;\n}\n\nhttp {\n\n map $http_upgrade $connection_upgrade {\n    \t\tdefault upgrade;\n    \t\t''      close;\n  }\n\n  server {\n    listen 80;\n\n    location /rstudio/ {\n      # Needed only for a custom path prefix of /rstudio\n      rewrite ^/rstudio/(.*)$ /$1 break;\n\n      # Use http here when ssl-enabled=0 is set in rserver.conf\n      proxy_pass http://localhost:8787;\n\n      proxy_http_version 1.1;\n      proxy_set_header Upgrade $http_upgrade;\n      proxy_set_header Connection $connection_upgrade;\n      proxy_read_timeout 20d;\n\n      # Not needed if www-root-path is set in rserver.conf\n      proxy_set_header X-RStudio-Root-Path /rstudio;\n\n      # Optionally, use an explicit hostname and omit the port if using 80/443\n      proxy_set_header Host $host:$server_port;\n    }\n\n    location /jupyter/ {\n      # NOTE important to also set bind url of jupyterhub to /jupyter in its config\n      proxy_pass http://127.0.0.1:8000;\n\n      proxy_redirect   off;\n      proxy_set_header X-Real-IP $remote_addr;\n      proxy_set_header Host $host;\n      proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;\n      proxy_set_header X-Forwarded-Proto $scheme;\n\n      # websocket headers\n      proxy_set_header Upgrade $http_upgrade;\n      proxy_set_header Connection $connection_upgrade;\n    }\n  }\n}\n\n\n\nTest that your configuration is valid sudo nginx -t.\nStart Nginx with sudo systemctl start nginx. If you see nothing all is well.\n\nIf you need to change anything, update the config and then restart with sudo systemctl restart nginx.\n\n\n12.6.2 Step 2: Open port 80\nNow, if you try to go to your your server’s public IP address or DNS, your browser will spin for a while and nothing will happen. That’s because the AWS security group still only allows SSH access on port \\(22\\). We need to add a rule that will allow HTTP access on port \\(80\\).\nOn the AWS console page for your instance, find the Security section and click into the security group for your instance. You want to add a new inbound HTTP rule that allows access on port \\(80\\) from anywhere. Make sure not to get rid of the rule that allows SSH access on \\(22\\). You still need that one too.\nOnce you do this, you should be able to visit your server address and get the default Nginx landing page.\n\n\n12.6.3 Step 3: Configure your subpaths\nComplex web apps like RStudio and JupyterHub frequently proxy traffic back to themselves. For example, when you launch a Shiny app in RStudio, you’re actually just opening a “headless” browser window that gets proxied back into your session.\nThis works by default when those apps are on the root path \\(\\text{/}\\). That’s not true in this case, so we’ve got to let the services know where they’re actually located.\nConfiguring RStudio Server is already done. The X-RStudio-Root-Path line in the Nginx configuration adds a header to each request coming through the proxy that tells RStudio Server that it’s on the \\(\\text{/rstudio}\\) path.\nJupyterHub needs a configuration update to let it know that it’s on a subpath. Luckily it’s a very simple change. You can edit the Jupyter configuration with\n\n\nTerminal\n\nsudo vim /etc/jupyterhub/jupyterhub_config.py\n\nFind the line that reads # c.JupyterHub.bind_url = 'http://:8000'.\n\n\n\n\n\n\nTip\n\n\n\nYou can search in vim from normal mode with / &lt;thing you're searching for&gt;. Go to the next hit with n.\n\n\nDelete the # to uncomment the line and add the subpath on the end. If you’re using the \\(\\text{/jupyter}\\) subpath and the default \\(8000\\) port, that line will read c.JupyterHub.bind_url = 'http://:8000/jupyter'.\nJupyterHub should pick up the new config when it’s restarted with\n\n\nTerminal\n\nsudo systemctl restart jupyterhub\n\n\n\n12.6.4 Step 4: Try it out!\nNow we should have each service configured on a subpath. RStudio Server at \\(\\text{/rstudio}\\), JupyterHub at \\(\\text{/jupyter}\\). For example, with my server at \\(\\text{64.56.223.5}\\), I can get to RStudio Server at \\(\\text{http://64.56.223.5/rstudio}\\).\nNote that right now, this server is on HTTP, which is not a best practice. In fact, it’s such a bad practice that your browser will probably autocorrect the url to https and you’ll have to manually correct it back to http and ignore some scary warnings. Don’t worry, we’ll fix this in Chapter 14.\n\n\n12.6.5 Lab Extensions\nIf you’ve gone to the root URL for your server, you’ve probably noticed that it’s just the default Nginx landing page, which is not very attractive.\nYou might want to create a landing page with links to the subpath by serving a static html page off of \\(\\text{/}\\). Or maybe you want one of the services at \\(\\text{/}\\) and the others at a different subpath.\nRight now, neither the penguins model API or the Shiny app are available from the outside. You might want to add them to the proxy to make them accessible. I’ll leave that as an exercise for you.\n\n\n\n\n\n\nTip\n\n\n\nIt’s very common to put an API and/or a Shiny app behind a proxy. Googling “Shiny app behind nginx” or “FastAPI with nginx” will yield good results.\n\n\nOne thing to consider is whether the model API should be publicly accessible at all. If the only thing calling it is the Shiny app, maybe it shouldn’t be?"
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-    "text": "For this analogy to work, everyone lives in apartment buildings rather than standalone houses.↩︎\nTCP and IP are actually two separate protocols at different layers of the protocol stack. But they’re so closely linked that we can talk about them as one.↩︎\nOne of the biggest ways the mail is not like packet switching is that your message gets chopped up among lots of different packets, which are routed independently, and are reassembled when they get where they’re going. Works well for computers, not so well for real-world mail. It’s also pretty much an irrelevant detail, since this whole process works quite invisibly.↩︎\nOften it’s not a single server at the address – but it behaves like one. It could instead be a proxy in front of a cluster of servers or even more complicated routing. All that matters is that it behaves like a single server from the outside.↩︎\nThere are actually a few different types of addresses used to do this. IP addresses are used for identifying network resources and the MAC address used for physical hardware. Your router is also responsible for assigning IP addresses to devices as they join the network via the dynamic host configuration protocol (DHCP). I’m glossing over all these details as they’re immaterial to the understanding important for this chapter.↩︎\nThis is generally a good practice before you start messing with config files. Bad configuration is usually preferable to a service that can’t start at all because you’ve messed up the config so badly. It happens.↩︎"
+    "text": "URLs are a subset of a broader category called Uniform Resource Identifiers (URIs), which look like a URL and are used to identify a resource by may not be a valid address. I mention them only because you may run across them in certain contexts, like configuring SSO.↩︎\nDifferent resources divide URLs into somewhere between three and seven parts. I think these four are the most useful for this chapter’s purpose.↩︎\nHow packet switching works isn’t super relevant, but it is cool. Packets are addressed with their target IP address when they’re first created and are passed off to the router to which the computer is connected. Routers are arranged in a tree-style hierarchy. What’s clever is that each router only keeps track of downstream addresses and a single upstream default address. So the packet gets passed upstream until it hits a router that knows about the target IP address and then back downstream to the host.↩︎\nPorts are also used for outbound communication. Computers know how to automatically open ports for outbound communication and specify that’s where the response should come, so we’re not going to get into them here.↩︎\nAs you might guess from this complicated syntax, you can do a lot more than this with SSH tunneling, but this is most often what I use it for.↩︎\nThis is generally a good practice before you start messing with config files. Bad configuration is usually preferable to a service that can’t start at all because you’ve messed up the config so badly. It happens.↩︎"
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     "title": "13  DNS allows for human-readable addresses",
-    "section": "13.1 How DNS lookups work",
-    "text": "13.1 How DNS lookups work\nIn Chapter 12, we discussed how packets gets routed to successively higher-level routers until there’s one that knows where the packet is going and sends it back down. It turns out that this process essentially happens twice. The first time is to get the IP address for the domain in a process called DNS resolution. The second time is when it actually sends the information to that IP address.\nYou can see the basic structure of a DNS lookup using the terminal command nslookup. Here’s the DNS routing for \\(google.com\\):\n ❯ nslookup google.com                                              \nServer:     192.168.86.1\nAddress:    192.168.86.1#53\n\nNon-authoritative answer:\nName:   google.com\nAddress: 142.251.163.113\nName:   google.com\nAddress: 142.251.163.100\nName:   google.com\nAddress: 142.251.163.138\nName:   google.com\nAddress: 142.251.163.101\nName:   google.com\nAddress: 142.251.163.102\nName:   google.com\nAddress: 142.251.163.139\nThese addresses do change periodically, so they may no longer be valid by the time you read this. But if you want to go do an nslookup yourself, you can visit one of those IP addresses and see that it takes you right to the familiar \\(google.com\\).1\nDNS resolution is actually quite a complex process because every computer in the world needs to be able to resolve a DNS entry to the same IP address in a timely fashion. The simplest form of DNS lookup would be easy – there would just be one nameserver with the top-level domains and then one server for each top-level domain.\nThere are two problems with this theoretical DNS lookup – it wouldn’t be very resilient because of a lack of redundancy and it would be slow. In order to speed things up, the DNS system is highly decentralized.\nAlong with decentralization, DNS resolution relies on a lot of cacheing. When your computer or an intermediate DNS server looks up an IP address for you, it caches it. This is because its likely that if you’ve looked up a domain once, you’re going to do it again soon.\nThis is great if you are using the internet and don’t want to wait for DNS lookups, but when you’re changing the domains on servers you control, there are thousands of public DNS servers that a request could get routed to, and many of them may have outdated cache entries. DNS changes can take up to 24 hours to propagate.\nThat means that if you make a change and it’s not working, you have no idea whether you made a mistake or it just hasn’t propagated yet. It’s very annoying.\nSometimes, using a private browsing window will cause DNS cache refreshes, but not always."
+    "section": "13.1 Basics of DNS and domains",
+    "text": "13.1 Basics of DNS and domains\nWhen you create or launch a website, you’ll purchase (rent, really) a domain like \\(\\text{do4ds.com}\\) from a domain name registrar. Purchasing a domain gives you the right to attach that domain to an IP Address.\nWhen someone comes to visit your website, their computer resolves the IP Address via a DNS lookup against public DNS nameservers. So when you purchase a domain, you register the association between your domain and the IP Address with the DNS nameservers so users can look them up.\nA complete domain is called a Fully-Qualified Domain Name (FQDN) and consists of three parts:\n\\[\n\\overbrace{\\text{blog}}^{\\text{Subdomain}}.\\overbrace{\\underbrace{\\text{example}}_{\\text{Domain Name}}.\\underbrace{\\text{com}}_{\\text{Top-Level Domain}}}^{\\text{Root Domain}}\n\\]\nWhen you get a domain from a registrar, the thing you’ll actually rent is the root domain. You can choose any root domain you want, as long as it’s not already taken. Domain names are unique only within top-level domains, so you might be able to get \\(\\text{example.fun}\\) even if someone else owns \\(\\text{example.com}\\).\n\n\n\n\n\n\nTop-level domains\n\n\n\nWhen the web first launched, there were only a limited number of top-level domains like \\(\\text{.com}\\), \\(\\text{.org}\\), and \\(\\text{.net}\\). ICANN, the group that controls how domains are assigned, controlled them all.\nIn 2013, ICANN decided to allow people and organizations to register their own top-level domains. That’s why there’s been an explosion in websites at top level domains like \\(\\text{.io}\\), \\(\\text{.ai}\\), and \\(\\text{.fun}\\) in the last decade or so.\nI think it’d be fun to have my own top-level domain, so it’s unfortunate that owning a top-level domain is not something to do on a whim. In 2012, the initial application fee was $185,000.\n\n\nSubdomains are a way to specify a part of a domain, usually to signify to users that its for a distinct purpose. You can generally register as many subdomains as you want against a root domain."
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     "section": "13.2 How DNS is configured",
-    "text": "13.2 How DNS is configured\nFrom the perspective of someone trying to set up their own website, there’s only one DNS server that matters to you personally – the DNS server for your domain name registrar.\nDomain name registrars are the companies that actually own domains. You can buy or rent one from them in order to have a domain on the internet.\nYour first stop would be a domain name registrar where you’d find an available domain you like and pull out your credit card.\nCosts for domain names vary widely. Buying a meaningless domain in a less popular top-level domain, say ladskfmlsdf.me can cost as little as $3 per year. On the other hand, buying a .com domain that’s a real word or phrase can be a few thousand dollars. There are articles every few years about some major company accidentally allowing their domain name to lapse and ransoming it back for stupid amounts of money.\nConfiguration of DNS is done by way of records, of which there are a menagerie of types you can configure. Luckily, most simple configurations only need CNAME and A records.\nHere’s an imaginary DNS record table for the domain example.com:\n\n\n\nPath/Host\nType\nTarget\n\n\n\n\n@\nA\n143.122.8.32\n\n\nwww\nCNAME\nexample.com\n\n\n*\nA\n143.122.8.33\n\n\n\nLet’s go through how to read this table.\nSince we’re configuring example.com, the paths/hosts in this table are relative to example.com.\nIn the first row we’re configuring an A record to go to the target IP address. A records (or their IPv6 cousin AAAA records) map a domain to an actual IP address. The path @ is a special symbol meaning exact match. So by this configuration, any traffic to example.com will be passed straight through to the specified IP address.\nThe second row deals with traffic to the www subdomain. CNAME records alias sub-domains. They’re most frequently used to map sub-domains to the main domain. Since this is a CNAME record for example.com, this record indicates that traffic to www.example.com should be treated exactly like traffic to example.com. Some domain providers do automatic redirection of www traffic, and so this row may not be necessary in some configurations.\nThe last record uses the wildcard symbol * to send all subdomain traffic that’s not already spoken for – say blog.example.com or info.example.com directly to the IP address specified. In this case, I’m sending all of those subdomains to a different IP address, maybe a 404 (not found) page – or maybe I’m serving all the subdomains off a different server.\nSo what happens is that your query goes through several layers of public DNS servers to get to the DNS entry for your domain name registrar. In many cases, you’ll directly configure your domain name registrar to point to your website or server – but you also can configure the domain name registrar to point at another set of DNS servers you actually control with an NS record.\nIf you’re setting up your own server, this probably isn’t the case, but some large enterprises do run their own private DNS servers."
+    "text": "13.2 How DNS is configured\nDNS is configured by giving the proper IP Address information to the domain name registrar where you bought your domain. There’s often some minor configuration on the server side as well to let the server know where it lives.\nMost places you might serve a website from have instructions on how to do configure it you can google. The point of this section is just to make you comfortable with whatever instructions you find in your googling.\nThere are a variety of different domain name registrars. Each of the big 3 has their own and there are a number of others including Namecheap (my personal favorite as it is indeed, cheap), Cloudflare, and GoDaddy.\nCosts for domain names vary widely. Buying a meaningless domain in a less popular top-level domain can cost as little as a few dollars per year. For example, I was able to get the domain \\(\\text{do4ds-lab.shop}\\) for $1.98 for a year on Namecheap.\nOn the other hand, buying a \\(\\text{.com}\\) domain that’s a real word or phrase can be thousands of dollars. There are articles every few years about some major company accidentally allowing their domain name to lapse and ransoming it back for stupid amounts of money.\nOnce you’ve purchased your domain, you need to configure the public DNS records of your domain to point to the IP Address you want. Configuration of DNS is done by way of records. Records map a path or host to a target.\nDepending on the type of mapping, records fall into a number of different categories, but there are only a few you’re likely to see:\n\nA records (or their IPv6 cousin AAAA records) map a domain to an actual IP Address.\nCNAME records alias subdomains to another record.\nNS records tells the DNS server to forward the request on to another namespace server. This is usually only used by big organizations that run their own domain name servers for their subdomains.\n\nWhen you go to configure DNS with your domain name registrar, you’ll configure the records in a record table. Here’s an imaginary DNS record table for the domain \\(\\text{example.com}\\):\n\n\n\nPath/Host\nType\nTarget\n\n\n\n\n\\(\\text{@}\\)\nA\n\\(\\text{64.56.223.5}\\)\n\n\n\\(\\text{www}\\)\nCNAME\n\\(\\text{example.com}\\)\n\n\n\\(\\text{blog}\\)\nA\n\\(\\text{114.13.56.77}\\)\n\n\n\\(\\text{*}\\)\nA\n\\(\\text{64.56.223.5}\\)\n\n\n\nThe first row provides an A record for the special \\(\\text{@}\\) symbol meaning exact match. So by this configuration, any traffic to \\(\\text{example.com}\\) will be passed straight through to the specified IP Address.\nThe second row deals with traffic to the \\(\\text{www}\\) subdomain. Since this is a CNAME record, this record indicates that traffic to \\(\\text{www.example.com}\\) should be treated exactly like traffic to the bare \\(\\text{example.com}\\). Some domain providers do automatic redirection of \\(\\text{www}\\) traffic, and so this row may not be necessary in some configurations.\nThe next record sends the \\(\\text{blog}\\) subdomain to a completely different IP Address. This is a common configuration when the subdomain might be owned by a completely different group than the main website or is served from a different server.\nThe last record uses the wildcard symbol \\(\\text{*}\\) to send all subdomain traffic that’s not already spoken for back to the main IP Address.\nOther than the \\(\\text{www}\\) subdomain, which stands for world wide web, and is generally routed to the same place as the bare root domain, using subdomains and choosing between subdomains and paths is entirely about organizing how users experience your website and what’s easiest for your organization to maintain.\n\n\n\n\n\n\n\\(\\text{www}\\) is just a subdomain\n\n\n\nWhen the internet was first started, it seemed like it might be important to differentiate the subdomain where the website would live from, for example, the email domain people at that organization would use.\nThat turned out not really to be the case and these days \\(\\text{www}\\) and the bare root domain are generally used interchangeably.\n\n\nOnce you’ve configured your DNS records, you will need to wait an annoyingly long time to see if you did it correctly.\nWhen your computer does a DNS lookup, there are often at least three nameservers involved. First, your computer talks to a resolver, which is a server that keeps track of where the nameservers are. Then you’re routed to the correct nameserver for the top-level domain, which routes you to the nameserver for your actual domain.\nAnd then there are various geographic repeats of this whole set of servers to make sure your query doesn’t get slowed down by having to travel too far.\nThat means that when you update a DNS record, it can take some time to propagate to all these servers. The other issue is that your computer, and each of these servers, tries to do as few lookups as possible, because they’re slow.\nWhen you configure a DNS record, you configure something called the TTL (time to live). Each level of DNS lookup, may cache the results of looking up a domain to avoid having to ask the next level. How long that cache lasts is configured by the TTL.\nThis is great if you are using the internet and don’t want to wait for DNS lookups, but when you’re changing the domains on servers you control, there are many DNS servers that a request could get routed to, and many of them may have outdated cache entries. That’s why DNS changes can take up to 24 hours to propagate.\nThat means that if you make a change and it’s not working, you have no idea whether you made a mistake or it just hasn’t propagated yet. It’s very annoying."
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+    "text": "13.3 Comprehension Questions\n\nWhat are the parts of a fully-qualified domain name? How does each of them get created?\nHow does your computer find the IP Address for a domain? Why could it sometimes be wrong?\nWhat are the different kinds of DNS records you’re likely to use?"
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     "section": "13.4 Lab: Configuring DNS for your server",
-    "text": "13.4 Lab: Configuring DNS for your server\nIn the last lab, we configured the server so that all of the services were served off of one single port that redirected to various subpaths.\nNow we want to get a real URL for the server so that you don’t have to remember some random ec2- URL for your server. In this lab, we’ll configure DNS records for our server so it’s available at a real URL.\n\n13.4.1 Step 1: Allocate Elastic IP\nEC2 instances get assigned a public IP when they are started. That’s great – it makes it easy to do the kind of work we’ve done. But if you’ve stopped or restarted your server, you’ve you’ve probably noticed that the public IP address changed!\nThis is no good for configuring a long-lived DNS record that consistently routes to your server. So we’re going to use AWS’s Elastic IP service, which gives you a stable public IP address you can keep and move around from one instance to another as you wish.\nElastic IP payment is a little weird. You don’t get charged for Elastic IPs as long as you’re using them. So if your server is up and using an elastic IP, it’s all free. If you take your server down and want to reserve the Elastic IP so it’s the same when you bring it back up, you’ll pay. It’s very cheap for one IP (12 cents per day as of this writing), so don’t worry about it.\nBasically AWS doesn’t want you hoarding Elastic IPs. Great – just make sure to give back the elastic IP if you take down your instance permanently.\n\n\n\n\n\n\nNote\n\n\n\nThe labs in this book are ordered to promote learning.\nIf you configure a server later for real, I’d recommend setting up an Elastic IP as soon as you bring the server up so you have a permanent IP address right off the bat.\n\n\nTo actually do it, find Elastic IP in the AWS console and allocate an address. Once it has been allocated, click through to the elastic IP and associate it with the default private IP address for your instance.\nNote that once you make this change, your server will no longer be available at its old IP address, so you’ll have to SSH in at the new one. If you have SSH terminals open when you make the change, they will break.\n\n\n13.4.2 Step 2: Buy a domain\nYou can buy a domain from any of the many domain purchasing services on the web. Now, it won’t be free, but many domains are very cheap.\nThe easiest place to buy a domain is via AWS’s Route53 service. You can get domains on Route53 for as little as $9 per year – but there are even cheaper services. For example, I was able to get the domain \\(do4ds-lab.shop\\) for $1.98 for a year on namecheap.com, which has long been my choice for purchasing domains because it is indeed, cheap.\n\n\n13.4.3 Step 3: Configure DNS\nOnce you’ve got your domain, you have to configure your DNS. You’ll have to create 2 A records – one each for the @ host and the * host pointing to your IP and one for the CNAME at the www with the value being your bare domain.\nExactly how you configure this will depend on the domain name provider you choose.\nIn NameCheap, my Advanced DNS configuration looks like this:\n\n\n\n13.4.4 Step 4: Wait an annoyingly long time\nNow you just have to be patient. Unfortunately DNS takes time to propagate. After a few minutes (or hours?), your server should be reachable at your domain.\nIf it’s not (yet) reachable, try seeing if an incognito browser works. If it doesn’t, wait some more. When you run out of patience, try reconfiguring everything and check if it works now.\nNote that we still haven’t configured SSL, so you’ll need to make sure to correct your browser away from the https URL.\n\n\n13.4.5 Step 5: Add the Shiny app to your site\nNow that the Shiny app is at a stable URL, let’s put it on our site so people can look at our penguin size prediction model.\nWe’re going to use something called an iFrame, which lets you embed one website inside another. Luckily, it’s really easy to create an iFrame in a Quarto site.\n\n\n\n\n\n\nNote\n\n\n\nOnce you change your website to go over HTTPS in the next section, you’ll have to adjust the iFrame URL as well.\n\n\nIn Quarto, you can just add an html block into your index.qmd. In my case, that block just says\n\n\nindex.qmd\n\n&lt;iframe width=\"780\" height=\"500\" src=\"https://do4ds-lab.shop/penguins/\" title=\"Penguin Model Explorer\"&gt;&lt;/iframe&gt;"
+    "text": "13.4 Lab: Configuring DNS for your server\nIn the last lab, we configured the server so that all of the services were served off of one single port that redirected to various subpaths.\nNow we want to get a real, memorable domain for the server so that you and your users don’t have to remember some random ec2- domain or an IP Address. In this lab, we’ll configure DNS records for our server so it’s available at a real domain.\n\n13.4.1 Step 1: Allocate an Elastic IP\nEC2 instances get assigned a public IP when they are started. The issue is that every time the server stops that IP is released and a new one is assigned when it comes back up. This means you’d have to change your DNS record every time you temporarily take your server offline – no good.\nLuckily, AWS has a great solution here called Elastic IP. which gives you a stable public IP Address you can move from one instance to another as you wish.\n\n\n\n\n\n\nPaying for Elastic IPs\n\n\n\nElastic IPs are free as long as they’re attached to a running EC2 instance. You pay when they’re not in use to discourage hoarding them.\nIf you do take your server down for a short time, it’s no big deal. As of this writing, it’s 12 cents per day for a single IP. But do make sure to release the Elastic IP if/when you take your server down permanently.\n\n\nTo set up your Elastic IP, find it in the AWS console and allocate an address. Then you will associate your Elastic IP as the default public IP Address for your instance.\nNote that once you make this change, your server will no longer be available at its old IP Address, so you’ll have to SSH in at the new one. If you have SSH terminals open when you make the change, they will break.\n\n\n\n\n\n\nNote\n\n\n\nNext time you stand up a server, you should start by giving it an Elastic IP so you are immediately using it’s permanent IP Address. The labs in this book are ordered to promote learning, not the right order to configure things.\n\n\n\n\n13.4.2 Step 2: Buy a domain\nYou can buy a domain from any of the many domain purchasing services on the web. This won’t be free, but many domains are very cheap.\nThe easiest place to buy a domain is via AWS’s Route53 service, but you can feel free to use another provider. I usually use Namecheap just because all of the domains I own are there.\n\n\n13.4.3 Step 3: Configure DNS\nOnce you’ve got your domain, you have to configure your DNS. You’ll have to create 2 A records – one each for the \\(\\text{@}\\) host and the \\(\\text{*}\\) host pointing to your IP and one for the CNAME at the \\(\\text{www}\\) with the value being your bare domain.\nExactly how you configure this will depend on the domain name provider you choose. In NameCheap, you configure this via a table under Advanced DNS, which looks like this.\n\n\n\nType\nHost\nValue\nTTL\n\n\n\n\nA Record\n\\(\\text{*}\\)\n\\(\\text{64.56.223.5}\\)\nAutomatic\n\n\nCNAME Record\n\\(\\text{www}\\)\n\\(\\text{do4ds-lab.shop}\\)\nAutomatic\n\n\nA Record\n\\(\\text{@}\\)\n\\(\\text{64.56.223.5}\\)\nAutomatic\n\n\n\nI would recommend sticking with the default for TTL.\n\n\n13.4.4 Step 4: Wait an annoyingly long time\nNow you just have to be patient. Unfortunately DNS takes time to propagate. After a few minutes (or hours?), your server should be reachable at your domain.\nIf it’s not (yet) reachable, try seeing if an incognito browser works because that sidesteps the browser level of caching. If it doesn’t, wait some more. When you run out of patience, try reconfiguring everything and check if it works now.\n\n\n\n\n\n\nTip\n\n\n\nWe still haven’t configured HTTPS, so you’ll need to manually input the URL as \\(\\text{http://}\\), because your browser will otherwise assume it’s HTTPS.\n\n\n\n\n13.4.5 Step 5: Add the Shiny app to your site\nNow that the Shiny app is at a stable URL, let’s put it on our site so people can look at our penguin size prediction model. I put the app at the subpath \\(\\text{/penguins}\\), so it’s now at \\(\\text{http://do4ds-lab.shop/penguins}\\).\nWe’re going to use something called an iFrame, which lets you embed one website inside another. An iFrame is a basic HTML construct and it’s easy to put one in a Quarto site.\n\n\n\n\n\n\nNote\n\n\n\nOnce you change your website to go over HTTPS in the next section, you’ll have to adjust the iFrame URL as well.\n\n\nIn Quarto, you can just add an html block to a any document and it will get loaded in automatically. I want the app on the landing page of my site, index.qmd. So I’ve added a block that looks like:\n\n\nindex.qmd\n\n&lt;iframe width=\"780\" height=\"500\" src=\"http://do4ds-lab.shop/penguins/\" title=\"Penguin Model Explorer\"&gt;&lt;/iframe&gt;"
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-    "text": "If you try to do an nslookup on some websites – like \\(do4ds.com\\), you’ll notice the IP address doesn’t actually take you to this book’s site. That’s because this book isn’t actually hosted directly on a server. It’s instead hosted on GitHub pages – so the IP addresses nslookup finds are the Google Pages servers, which themselves know how to resolve \\(do4ds.com\\).↩︎"
+    "text": "This is really a very shallow intro to DNS. If you want to go a little deeper, I highly recommend Julia Evans’s zines on a variety of technical topics, including DNS. You can find them at wizardzines.com.↩︎"
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     "title": "14  You should use SSL/HTTPS",
-    "section": "14.1 The problems https solves",
-    "text": "14.1 The problems https solves\nFor a long time, most web traffic was just plain http traffic.\nIf you recall, there used to be a lot of warnings around that you shouldn’t just connect to and use the WiFi at your neighborhood Starbucks. That was (mostly) because of the risks of using plain http traffic.\nOver the last 10 years or so, almost all web traffic has migrated to https, particularly since 2015 when Google Chrome began the process of marking any site using plain http as insecure. These days it’s actually pretty safe to use any random WiFi network you want – because of https.\nThe biggest risk with those public WiFi networks was that someone could compromise the router. If the router was compromised, there were two things a bad actor could do.\nhttp has no way to verify that the website you think you’re interacting with is actually that website. So a bad actor could mess with the router’s DNS resolution, and make it so that \\(bankofamerica.com\\) went to a lookalike website to capture your banking login. That’s called a man-in-the-middle attack.\nhttp traffic is also completely unencrypted. So that packet you’re sending would be just as readable by someone who installed spyware on the router that’s passing it along as by the website you intended to send it to. This is called a packet sniffing attack.\nBoth of these risks are defanged when you’re using https rather than plain http.\n\n\n\n\n\n\nWhat doesn’t https do?\n\n\n\nUsing SSL/TLS helps a lot with security – but it’s worth noting that it ends at the domain. Using https validates that you’ve gotten to the real example.com if that’s the website you think you’re visiting. It doesn’t in any way validate who owns example.com, whether they’re reputable, or whether you should trust them.\nThere are higher levels of SSL certification that do validate that, for example, the company that owns google.com is actually the company Google.\n\n\nHere’s the process of connecting to a website that uses https. Before your browser starts exchanging any real data with the website, the website sends over its signature, which is generated with its private certificate.\nYour computer checks this signature with a trusted certificate authority (CA) who has a copy of the site’s public certificate. Once your browser has verified that the signature is valid, you know that you’re actually communicating with \\(bankofamerica.com\\) and you’re not victim to a man-in-the-middle attack.\nOnce the verification process is done, your browser then establishes an encryption routine with the website on the other end. Only then does it start sending real data – now encrypted so that only the website on the other end can read the contents.\n\n\n\n\ngraph TD\n    A[Browser] --&gt;|Request| B[SSL Certificate]\n    B --&gt; |Sent| A\n    C[Certificate Authority] --&gt; |Verifies| B\n    A --&gt; |Consults| C"
+    "section": "14.1 What HTTPS does",
+    "text": "14.1 What HTTPS does\nHTTPS is the same as HTTP, but secured with a technology called SSL/TLS (secure sockets layer/transport layer security). SSL/TLS works by configuring the resource to provide an SSL certificate upon demand, which is used to verify the site’s identity and establish an encrypted session.\n\n\n\n\n\n\nSSL vs TLS\n\n\n\nTLS is actually what’s in use these, but you’ll mostly talk about SSL. TLS is the successor to SSL, but the configuration is identical, so most people didn’t update how they talk about it.\n\n\nYou use HTTPS constantly. Go to a website in your browser and look for a little lock icon near the search bar. That little lock indicates that the domain is secured using HTTPS. If you click on it, you can get more information about the site’s SSL certificate.\nIf you’re of a certain age, you may recall warnings that you shouldn’t use the WiFi at your neighborhood Starbucks. The issue was twofold.\nHTTP has no way to verify that the website you think you’re interacting with is actually that website. So a bad actor could put up a fake WiFi network that makes \\(\\text{bankofamerica.com}\\) resolve to a lookalike website to capture your banking information. That’s called a man-in-the-middle attack.\nAnd even if they didn’t do that, they could inspect the traffic going back and forth and just read whatever you’re sending over the web in what’s called a packet sniffing attack.\nIn 2015, Google Chrome began the process of marking any site using plain HTTP as insecure, which led to nearly complete adoption of HTTPS across the internet. The risk of both of these kinds of attacks has been neutered and it’s actually pretty safe to use any random WiFi network you want these days – because of HTTPS.\nAs a website administrator, securing your website or server with HTTPS is one of the most basic things you can do to make sure your website traffic is safe. You should always configure HTTPS for a public website – full stop.\nIt’s worth noting that this SSL/TLS security can be applied to a number of different application layer protocols, including (S)FTP and LDAP(S). You may run across these depending on your organization. In any case, the SSL/TLS part works the same and all that changes is what’s inside the secure digital envelope."
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-    "section": "14.2 Configuring https",
-    "text": "14.2 Configuring https\nThere are three steps to configuring https on a website you control – getting an SSL certificate, putting the certificate on the server, and making sure the server only accepts https traffic.\nIt used to be that getting an SSL certificate was somewhat of a pain. While it could cost less than $10 per year to get a basic SSL certificate for particular subdomains, getting a wildcard certificate that covered all the subdomains of a root domain could be quite pricey.\nThe main alternative at the time was to use a self-signed cert. With a self-signed cert, you would create a certificate yourself and add the certificate directly to any machine that needed to access that site. This is a pain. You need to share the certificate with everyone and get them to install it on their machine. Certificates do expire and so this would have to be periodically repeated. The alternative is just to ignore the scary warning that you might be the victim of a man-in-the-middle attack – and some software doesn’t even allow that.\nLuckily there’s now another option. With the rise of https everywhere, there’s now an organization called letsencrypt. It’s a free CA that issues basic SSL/TLS certificates for free. They even have some nice tooling that makes it super easy to create and configure your certificate right on your server.\nWhen you’re talking about communications that run entirely inside private networks, you have a choice to make. Large organizations often run their own private CA that verifies all the certificates inside your private network.\nThis is a bit of a hassle, since you’ve got to maintain the CA and configure every host inside the network to trust your private CA. Many organizations decide they’re fine with plain http communication within private networks.\nEither way, once you’ve configured your server with https, you generally want to shut down access via plain http, usually by redirecting http traffic, which comes in on port 80 to come in over https via port 443."
+    "section": "14.2 How SSL/TLS works",
+    "text": "14.2 How SSL/TLS works\nSSL/TLS uses public key encryption (remember, we learned about that in Chapter 8) to do two things – validate that the site you’re visiting is the site you intend and encrypt the traffic back and forth to the site.\nTo set up SSL for a website, you create or acquire an SSL certificate, which has a public and a private component (sound familiar?).1 Then, verify the public certificate with a trusted Certificate Authority (CA) and put the private certificate in the right place on the website.2\nThen, when you go to access that resource, the first thing your machine asks for is a signature. The site uses its private key to generate the signature and your machine verifies the signature against it’s internal trusted CA store.\nNow your machine knows it’s communicating with the right host on the other side and you’re not falling victim to a man-in-the-middle attack.\nOnce the verification process is done, your machine and the remote on the other side create temporary session keys to establish encryption with the website on the other end.3 Only then does it start sending real data, now encrypted securely inside a digital envelope."
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-    "text": "14.3 Comprehension Questions\n\nWhat are the two risks of using plain http and how does https mitigate that?\nWrite down a mental map of how SSL secures your web traffic. Include the following: public certificate, private certificate, certificate authority, encrypted traffic, port 80, port 443"
+    "section": "14.3 Getting and using SSL certificates",
+    "text": "14.3 Getting and using SSL certificates\nWhen you buy a computer, it comes configured out of the box to trust a small number of official CAs. So if you’re a website wanting to get a certificate, you generally want to get it from one of those CAs.\nThis used to be kinda a pain. The CAs charged to issue certificates. While it was only $10 per year to for a basic SSL certificate, they typically would only cover a single subdomain. A wildcard certificate to cover all the subdomains of a root domain was expensive enough to discourage hobbyists.\nIf you wanted a free certificate, your only option was to use a self-signed certificate, which you’d create similarly to creating an SSH key. This was a pain because you had to manually add the public certificate to the CA store of every machine that would be accessing the site, and then re-add it when the certificate expired.4\nLuckily there’s now another option. For most small organizations, I recommend getting a free SSL certificate from the nonprofit CA Let’s Encrypt. They even have some nice tooling that makes it super easy to create and configure your certificate right on your server.\nFor most organizations, using a public CA to get SSL on public-facing resources is sufficient and use plain HTTP inside private networks. Some large organizations want to encrypt their private traffic as well and run their own private CA. If this is the case, your organization’s policies will make it clear. This can be a pain, because you’ve got to make sure every host inside the network trusts the private CA.\nOnce you’ve configured SSL/TLS, you generally want to only allow HTTPS traffic to your site. You’ll accomplish this by redirecting all HTTP traffic on port \\(80\\) to come in via HTTPS on port \\(443\\).\nSome web applications support configuring a certificate directly, while others only accept HTTP traffic, so you’d need to do SSL termination with a proxy in front of the application."
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-    "section": "14.4 Lab: Configure SSL",
-    "text": "14.4 Lab: Configure SSL\nWe’re going to use letsencrypt’s certbot utility to automatically generate an SSL certificate, share it with the CA, install it on the server, and even update your nginx configuration.\nFor anyone who’s never dealt with self-signing certificates in the past, let me tell you, the fact that it does this all automatically is magical!\n\n14.4.1 Step 1: Update Nginx configuration\nIn our nginx configuration, we’ll need to add a line certbot will use to know which site to generate the certificate for.\nSomewhere inside the nginx configuration’s server block, add\n\n\n/etc/nginx/nginx.conf\n\nserver_name do4ds-lab.shop www.do4ds-lab.shop;\n\nsubstituting in your domain for mine. Make sure to include both the bare domain and the www subdomain.\n\n\n14.4.2 Step 2: Certbot does its thing\nIf you google “configure nginx with letsencrypt”, there’s a great article by someone at Nginx walking you through the process.\nAs of this writing, that was as simple as running these lines on the server\n\n\nTerminal\n\nsudo apt-get install certbot python3-certbot-nginx \nsudo systemctl restart nginx \nsudo certbot --nginx -d do4ds-lab.shop -d www.do4ds-lab.shop\n\nBefore you move along, I’d recommend you take a moment and inspect the /etc/nginx/nginx.conf file to look at what certbot added.\nYou’ll notice two things. You’ll notice that the listen 80 is gone from inside the server block. We’re no longer listening for http traffic.\nInstead there’s a listen 443 – the default port for https, and a bunch of stuff that tells Nginx where to find the certificate on the server.\nScrolling down a little, there’s a new server block that is listening on 80. This block returns a 301, which you might recall is a redirect code (specifically for a permanent redirect) sending all http traffic to https.\n\n\n14.4.3 Step 3: Let RStudio know it’s on https\nBefore we exit and test it out, let’s do one more thing. RStudio does a bunch of sending traffic back to itself. For that reason, the /rstudio proxy location also needs to know to upgrade traffic from http to https.\nSo add the following line to the Nginx config:\n\n\n/etc/nginx/nginx.conf\n\nproxy_set_header X-Forwarded-Proto https;\n\nThis line adds a header to the traffic the proxy forwards specifying the protocol to be https. RStudio Server uses this header to know that it should send traffic back to itself using https, not http.\nOk, now try it by going to the URL your server is hosted at, and you’ll find that…it’s broken again.\nBefore you read along, think for just a moment. Why is it broken?\n\n\n14.4.4 Step 4: Configure security groups\nIf your thoughts went to something involving ports and AWS security groups, you’re right!\nBy default, our server was open to SSH traffic on port 22. Since then, we may have opened or closed port 80, 8000, 8787, and/or 8080.\nBut now that we’re exclusively sending https traffic into the proxy on 443 and letting the proxy redirect things elsewhere. So you have to go into the security group settings and change it so there are only 2 rules – one that allows SSH traffic on 22 from anywhere and one that allows https traffic on 443 from anywhere.\nIt’s up to you whether you want to leave port 80 open. If you do, it will redirect people to https on 443. If you close it entirely, people who come to port 80 will just be blocked and will eventually get a timeout. That shouldn’t be an issue as all modern browsers default to https.\n\n\n\n\n\n\nNote\n\n\n\nIf you decided to only configure one service on the server, you could have a much simpler setup. Neither RStudio Server nor Plumber support direct configuration of a SSL certificate, so you would still need a proxy – though it could be a much simpler configuration that just passes traffic at the root / on to your service at a different port.\nJupyterHub can be configured directly with an SSL certificate, so you would just configure JupyterHub to be aware of the SSL certificate and put itself on port 443.\n\n\n\n\n14.4.5 Step 5: Check it out!\nNOW you should be able to go to &lt;your-domain&gt;/rstudio and get to RStudio, &lt;your-domain&gt;/jupyter to get to JupyterHub, and &lt;your-domain&gt;/penguins to get the API! Voila!\nAnd you should still be able to SSH into your server on your domain.\nAt this point your server is fully configured. You have a server hosting three real data science services available on a domain of your choosing protected by https. You can really use this server to do real data science work.\nThat’s not to say this is fully enterprise-ready. If you’re working on a small team or at a small organization, this may be sufficient. But if you’re working at a large organization, your IT/Admin group is going to have other concerns.\nYou can learn more about what those concerns are in the last section of this book, starting with ?sec-4-intro."
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-    "section": "15.1 Computers are (just) addition factories",
-    "text": "15.1 Computers are (just) addition factories\nYou’re probably aware that everything you’ve ever seen on a computer – from this book to your work in R or Python, your favorite internet cat videos, and Minecraft – it’s just 1s and 0s.\nThe theory of why this works is deep and fascinating.1 Luckily, the amount of computational theory you need to understand to be an effective data scientist can be can be summarized in three sentences:\n\nEverything on a computer is represented by a (usually very large) number.\nAt a hardware level the only thing computers do is add these numbers together.\nModern computers add very quickly and very accurately.\n\nThis means that for your day-to-day work, you can think of a computer as just a big factory for doing additions.\nEvery bit of input your computer gets is turned into an addition problem, processed, and the results are reverted back into something we interpret as meaningful.\nThe addition assembly line itself – where the work actually gets done – is referred to as compute. It’s where 2+2 gets turned into 4, and where 345619912 + 182347910 gets turned into 527967822.\nThere are a number of different kinds of compute, but they all basically work the same. The total speed is determined by two factors – the number of conveyor belts (cores) and the speed at which each belt is running (clock speed).\nWe’re going to spend some time considering the three important resources – compute, memory, and storage – you have to allocate and manage on your computer or server. We’re going to spend some time generally exploring what each one is and then get into how you should think about each specifically with regard to data science."
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-    "section": "15.2 Recommendation 1: Fewer, faster CPU cores",
-    "text": "15.2 Recommendation 1: Fewer, faster CPU cores\nAll computers have a central processing unit (CPU). These days, most consumer-grade laptops have between 4 and 16 cores, and may have additional capabilities that effectively doubles that number. So most laptop CPUs can do between 4 and 32 simultaneous addition problems.\nClock speeds are measured in operations per second or hertz (hz). The cores in your laptop probably run between two and five gigahertz (GHz), which means between 2 and 5 billion operations per second when running at full speed.\nFor decades, many of the innovations in computing were coming from increases in clock speed, but raw increases in speed have fallen off a lot in the last few decades. The clock speeds of consumer-grade chips increased by approximately 10x during the 90s, by 2-3x in the 2000s, and somewhere between not at all and 1.5x in the 2010s.\nBut computers have continued getting a lot faster even as the increase in clock speeds has slowed. The increase has mostly come from increases in the number of cores, better software usage of parallelization, and innovative chip architectures for special-purpose usage.\nR and Python are single-threaded. Unless you’re using special libraries for parallel processing, you’ll end up red-lining a single CPU core while the other just look on in silence.\nTherefore for most R and Python work, single core clock speed matters more than the number of cores, and fewer, faster cores are usually preferable to many slower\nYou’re probably not used to thinking about this tradeoff from buying a laptop or phone. The reality is that modern CPUs are pretty darn good and you should just buy the one that fits your budget.\nIf you’re standing up a server, you often do have an explicit choice between more slower cores and fewer faster ones. In AWS, the instance type is what dictates the tradeoff – more on this below.\nIf you’re running a multi-user server, the number of cores you need is really hard to estimate. If you’re doing non-ML tasks like counts and dashboarding or relatively light-duty machine learning I might advise the following:\n\\[\n\\text{n cores} = \\text{1 core per user} + 1\n\\]\nThe spare core is for the server to do its own operations apart from the data science usage. On the other hand, if you’re doing heavy-duty machine learning or parallelizing jobs across the CPU, you may need more cores than that."
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-    "section": "15.3 Recommendation 2: Get as much RAM as feasible",
-    "text": "15.3 Recommendation 2: Get as much RAM as feasible\nYour computer’s random access memory (RAM) is its short term storage. In the computer as adding factory analogy, the RAM is like the stock that’s sitting out on the factory floor ready to go right on an assembly line.\nRAM is very fast to for your computer to access, so you can read and write to it very quickly. The downside is that it’s temporary. When your computer turns off, the RAM gets wiped.2\n\n\n\n\n\n\nNote\n\n\n\nYou probably know this, but memory and storage is measured in bytes prefixed by metric prefixes. Common sizes for memory these days are in gigabytes (billion bytes) and terrabytes (trillion bytes). Some enterprise data stores run on the scales of thousands of terrabytes (pettabytes) or even thousands of pettabytes (yottabytes).\n\n\nModern consumer-grade laptops come with somewhere between 4 and 16 Gb of memory.\nIn most cases, R and Python have to load all of your data into memory. Thus, the size of the data you can use is limited to the size of your machine’s RAM. Most other limits of your machine will just result in things being slower than you’d really want, but trying to load too much data into memory will result in a session crash, and you won’t be able to do your analysis.\n\n\n\n\n\n\nNote\n\n\n\nYou can get around the in-memory limitation by using a database or libraries that facilitate on-disk operations like Apache Arrow or dask.\n\n\nBecause you’ll often be doing some sort of transformation that results in invisible data copies and your computer can’t devote all of its memory, you’ll want to leave plenty of room over your actual data size.\nIt’s easy to say that you’ll always want more RAM, but a rough rule of thumb for whether you’ve got enough is the following:\n\\[\\text{Amount of RAM} = \\text{max amount of data} * 3\\]\nIf you’re thinking about running a multi-user server, you’ll want to think about the maximum simultaneous number of users on the server, the most data each one would want to have loaded into memory and use that for your max amount of data"
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-    "text": "15.4 Recommendation 3: Get lots of storage, it’s cheap\nRelative to the RAM that’s right next to the factory floor, your computer’s storage is like the warehouse in the next building over. It’s much, much slower to get things from storage than RAM, but it’s also permanent once its stored there.\nUp until a few years ago, hard drives were very slow. HDD drives have a bunch of magnetic disks that spin very fast (5,400 and 7,200 RPM are common speeds). Magnetized read/write heads move among the disks and save and read your data.\nWhile 7,200 RPM is very fast, there were still physical moving parts, and reading and writing data was very slow by computational standards.\nIn the last few years, solid-state drives (SSDs) have become more-or-less standard in laptops. SSDs, which are collections of flash memory chips with no moving parts, are up to 15x faster than HDDs. They also can take a wider variety of shapes and sizes, and are more reliable and durable because they have no moving parts. The main drawback is that they’re usually more expensive per byte, but prices are still quite reasonable.\nMany consumer laptops have only an SSD at this point. Some desktops and high-end laptops combine a smaller SSD with a larger HDD.\nAs for storage – get a lot – but don’t think about it too hard, because it’s cheap. Both a 1TB SSD and a 4TB HDD are around $100. Storage is cheap enough these days that it is almost always more cost efficient to buy more storage rather than making a highly-paid professional spend their time trying to figure out how to move things around.\nOne litmus test of an IT organization that is well-equipped to support data science is whether they understand this. Smart organizations know that just getting more storage is almost always worth the cost in terms of the time of admins and data scientists.\nIf you’re running a multi-user server, the amount of storage you need depends a lot on your data and your workflows. A reasonable rule of thumb is to choose\n\\[\n\\text{Amount of Storage} = \\text{data saved} + 1Gb * \\text{n users}\n\\]\nOne thing to keep in mind is that you can basically just choose storage to match your data size and add a Gigabyte per person.\nAside from actual data, the amount of space each person needs on the server is small. Code is very small and it’s rare to see R and Python packages take up more than a few dozen Mb per data scientist.\n\n\n\n\n\n\nNote\n\n\n\nIf you’re working with a professional IT admin, they may be concerned about the storage implications of having package copies for each person on their team. I’ve heard this concern a lot from IT/Admins thinking prospectively about running their server and almost never of a case where it’s actually been a problem.\nFinding a person who has more than a few hundred Mb of packages would be very strange indeed.\n\n\nSo it really comes down to how much data you expect to save on the server. In some organizations, each data scientist will save dozens of flat files of a Gb or more for each of their projects. That team would need a lot of storage. In other teams, all the data lives in a database and you basically don’t need anything beyond that 1 Gb per person.\nIf you’re operating in the cloud, this really isn’t an important choice. As you’ll see in the lab, upgrading the amount of storage you have is a really trivial operation, requiring at most a few minutes of downtime. Choose a size you guess will be adequate and add more if you need."
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+    "text": "14.4 Comprehension Questions\n\nWhat are the two risks of using plain HTTP and how does HTTPS mitigate them?\nWrite down a mental map of how SSL secures your web traffic. Include the following: public certificate, private certificate, certificate authority, encrypted traffic, port 80, port 443"
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-    "text": "15.5 Recommendation 4: Get a GPU…maybe\nThe most common special architecture chips is the graphical processing unit (GPU). GPUs are specialized chips used for tasks like editing photo or videos, rendering video game graphics, some kinds of machine learning, and (yes) Bitcoin mining.\nLike a CPU, a GPU is just an addition factory but with a different architecture. A CPU has a few fast cores, so it can only work on a few problems simultaneously, but it does them very fast. In contrast, a GPU takes the opposite approach, with many slower cores. Where a consumer-grade CPU has 4-16 cores, mid-range GPUs have 700-4,000 cores, but each one runs between 1% and 10% the speed of a CPU core.\nFor GPU-centric tasks, the overwhelming parallelism of a GPU is more important than the speed of any individual core, and GPU computation can be dramatically faster. For the purposes of data science, many popular machine learning techniques – including neural networks, XGBoost, and other tree-based models – potentially run much much faster on GPUs relative to CPUs.\nSome machines are also adding other types of specialized chips to do machine learning – though these generally aren’t accessible for training models. For example, iPhone TODO.\nThe choice of whether you need a GPU to do your work will really depend on what you’re doing and your budget.\nOnly certain kinds of data science tasks are even amenable to GPU-backed acceleration. Many data science tasks can only be done in sequence others can be parallelized, but splitting it into a small number of CPU cores is perfectly adequate. For the most part, the things that will benefit most from GPU computing are training highly parallel machine learning models like a neural network or tree-based models.\nIf you do have one of these use cases, GPU computing can massively speed up your computation – making models trainable in hours instead of days.\nIf you are planning to use cloud resources for your computing, GPU-backed instances are quite pricey, and you’ll want to be careful about only putting those machines up when you’re using them.\nIt’s also worth noting that using a GPU won’t happen automatically. The tooling has gotten good enough that it’s usually pretty easy to set up, but your computer won’t train your XGBoost models on your GPU unless you tell it to do so.\nBecause GPUs are expensive, I generally wouldn’t bother with GPU-backed computing unless you’ve already tried without a GPU and find that it takes too long to be feasible."
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-    "text": "15.6 Scaling Servers\nThere are two reasons you might need to scale to a bigger server. The first reason that people think of most often is because people are running big jobs. This can happen at any scale of organization. There are data science teams of one who have use cases that necessitate terrabytes of data. There are also issues that come up as your data science team gets bigger.\nEither way, there are two basic options for how to scale your data science workbench. The first is vertical scaling, which is just a fancy way of saying get a bigger server. If your budget allows it, you shouldn’t feel shy about vertically scaling – the complexity of managing a t3.nano with 2 cores and 0.5 Gb of memory is exactly the same as a C5.24xlarge with 96 cores and 192 Gb of memory. In fact, the bigger one may well be easier to manage, since you won’t have to worry about running low on resources.\nAWS resource costs generally scale linearly within a server family. But there are limits. As of this writing, AWS’s general-use instance types max out at 96-128 cores these days. That’s probably sufficient for many workloads, but if you’ve got an RStudio Server with 50 concurrent users doing reasonably heavy compute loads, that can quickly get eaten up.\nThe nice thing about being in the cloud is that vertical scaling is almost trivially easy, as we’ll see in the lab in this chapter.\nIf your needs grow beyond the capacity of a single server, you’re starting to get into horizontal scaling territory. Once you’re thinking about horizontal scaling, you should almost certainly get an IT/Admin professional involved. See Chapter 19 for more on how to talk to them about it."
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-    "text": "15.7 AWS Costs\nThat said, a modestly-sized server is still pretty cheap if you’re only putting it up for a short amount of time.\nI’m writing this on a 2021 M1 Macbook Pro with 10 CPUs and 32 Gb of memory. If you wanted that same computational power from an AWS server, it’s roughly comparable to a t3.2xlarge – with 8 CPUs and 32Gb of memory. That server costs is $0.33 an hour. So a full year running full time for an instance is nearly $3,000, but if you’re only running that instance for a little while – say, the few hours it’ll take you to complete this lab – it will probably only be a few dollars."
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-    "section": "15.8 Comprehension Questions",
-    "text": "15.8 Comprehension Questions\n\nThink about the scenarios below – which part of your computer would you want to upgrade to solve the problem?\n\nYou try to load a big csv file into pandas in Python. It churns for a while and then crashes.\nYou go to build a new ML model on your data. You’d like to re-train the model once a day, but it turns out training this model takes 26 hours on your laptop.\nYou design an visualization Matplotlib , and create a whole bunch in a loop, you want to parallelize the operation. Right now you’re running on a t2.small with 1 CPU.\n\nDraw a mind map of the following: CPU, RAM, Storage, Operations Per Second, Parallel Operations, GPU, Machine Learning\nWhat are the architectural differences between a CPU and a GPU? Why does this make a GPU particularly good for Machine Learning?\n15.9 AWS Instance Classes for Data Science\nAWS offers a variety of different EC2 instance types. There are a few different types you’ll probably consider, here’s a quick guide to the types most commonly used for data science purposes.\nWithin each family, there are different sizes available, ranging from nano to 2xl. Instances are denoted by &lt;family&gt;.&lt;size&gt;. So, for example, when we put our instance originally on a free tier machine, we put it on a t2.micro.\nIn most cases, going up a size doubles the amount of RAM, the number of cores, and the cost.\n\n\n\n\n\n\n\nInstance Type\nNotes\n\n\n\n\nt3\nThe “standard” configuration. Relatively cheap per core/Gb RAM.\ngood b/c of instance credits, limited size\n\n\nC\nFaster CPUs\n\n\nR\nHigher ratio of RAM to CPU\n\n\nP\nGPU instances, very expensive\n\n\n\n15.10 Lab: Changing Instance Size\n\nOk, now we’re going to experience the real magic of the cloud – flexibility.\nWe’re going to upgrade the size of our server in just a minute or two.\n\n15.10.1 Step 1: Confirm current server size\nFirst, let’s confirm what we’ve got available. You can check the number of CPUs you’ve got with lscpu in a terminal. Similarly, you can check the amount of RAM with free -h. This is just so you can prove to yourself later that the instance really changed.\n\n\n15.10.2 Step 2: Change the instance type and bring it back\nNow, you can go to the instance page in the AWS console. The first step is to stop (not terminate!) the instance. This means that changing instance type does require some downtime for the instance, but it’s quite limited.\nOnce the instance has stopped, you can change the instance type under Actions &gt; Instance Settings. Then start the instance. It’ll take a few seconds to start the instance.\nAnd that’s it.\n\n\n15.10.3 Step 3: Confirm new server size\nSo, for example, I changed from a t2.micro to a t2.small. Both only have 1 CPU, so I won’t see any difference in lscpu, but running free -h before and after the switch reveals the difference in the total column:\ntest-user@ip-172-31-53-181:~$ free -h\n               total        used        free      shared  buff/cache   available\nMem:           966Mi       412Mi       215Mi       0.0Ki       338Mi       404Mi\nSwap:             0B          0B          0B\ntest-user@ip-172-31-53-181:~$ free -h\n               total        used        free      shared  buff/cache   available\nMem:           1.9Gi       225Mi       1.3Gi       0.0Ki       447Mi       1.6Gi\nSwap:             0B          0B          0B\nI got twice as much RAM!\nThere are some rules around being able to change from one instance type to another…but this is an amazing superpower if you’ve got variable workloads or a team that’s growing. The ability to scale a machine so easily is a game-changer.\nThe work we did in earlier lab chapters, for example adding the elastic IP and daemonizing JupyterHub, are the reason that we’re able to bring it back up so smoothly.\nIt’s similarly easy to resize the EBS volume attached to your server for more storage.\nThere are two caveats worth knowing for EBS:\n\nYou can only automatically adjust volume sizes up, so you’d have to manually transfer all of your data if you ever wanted to scale back down.\nIf you resize the volume, you’ll also have to adjust the Linux filesystem so it knows about the new space available. AWS has a great walk through called Extend a Linux filesystem after resizing the volume that I recommend you follow."
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+    "section": "14.5 Lab: Configure SSL",
+    "text": "14.5 Lab: Configure SSL\nWe’re going to use Let’s Encrypt’s certbot utility to automatically generate an SSL certificate, share it with the CA, install it on the server, and even update your NGINX configuration.\nIf you’ve never had to manually configure SSL in the past, let me tell you, this is magical!\n\n14.5.1 Step 1: Follow instructions to add SSL for NGINX\nUsing Let’s Encrypt to add an SSL certificate to NGINX configuration is a super common task. As of this writing, there’s a great blog post entitled Using Free Let’s Encrypt SSL/TLS Certificates with NGINX. I’d encourage you to look for that article (or something similar) and follow the steps there.\nAt a high level, what you’ll do is\n\nConfigure the NGINX configuration to know what domain its on.\nInstall certbot on the system.\nRun certbot to get the certificate, apply it to the server, and update the NGINX configuration.\n\nBefore you move along, I’d recommend you take a moment and inspect the /etc/nginx/nginx.conf file to look at what certbot added.\nRelative to the old version, you’ll notice two things. First, the line that read listen 80 is gone from the server block because we’re no longer listening for HTTP traffic. In it’s place, there’s now a listen 443 along with a bunch of stuff that tells NGINX where to find the certificate on the server.\nScrolling down a little, there’s a new server block that is listening on \\(80\\). This block returns a 301 status code (permanent redirect) and sends traffic to HTTPS on \\(443\\).\n\n\n14.5.2 Step 2: Let RStudio Server know it’s on HTTPS\nBefore we exit and test it out, let’s do one more thing. As mentioned when we configured NGINX the first time, RStudio Server does a bunch of proxying traffic back to itself, so it needs to know that it’s on HTTPS.\nYou can let RStudio Server know that it’s on HTTPS by adding a header to all traffic letting RStudio Server know the protocol is HTTPS. You can add this line to your nginx.conf:\n\n\n/etc/nginx/nginx.conf\n\nproxy_set_header X-Forwarded-Proto https;\n\nOk, now try to visit RStudio Server at your URL, and you’ll find that…it’s broken again.\nBefore you read along, think for just a moment. Why is it broken?\n\n\n14.5.3 Step 3: Configure security groups\nIf your thoughts went to something involving ports and AWS security groups, you’re right!\nBy default, our server was open to SSH traffic on port \\(22\\). Since then, we may have opened or closed port \\(80\\), \\(8000\\), \\(8080\\), \\(8787\\), and/or \\(3838\\).\nBut now that we’re exclusively sending HTTPS traffic into the proxy on \\(443\\) and letting the proxy redirect things elsewhere. So you have to go into the security group settings and change it so there are only 2 rules – one that allows SSH traffic on \\(22\\) and one that allows HTTPS traffic on \\(443\\).\nIt’s up to you whether you want to leave port \\(80\\) open. If you do, it will redirect people to HTTPS on \\(443\\). If you close it entirely, people who come to port \\(80\\) will be blocked and will eventually get a timeout. If people are used to coming to the server via HTTP, it might be nice to leave \\(80\\) open so they get a nice redirect experience instead of getting confusingly blocked.\n\n\n14.5.4 Step 4: We did it!\nThis is the end of the labs in this book.\nAt this point your server is fully configured. You have three real data science services available on a domain of your choosing protected by HTTPS and you can SSH in to do admin work.\nTake a moment to celebrate. It’s very cool to be able to stand up and administer your own data science workbench. If you’re working at a small organization or are a hobbyist, you can really use this server to do real data science work.\nBut this server isn’t enterprise-ready. If you work at a large organization or one with stringent security or privacy rules, your IT/Admin group is going to have concerns. Read on to learn more about what they are and why they’re completely valid."
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-    "text": "The reason why this is the case and how it works is fascinating. If you’re interested, it comes back to Alan Turing’s famous paper on computability. I recommend The Annotated Turing: A Guided Tour Through Alan Turing’s Historic Paper on Computability and the Turing Machine by Charles Petzold for a surprisingly readable walkthrough of the paper.↩︎\nYou probably don’t experience this personally. Modern computers are pretty smart about dumping RAM onto the hard disk before shutting down, and bringing it back on startup, so you usually won’t notice this happening.↩︎"
+    "text": "Like with SSL, this makes more sense if you think key where you see private and lock where you see public.↩︎\nThe CA verifies the certificate by signing it. Your machine just keeps public certificates for the CAs. Then, when it gets an SSL certificate that’s signed by one of those CAs, it can validate that the CA actually stamped this certificate as valid.↩︎\nUnlike the asymmetric encryption used by SSL and SSH for the public key encryption, the session keys are symmetric, so they work the same in both directions.↩︎\nYou also could skip that step, in which case you got the session encryption benefits of SSL/TLS, but not the verification.↩︎"
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-    "text": "What enterprise IT is about\nAs a data scientist, your primary concern about your data science environment is that it’s useful. You want to be able to get all the data you want at your fingertips.\nMany data scientists in enterprises find that this desire runs headlong into requirements from their organization’s IT/Admin teams.\nThis can be extremely frustrating, so it’s helpful to understand the concerns enterprise IT/Admins have in mind. Broadly, IT/Admins care about the security and stability of the systems they control.\nGreat IT/Admin teams also care about the usefulness of the system to users (that’s you), but it’s usually a distant third. And there is sometimes a tension here. After all the only system that’s completely secure is the one that doesn’t exist at all.\nBut that’s not always the case. Often, there’s a lot to gain by partnering with the IT/Admin team at your organization. You may be primarily focused on getting stuff done minute-to-minute, but a data science platform that is insecure and allows bad actors to break in and steal data is not useful. And one where you can do what you want but end up crashing the workbench for 50 other users is ultimately self-defeating.\nBalancing security, stability, and usefulness is always about tradeoffs. Great IT/Admin organizations are constantly in conversations with other parts of the organization to figure out the right stance for your organization given the set of tradeoffs you face.\nUnfortunately, many IT/Admin organizations don’t act that way – they act as gatekeepers to the resources you need to do your job. That means you’ll have to figure out how to communicate with those teams, understand what matters to them, help them understand what matters to you, and reach acceptable organizational outcomes.\nYou probably already have a good understanding of how a data science environment can be useful – but what about secure and stable. What do they mean?\nSecurity is about making sure that the right people can interact with the systems they’re supposed to and that unauthorized people can’t.\nIT security professionals think about security in layers. And while you’ve done a good job setting your server up to comply with basic security best practices, there are no layers. That server front door is open to the internet. Literally anyone in the world can come to that authentication page for your RStudio Server or JupyterHub and start trying out passwords. That means you’re just one person choosing the password password away from a bad actor getting access to your server.\nLest you think you’re immune because you’re not an interesting target, there are plenty of bots out there randomly trying to break in to every existing IP address, not because they care about what’s inside, but because they want to co-opt your resources for their own purposes like crypto mining or virtual DDOS attacks on Turkish banks.1\nMoreover, security and IT professionals aren’t just concerned with bad actors from outside (called outsider threat) or even someone internal who decides to steal data or resources (insider threat). They are (or at least should be) also concerned with accidents and mistakes – data that is accidentally permanently deleted is bad the same way stolen data is bad.\nStability is ensuring enterprise-grade systems are around when people need them, and that they are stable during whatever load they face during the course of operating. The importance of stability tends to rise along with the scale of the team and the centrality of their operations to the functioning of your organization.\nIf you’re a team of three data scientists who sit in a room together, it probably won’t be a huge deal if someone accidentally knocks your data science workbench offline for 30 minutes because they tried to run a job that was too big. You’re probably all sitting in the same room and you can learn something from the experience.\nThat’s not the case when you get to enterprise-grade tooling. An enterprise-grade data science workbench probably supports dozens or hundreds of professionals across multiple teams. The server being down isn’t a sorta funny occurrence you can all fix together – it’s a problem that must be fixed immediately – or even better avoided altogether.\nIT/Admins think hard about how to provide resources in a way that avoids having servers go down because they’re hitting resource constraints.\nOne thing that is almost certain to be untrue in an enterprise context is that you’ll have root access as a user of the system.\nThere is no one-size-fits-all (or even most) position for security. Instead, great security teams are constantly articulating and making decisions about tradeoffs."
+    "text": "What enterprise IT is about\nAs a data scientist, your primary concern about your data science environment is that it’s useful. You want to be able to get all the data you want at your fingertips.\nMany data scientists in enterprises find that this desire runs headlong into requirements from their organization’s IT/Admin teams.\nThis can be extremely frustrating, so it’s helpful to understand the concerns enterprise IT/Admins have in mind. Broadly, IT/Admins care about the security and stability of the systems they control.\nGreat IT/Admin teams also care about the usefulness of the system to users (that’s you), but it’s usually a distant third. And there is sometimes a tension here. After all the only system that’s completely secure is the one that doesn’t exist at all.\nBut that’s not always the case. Often, there’s a lot to gain by partnering with the IT/Admin team at your organization. You may be primarily focused on getting stuff done minute-to-minute, but a data science platform that is insecure and allows bad actors to break in and steal data is not useful. And one where you can do what you want but end up crashing the workbench for 50 other users is ultimately self-defeating.\nBalancing security, stability, and usefulness is always about tradeoffs. Great IT/Admin organizations are constantly in conversations with other parts of the organization to figure out the right stance for your organization given the set of tradeoffs you face.\nUnfortunately, many IT/Admin organizations don’t act that way – they act as gatekeepers to the resources you need to do your job. That means you’ll have to figure out how to communicate with those teams, understand what matters to them, help them understand what matters to you, and reach acceptable organizational outcomes.\nYou probably already have a good understanding of how a data science environment can be useful – but what about secure and stable. What do they mean?\nSecurity is about making sure that the right people can interact with the systems they’re supposed to and that unauthorized people can’t.\nIT security professionals think about security in layers. And while you’ve done a good job setting your server up to comply with basic security best practices, there are no layers. That server front door is open to the internet. Literally anyone in the world can come to that authentication page for your RStudio Server or JupyterHub and start trying out passwords. That means you’re just one person choosing the password password away from a bad actor getting access to your server.\nLest you think you’re immune because you’re not an interesting target, there are plenty of bots out there randomly trying to break in to every existing IP Address, not because they care about what’s inside, but because they want to co-opt your resources for their own purposes like crypto mining or virtual DDOS attacks on Turkish banks.1\nMoreover, security and IT professionals aren’t just concerned with bad actors from outside (called outsider threat) or even someone internal who decides to steal data or resources (insider threat). They are (or at least should be) also concerned with accidents and mistakes – data that is accidentally permanently deleted is bad the same way stolen data is bad.\nStability is ensuring enterprise-grade systems are around when people need them, and that they are stable during whatever load they face during the course of operating. The importance of stability tends to rise along with the scale of the team and the centrality of their operations to the functioning of your organization.\nIf you’re a team of three data scientists who sit in a room together, it probably won’t be a huge deal if someone accidentally knocks your data science workbench offline for 30 minutes because they tried to run a job that was too big. You’re probably all sitting in the same room and you can learn something from the experience.\nThat’s not the case when you get to enterprise-grade tooling. An enterprise-grade data science workbench probably supports dozens or hundreds of professionals across multiple teams. The server being down isn’t a sorta funny occurrence you can all fix together – it’s a problem that must be fixed immediately – or even better avoided altogether.\nIT/Admins think hard about how to provide resources in a way that avoids having servers go down because they’re hitting resource constraints.\nOne thing that is almost certain to be untrue in an enterprise context is that you’ll have root access as a user of the system.\nThere is no one-size-fits-all (or even most) position for security. Instead, great security teams are constantly articulating and making decisions about tradeoffs."
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     "text": "Labs in this Section\nThere are no labs in this section. This section is about how to interact with a professional IT/Admin group. Since it’s about work you really shouldn’t undertake yourself, there are no labs for you to DIY these things.\nIf you want to go deeper into any of the topics, there are plenty of great resources online – a google search should turn them up quickly"
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     "text": "Yes, these both really happened.↩︎"
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-    "title": "16  Open Source Data Science in the Enterprise",
-    "section": "16.1 Data Science Sandboxes",
-    "text": "16.1 Data Science Sandboxes\nIn Chapter 5 on code promotion, we talked about wanting to create separate dev/test/prod environments for your data science assets. In many organizations, your good intentions to do dev/test/prod work for your data science assets are insufficient.\nIn the enterprise, it’s often the case that IT/Admins are required to ensure that your dev work can’t wreak havoc on actual production systems. If you can work with your organization’s IT/Admins to get a place to work, this is a good thing! It’s nice to have a sandbox where you can do whatever you want with no concern of breaking anything real.\nThere are three components to a data science sandbox:\n\nFree read-only access to real data\nRelatively broad access to packages\nA process to promote data science projects into production\n\nMany IT/Admins are familiar with building workbenches for other sorts of software development tasks, so they may believe they understand what you need.\n\n16.1.0.1 Read-Only Data Access\nIn software engineering, the shape of the data in the system matters a lot, but the content doesn’t matter much. If you’re building software to do inventory tracking, you’re perfectly fine testing on data that isn’t of a real inventory as long as it’s formatted the same as real inventory data. That means that a software engineering dev environment doesn’t require access to any real data.\nIT/Admins may believe that providing a standalone or isolated environment for you to work in is sufficient. You’re probably wincing reading this knowing that it’s not the case.\nAs you know, data science isn’t like that. In data science, what you’re doing in dev environments – exploring relationships between variables, visualizing, training models, looks much more different from test and prod than for software engineering. You need a place where you can work with real data, explore relationships in the data, and try out ways of modeling and visualizing the data to see what works.\nIn many cases, creating a data science sandbox with read-only access to data is a great solution. If you’re creating a tool that also writes data, you can write the data only within the dev environment.\nIf you’re able to do this, you can explore the data to your heart’s content without the IT/Admin team having to worry you’re going to mess up production data.\nDepending on your organization, they may also be worried about data exfiltration – people intentionally or accidentally removing data from the sandbox environment. In that case, you may want to run your sandbox without the ability to connect to the internet, sometimes called airgapped or offline. More on how to work in an airgapped environment is in Chapter 17.\n\n\n16.1.0.2 Package Availability\nYour organization may not have any restrictions on the packages you can install and use in your environment. If so, that’s great! You should still use environment as code tooling as we explored in Chapter 1.\nBut other organizations don’t allow free-and-open access to packages inside their environments for security or other reasons. They may have restrictive networking rules that don’t allow you to reach our to CRAN, BioConductor, PyPI, or GitHub to install packages publicly.\nThere may also be rules about having to validate packages – for security and/or correctness – before they can be used in a production context.\nThis is difficult, since the exploratory dev process often involves trying out new packages – is it best to use this modeling package or that, best to use one type of visualization or another. If you can convince your IT/Admins to give you freer access to packages in dev, that’s ideal.\nYou can work with them to figure out what the promotion process will look like. It’s easy to generate a list of the packages you’ll need to promote apps or reports into production with tools like renv or venv. Great collaborations with IT/Admin are possible if you can develop a procedure where you give them package manifests that they can compare to allow-lists and then make those packages available.\n\n\n16.1.0.3 A Promotion Process\nThe last thing you’ll need is a process to promote content out of the dev environment into test or prod. The parameters of this process will vary a lot depending on your organization.\nIn many organizations, data scientists won’t have permissions to deploy into the prod environment – only a small group of admins will have the ability to verify changes and submit them to the prod environment.\nIn this case, a code promotion strategy (see Chapter 5) co-designed with your IT/Admins is the way to go. You want to hand off a fully-baked production asset so all they need to do is put it into the right place, preferably with CI/CD tooling."
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+    "text": "15.1 Data Science Sandboxes\nIn Chapter 5 on code promotion, we talked about wanting to create separate dev/test/prod environments for your data science assets. In many organizations, your good intentions to do dev/test/prod work for your data science assets are insufficient.\nIn the enterprise, it’s often the case that IT/Admins are required to ensure that your dev work can’t wreak havoc on actual production systems. If you can work with your organization’s IT/Admins to get a place to work, this is a good thing! It’s nice to have a sandbox where you can do whatever you want with no concern of breaking anything real.\nThere are three components to a data science sandbox:\n\nFree read-only access to real data\nRelatively broad access to packages\nA process to promote data science projects into production\n\nMany IT/Admins are familiar with building workbenches for other sorts of software development tasks, so they may believe they understand what you need.\n\n15.1.0.1 Read-Only Data Access\nIn software engineering, the shape of the data in the system matters a lot, but the content doesn’t matter much. If you’re building software to do inventory tracking, you’re perfectly fine testing on data that isn’t of a real inventory as long as it’s formatted the same as real inventory data. That means that a software engineering dev environment doesn’t require access to any real data.\nIT/Admins may believe that providing a standalone or isolated environment for you to work in is sufficient. You’re probably wincing reading this knowing that it’s not the case.\nAs you know, data science isn’t like that. In data science, what you’re doing in dev environments – exploring relationships between variables, visualizing, training models, looks much more different from test and prod than for software engineering. You need a place where you can work with real data, explore relationships in the data, and try out ways of modeling and visualizing the data to see what works.\nIn many cases, creating a data science sandbox with read-only access to data is a great solution. If you’re creating a tool that also writes data, you can write the data only within the dev environment.\nIf you’re able to do this, you can explore the data to your heart’s content without the IT/Admin team having to worry you’re going to mess up production data.\nDepending on your organization, they may also be worried about data exfiltration – people intentionally or accidentally removing data from the sandbox environment. In that case, you may want to run your sandbox without the ability to connect to the internet, sometimes called airgapped or offline. More on how to work in an airgapped environment is in Chapter 16.\n\n\n15.1.0.2 Package Availability\nYour organization may not have any restrictions on the packages you can install and use in your environment. If so, that’s great! You should still use environment as code tooling as we explored in Chapter 1.\nBut other organizations don’t allow free-and-open access to packages inside their environments for security or other reasons. They may have restrictive networking rules that don’t allow you to reach our to CRAN, BioConductor, PyPI, or GitHub to install packages publicly.\nThere may also be rules about having to validate packages – for security and/or correctness – before they can be used in a production context.\nThis is difficult, since the exploratory dev process often involves trying out new packages – is it best to use this modeling package or that, best to use one type of visualization or another. If you can convince your IT/Admins to give you freer access to packages in dev, that’s ideal.\nYou can work with them to figure out what the promotion process will look like. It’s easy to generate a list of the packages you’ll need to promote apps or reports into production with tools like renv or venv. Great collaborations with IT/Admin are possible if you can develop a procedure where you give them package manifests that they can compare to allow-lists and then make those packages available.\n\n\n15.1.0.3 A Promotion Process\nThe last thing you’ll need is a process to promote content out of the dev environment into test or prod. The parameters of this process will vary a lot depending on your organization.\nIn many organizations, data scientists won’t have permissions to deploy into the prod environment – only a small group of admins will have the ability to verify changes and submit them to the prod environment.\nIn this case, a code promotion strategy (see Chapter 5) co-designed with your IT/Admins is the way to go. You want to hand off a fully-baked production asset so all they need to do is put it into the right place, preferably with CI/CD tooling."
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-    "text": "16.2 Dev/Test/Prod for Admins\nIn the chapter on environment as code tooling, we discussed how you want to create a version of your package environment in a safe place and then use code to share it with others and promote it into production.\nThe IT/Admin group at your organization probably is thinking about something similar, but at a more basic level. They want to make sure that they’re providing a great experience to you – the users of the platform.\nSo they probably want to make sure they can upgrade the servers you’re using, change to a newer operating system, or upgrade to a newer version of R or Python without interrupting your use of the servers.\nThese are the same concerns you probably have about the users of the apps and reports you’re creating. In this case, I recommend a two-dimensional grid – one for promoting the environment itself into place for IT/Admins and another for promoting the data science assets into production.\nIn order to differentiate the environments, I often call the IT/Admin development and testing area staging, and use dev/test/prod language for the data science promotion process.\nBack in section one, we learned about environments as code – using code to make sure that our data science environments are reproducible and can be re-created as needed.\nThis idea isn’t original – in fact, DevOps has it’s own set of practices and tooling around using code to manage DevOps tasks, broadly called Infrastructure As Code (IaC).\nTo get from “nothing” to a usable server state, there are (at minimum) two things you need to do – provision the infrastructure you need, and configure that infrastructure to do what you want.\nFor example, let’s say I’m standing up a server to deploy a simple shiny app. In order to get that server up, I’ll need to stand up an actual server, including configuring the security settings and networking that will allow the proper people to access the server. Then I’ll need to install a version of R on the server, the Shiny package, and a piece of hosting software like Shiny Server.\nSo, for example, you might use AWS’s CloudFormation to stand up a virtual private cloud (VPC), put an EC2 server instance inside that VPC, attach an appropriately-sized storage unit, and attach the correct networking rules. Then you might use Chef to install the correct software on the server and get your Shiny app up-and-running.\nIn infrastructure as code tooling, there generally isn’t a clear dividing line between tools that do provisioning and tools that do configuration…but most tools lean one way or the other.\nBasically any tool does provisioning will directly integrate into the APIs of the major cloud providers to make it easy to provision cloud servers. Each of the cloud providers also has their own IaC tool, but many people prefer to use other tools when given the option (to be delicate).\nIt’s worth noting that Docker by itself is not an IaC tool. A Dockerfile is a reliable way to re-create the container, but that doesn’t get you all the way to a deployed container that’s reliable. You’ll need to combine a container with a deployment framework like Docker Compose or Kubernetes, as well as a way to stand up the servers that underlie that cluster.\nIt’s also worth noting that IaC may or may not be deployed using CI/CD. It’s generally a good practice to do so, but you can have IaC tooling that’s deployed manually.\nBasically none of these tools will save you from your own bad habits, but they can give you alternatives."
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+    "text": "15.2 Dev/Test/Prod for Admins\nIn the chapter on environment as code tooling, we discussed how you want to create a version of your package environment in a safe place and then use code to share it with others and promote it into production.\nThe IT/Admin group at your organization probably is thinking about something similar, but at a more basic level. They want to make sure that they’re providing a great experience to you – the users of the platform.\nSo they probably want to make sure they can upgrade the servers you’re using, change to a newer operating system, or upgrade to a newer version of R or Python without interrupting your use of the servers.\nThese are the same concerns you probably have about the users of the apps and reports you’re creating. In this case, I recommend a two-dimensional grid – one for promoting the environment itself into place for IT/Admins and another for promoting the data science assets into production.\nIn order to differentiate the environments, I often call the IT/Admin development and testing area staging, and use dev/test/prod language for the data science promotion process.\nBack in section one, we learned about environments as code – using code to make sure that our data science environments are reproducible and can be re-created as needed.\nThis idea isn’t original – in fact, DevOps has it’s own set of practices and tooling around using code to manage DevOps tasks, broadly called Infrastructure As Code (IaC).\nTo get from “nothing” to a usable server state, there are (at minimum) two things you need to do – provision the infrastructure you need, and configure that infrastructure to do what you want.\nFor example, let’s say I’m standing up a server to deploy a simple shiny app. In order to get that server up, I’ll need to stand up an actual server, including configuring the security settings and networking that will allow the proper people to access the server. Then I’ll need to install a version of R on the server, the Shiny package, and a piece of hosting software like Shiny Server.\nSo, for example, you might use AWS’s CloudFormation to stand up a virtual private cloud (VPC), put an EC2 server instance inside that VPC, attach an appropriately-sized storage unit, and attach the correct networking rules. Then you might use Chef to install the correct software on the server and get your Shiny app up-and-running.\nIn infrastructure as code tooling, there generally isn’t a clear dividing line between tools that do provisioning and tools that do configuration…but most tools lean one way or the other.\nBasically any tool does provisioning will directly integrate into the APIs of the major cloud providers to make it easy to provision cloud servers. Each of the cloud providers also has their own IaC tool, but many people prefer to use other tools when given the option (to be delicate).\nIt’s worth noting that Docker by itself is not an IaC tool. A Dockerfile is a reliable way to re-create the container, but that doesn’t get you all the way to a deployed container that’s reliable. You’ll need to combine a container with a deployment framework like Docker Compose or Kubernetes, as well as a way to stand up the servers that underlie that cluster.\nIt’s also worth noting that IaC may or may not be deployed using CI/CD. It’s generally a good practice to do so, but you can have IaC tooling that’s deployed manually.\nBasically none of these tools will save you from your own bad habits, but they can give you alternatives."
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-    "text": "16.3 Package Management in the Enterprise\nIn the chapter on environments as code, we went in depth on how to manage a per-project package environment that moves around with that project. This is a best practice and you should do it.\nBut in some Enterprise environments, there may be further requirements around how packages get into the environment, which packages are allowed, and how to validate those packages.\n\n16.3.1 Open Source in Enterprise\nOpen Souce software is the water code-first data science swims in. R and Python are open source. Any package you’ll access on CRAN, BioConductor, or PyPI is open source.\nEven if you don’t know the details, you’re probably already a big believer in the power of Free and Open Source Software (FOSS) to help people get stuff done.\nIn the enterprise, it is sometimes the case that people are more acquainted with the risks of open source than the benefits.\nFOSS is defined by a legal license. When you put something out on the internet, you can provide no licensing at all. That means that people can do whatever they want with it, but they also have no reassurances you might not come to sue them later.\nI am not a lawyer and this is not legal advice, but hopefully this is helpful context on the legal issues around FOSS software.\nPutting a license on a piece of software makes clear what is and isn’t allowed with that piece of software.\nThe type of license you’re probably most familiar with is a copyright. A copyright gives the owner exclusivity to do certain things with whatever falls under the copyright. FOSS licenses are the opposite – they guarantee that you’re freely allowed to do what you want with the software, though there may be other obligations as well.\nThe point of FOSS is to allow people to build on each other’s work. So the free in FOSS is about freedom, not about zero cost. As a common saying goes – it means free as in free speech, not free as in free beer.\nThere are many different flavors of open-source licenses, and all of them I’m aware of (even the anti-capitalist one) allows you to charge for access. The question is what you’re allowed to do after you acquire the software.\nBasically all open source licenses guarantee four freedoms. These are the freedom to view and inspect the source code, to run the software, to modify the software, and to redistribute the software as you see fit.\nWithin those parameters, there are many different kinds of open source licenses. The Open Source Initiative lists dozens of different licenses with slightly different parameters, but they fall into two main categories – permissive and copyleft.\nPermissive licenses allow you to do basically whatever you want with the software.\nFor example, the common MIT license allows you to, “use, copy, modify, merge, publish, distribute, sublicense, and/or sell” MIT-licensed software without attribution. The most important implication of this is that you can take MIT-licenses software, incorporate it into some other piece of code, and keep that code completely closed.\nCopyleft or viral licenses require that any derivative works are released under the same license. The idea is that open source software should beget more open source software and not silently be used by big companies to make megabucks.\nThe biggest concern with copyleft licenses is that they might propagate into the private work you are doing inside your company. This concern is especially keen at organizations that themselves sell proprietary software. For example, what if a court were to rule that Apple or Google had to suddenly open source all their software?\nThis is a subtle concern and largely revolves around what it means to include another piece of software. Many organizations deem that inclusion only happens if you were to literally copy/paste open source code into your code. In this view, the things created with open source software are not themselves open source.\nThe reality is that there have been basically no legal cases on this topic and nobody knows how it would shake out if it did get to court, so some organizations err on the side of caution.\nSo one of the concerns around open source software is the mixure of licenses involved. R is released under a copyleft GPL license, Python under a permissive Python Software Foundation (PSF) license, RStudio under a copyleft AGPL, and Jupyter Notebook under a permissive modified BSD. And every single package author can choose a license for themselves.\nSay I create an app or plot in R and then share that plot with the public – is that app or plot bound by the license as well? Do I now have to release my source code to the public? Many would argue no – it uses R, but doesn’t derive from R in any way. Others have concerns that stricter interpretations of copyleft might hold up in court if it were to come to that.\nThere are disagreements on this among lawyers, and you should be sure to talk to a lawyer at your organization if you have concerns.\n\n\n16.3.2 Dealing with Package Restrictions\nChapter 1 on environments as code dealt with how to create a reproducible version of your package library for any given piece of content. But in some enterprises, you won’t be able to freely create a library. Instead, your organization may have restrictions on package installation and will need to gate the packages that are allowed into your environment.\nIn order to enact these restrictions, IT/Admins have to do two things - make sure that public repositories are not available to users of their data science platforms, and use one of these repository tools to manage the set of packages that are available inside their environment. It often takes a bit of convincing, but a good division of labor here is generally that the IT/Admins manage the repository server and what’s allowed into the environment and the individual teams manage their own project libraries.\n\n\n\n\n\n\nAmount of Space for Packages\n\n\n\nWhen admins hear about a package cache per-project, they start getting worried about storage space. I have heard this concern many times from admins who haven’t yet adopted this strategy, and almost never heard an admin say they were running out of storage space because of package storage.\nThe reality is that most R and Python packages are very small, so storing many of them is reasonably trivial.\nAlso, these package storage tools are pretty smart. They have a shared package cache across projects, so each package only gets installed once, but can be used in a variety of projects.\nIt is true that each user then has their own version of the package. Again, because packages are small, this tends to be a minor issue. It is possible to make the package cache one that is shared across users, but the (small) risk this introduces of one user affecting other users on the server is probably not worth the very small cost of provisioning enough storage that this just isn’t an issue.\n\n\nMany enterprises run some sort of package repository software. Common package repositories used for R and Python include Jfrog Artifactory, Sonatype Nexus, Anaconda Business, and Posit Package Manager.\nArtifactory and Nexus are generalized library and package management solutions for all sorts of software, while Anaconda and Posit Package Manager are more narrowly tailored for data science use cases.\nThere are two main concerns that come up in the context of managing packages for the enterprise. The first is how to manage package security vulnerabilities.\nIn this context, the question of how to do security scanning comes up. What exactly security professionals mean by scanning varies widely, and what’s possible differs a good bit from language to language.\nIt is possible to imagine a security scanner that actually reads in all of the code in a package and identifies potential security risks – like usage of insecure libraries, calls to external web services, or places where it accesses a database. 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+    "text": "15.3 Package Management in the Enterprise\nIn the chapter on environments as code, we went in depth on how to manage a per-project package environment that moves around with that project. This is a best practice and you should do it.\nBut in some Enterprise environments, there may be further requirements around how packages get into the environment, which packages are allowed, and how to validate those packages.\n\n15.3.1 Open Source in Enterprise\nOpen Souce software is the water code-first data science swims in. R and Python are open source. Any package you’ll access on CRAN, BioConductor, or PyPI is open source.\nEven if you don’t know the details, you’re probably already a big believer in the power of Free and Open Source Software (FOSS) to help people get stuff done.\nIn the enterprise, it is sometimes the case that people are more acquainted with the risks of open source than the benefits.\nFOSS is defined by a legal license. When you put something out on the internet, you can provide no licensing at all. That means that people can do whatever they want with it, but they also have no reassurances you might not come to sue them later.\nI am not a lawyer and this is not legal advice, but hopefully this is helpful context on the legal issues around FOSS software.\nPutting a license on a piece of software makes clear what is and isn’t allowed with that piece of software.\nThe type of license you’re probably most familiar with is a copyright. A copyright gives the owner exclusivity to do certain things with whatever falls under the copyright. FOSS licenses are the opposite – they guarantee that you’re freely allowed to do what you want with the software, though there may be other obligations as well.\nThe point of FOSS is to allow people to build on each other’s work. So the free in FOSS is about freedom, not about zero cost. As a common saying goes – it means free as in free speech, not free as in free beer.\nThere are many different flavors of open-source licenses, and all of them I’m aware of (even the anti-capitalist one) allows you to charge for access. The question is what you’re allowed to do after you acquire the software.\nBasically all open source licenses guarantee four freedoms. These are the freedom to view and inspect the source code, to run the software, to modify the software, and to redistribute the software as you see fit.\nWithin those parameters, there are many different kinds of open source licenses. 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And every single package author can choose a license for themselves.\nSay I create an app or plot in R and then share that plot with the public – is that app or plot bound by the license as well? Do I now have to release my source code to the public? Many would argue no – it uses R, but doesn’t derive from R in any way. Others have concerns that stricter interpretations of copyleft might hold up in court if it were to come to that.\nThere are disagreements on this among lawyers, and you should be sure to talk to a lawyer at your organization if you have concerns.\n\n\n15.3.2 Dealing with Package Restrictions\nChapter 1 on environments as code dealt with how to create a reproducible version of your package library for any given piece of content. But in some enterprises, you won’t be able to freely create a library. Instead, your organization may have restrictions on package installation and will need to gate the packages that are allowed into your environment.\nIn order to enact these restrictions, IT/Admins have to do two things - make sure that public repositories are not available to users of their data science platforms, and use one of these repository tools to manage the set of packages that are available inside their environment. It often takes a bit of convincing, but a good division of labor here is generally that the IT/Admins manage the repository server and what’s allowed into the environment and the individual teams manage their own project libraries.\n\n\n\n\n\n\nAmount of Space for Packages\n\n\n\nWhen admins hear about a package cache per-project, they start getting worried about storage space. I have heard this concern many times from admins who haven’t yet adopted this strategy, and almost never heard an admin say they were running out of storage space because of package storage.\nThe reality is that most R and Python packages are very small, so storing many of them is reasonably trivial.\nAlso, these package storage tools are pretty smart. They have a shared package cache across projects, so each package only gets installed once, but can be used in a variety of projects.\nIt is true that each user then has their own version of the package. Again, because packages are small, this tends to be a minor issue. It is possible to make the package cache one that is shared across users, but the (small) risk this introduces of one user affecting other users on the server is probably not worth the very small cost of provisioning enough storage that this just isn’t an issue.\n\n\nMany enterprises run some sort of package repository software. Common package repositories used for R and Python include Jfrog Artifactory, Sonatype Nexus, Anaconda Business, and Posit Package Manager.\nArtifactory and Nexus are generalized library and package management solutions for all sorts of software, while Anaconda and Posit Package Manager are more narrowly tailored for data science use cases.\nThere are two main concerns that come up in the context of managing packages for the enterprise. The first is how to manage package security vulnerabilities.\nIn this context, the question of how to do security scanning comes up. What exactly security professionals mean by scanning varies widely, and what’s possible differs a good bit from language to language.\nIt is possible to imagine a security scanner that actually reads in all of the code in a package and identifies potential security risks – like usage of insecure libraries, calls to external web services, or places where it accesses a database. 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-    "text": "17.1 Enterprise Networking Terminology\nHopefully the analogy of a basic server as an apartment building and an enterprise server as a castle keep behind a drawbridge makes basic sense. But let’s get into the way you’ll actually talk about this with the IT/Admins at your organization – I promise they won’t talk about castles and apartments.\nWhen you stand up a server in the cloud, it’s inside a private network. In AWS, the private network that houses the servers is called a virtual private cloud (VPC), which you probably saw somewhere in the AWS console.\nFor our workbench server, we took that private network and made it public so every server (there was just one) inside our private network also has a public IP address so it was accessible from the internet.\nIn an enterprise configuration you won’t do that. Instead, you’ll take your private network and divide it into subnets – most often two of them.\nNow you’ll take the subnets and put all the stuff you actually care about in a private subnet. Private networks generally host all of the servers that actually do things. Your data science workbench server, your databases, server for hosting shiny apps – all these things should live inside the private network. Nothing in the private subnet will be directly accessible from the public internet.\n\n\n\n\n\n\nDefining private networks and subnets\n\n\n\nPrivate networks and subnets are defined by something called a Classless Inter-Domain Routing (CIDR) block. A CIDR block is basically an IP address range, so a private network is a CIDR block and each subnet is CIDR blocks within the private network’s block.\nEach CIDR block is defined by a starting address and the size of the network. For example, the address 10.33.0.0 and the /26 CIDR defines the block of 64 addresses from 10.33.0.0 to 10.33.0.63.\nLarger CIDR numbers indicate a smaller block, so you could take the 10.33.0.0/26 CIDR and split it into the 10.33.0.0/27 block that includes 10.33.0.0 to 10.33.0.31 and 10.33.0.32/27 for 10.33.0.32 through 10.33.0.63.\nAs you’ve probably guessed, the number of IPs in each CIDR have to do with powers of two. But the rules are hard to remember and there are online calculators if you ever have to figure a block out for yourself.\n\n\nThe only things you’ll put in the public subnet – often called a demilitarized zone (DMZ) – are servers that exist solely for the purpose of relaying traffic back and forth to the servers in your private network. These servers are called proxy servers or proxies – more on them in a moment.\nThis means that the traffic actually coming to your workbench comes only from other servers you control. It’s easy to see why this is more secure.\n[TODO: image of private networks + proxies]\nIn most cases, you’ll have minimum two servers in the DMZ. You’ll usually have one or more proxies to handle the incoming HTTPS traffic that comes in from the outside world. You’ll also usually have a proxy that is just for passing SSH traffic along to hosts in the private network, often called a bastion host or jump box.\nThe other benefit of using a private network for the things you actually care about is that you can manage the IP addresses and hostnames of those servers without having to worry about getting public addresses. If you want to name one of the servers in your private subnet google.com, you can do that (I wouldn’t recommend it), because the only time that name will be used is when traffic is coming past your proxy servers and into the private network.\nThere’s a device sitting on the boundary of all networks that provide translations between private IP addresses and public ones. For your private subnet, you’ll only have an outbound one available. In AWS, it’s called a Network Address Translation (NAT) Gateway. For your private network as a whole, there’ll be another gateway that provides both inbound and outbout support, it’s called an Internet Gateway by AWS.\n\n17.1.1 What proxies do\nAs a data scientist, this may be the first time you’re encountering the term proxy, but for IT/Admins – especially ones who specialize in networking – configuring proxies is an everyday activity.\nProxies can be either in software or hardware. For example, in our workbench server, we installed the nginx software proxy on the same server as our workbench to allow people to go to any of the different services we installed on that server. In enterprise use cases, proxies are most often on standalone pieces of hardware. They may run nginx or Apache – the other popular open source option. Popular paid enterprise options include F5, Citrix, Fortinet, and Cloudflare.\nProxies can deal with traffic coming into the private network, called an inbound proxy or they can deal with traffic going out from the private network, called an outbound proxy.\n\n\n\n\n\n\nNote\n\n\n\nInbound and outbound are not industry standard terms for proxies. The terms you’ll hear from IT/Admins are forward and reverse. Proxies are discussed from the perspective of being inside the network, so forward equals outbound and reverse equals inbound.\nI find it nearly impossible to remember which is which and IT/Admins will absolutely know what you mean with the terms inbound and outbound, so I recommend you use them instead.\n\n\nProxies are usually used for redirection, port management and firewalling.\nRedirection is when the proxy accepts traffic at the public DNS record and passes (proxies) it along to the actual server. One great thing about this configuration is that only the proxy needs to know the real hostname for your server. For example, you could configure the proxy so example.com/rstudio routes to the RStudio Server that’s at my-rstudio-1 inside the private network. If you want to change it to my-rstudio-2 later on, you just change the proxy routing, which is much easier than changing the public DNS record.\nOne advantage of doing redirection is making it easy to manage ports. For example, RStudio Server runs on port 8787 by default. Generally, you don’t want people to have to remember to go to a random port to access RStudio Server so it’s standard practices to keep standard ports (80 for HTTP, 443 for HTTPS, and 22 for SSH) open on the proxy and have the proxy just redirect the traffic coming into it on 443 to 8787 on the server with RStudio Server.\n\n\n\n\n\n\nNote\n\n\n\nFor our workbench server, we did path rewriting and port management in our nginx proxy.\nIf you recall, by the time we were done, our nginx config was set to only allow HTTPS traffic on 443, redirect all HTTP traffic on 80 to HTTPS on 443, and to take traffic at /rstudio to port 8787 on the same server, /jupyter to port 8000, and /palmer to 8080.\n\n\n[TODO: image of path rewriting + load-balancing]\nProxies are additionally sometimes configured to block traffic that isn’t explicitly allowed. In a data science environment, this means that you’ll have to configure the inbound proxy with all the locations you need. If you’ve got an outbound proxy that blocks traffic, you’re in an airgapped/offline situation.\nThere are a few other things a proxy may be used for. These use cases are less common in a data science environment.\nSometimes proxies terminate SSL. Because the proxy is the last server that is accessible from the public network, many organizations don’t bother to implement SSL/HTTPS inside the private network so they don’t have to worry about managing SSL certificates inside their private network. This is getting rarer as tooling for managing SSL certificates gets better, but it’s common enough that you might start seeing HTTP addresses if you’re doing server-to-server things inside the private network.\nOccasionally proxies also do authentication. In most cases, proxies pass along any traffic that comes in to where it’s supposed to go. If there’s authentication, it’s often at the server itself.\nSometimes the proxy is actually where authentication happens, so you have to provide the credentials at the edge of the network. Once those credentials have been supplied, the proxy will let you through. Depending on the configuration, the proxy may also add some sort of token or header to your incoming traffic to let the servers inside know that your authentication is good and to pass along identification for authorization purposes.\nTODO: image of auth at proxy\nLastly, there’s a special kind of reverse proxy called a load-balancer. A load-balancer is used to scale a service across a pool of servers on the back end. We’ll get more into how this works in Chapter 19."
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+    "title": "16  Enterprise Networking",
+    "section": "16.1 Enterprise Networking Terminology",
+    "text": "16.1 Enterprise Networking Terminology\nREORGED FROM 2.6\nIn order to be accessible to traffic from the internet, a host must have a public IP Address, which is unique across the entire internet.\nBut many, many more hosts don’t have apublic IP Address. Instead, they live only on a private network and have only a private IP Address. For example, your phone, personal computer, and smart fridge don’t (or shouldn’t) have a public IP Address. Instead, these devices register with your home router and the router assigns and keeps track of their private IP Addresses. Only your router has a public IP Address, so return mail has somewhere to go.\nThis system drastically simplifies the topology of the web. Instead of thinking of the web as an enormous set of public streets, it’s more like a series of gated communities and the public IP Address servers only need to keep track of those front gates.\nHopefully the analogy of a basic server as an apartment building and an enterprise server as a castle keep behind a drawbridge makes basic sense. But let’s get into the way you’ll actually talk about this with the IT/Admins at your organization – I promise they won’t talk about castles and apartments.\nWhen you stand up a server in the cloud, it’s inside a private network. In AWS, the private network that houses the servers is called a virtual private cloud (VPC), which you probably saw somewhere in the AWS console.\nFor our workbench server, we took that private network and made it public so every server (there was just one) inside our private network also has a public IP Address so it was accessible from the internet.\nIn an enterprise configuration you won’t do that. Instead, you’ll take your private network and divide it into subnets – most often two of them.\nNow you’ll take the subnets and put all the stuff you actually care about in a private subnet. Private networks generally host all of the servers that actually do things. Your data science workbench server, your databases, server for hosting shiny apps – all these things should live inside the private network. Nothing in the private subnet will be directly accessible from the public internet.\n\n\n\n\n\n\nDefining private networks and subnets\n\n\n\nPrivate networks and subnets are defined by something called a Classless Inter-Domain Routing (CIDR) block. A CIDR block is basically an IP address range, so a private network is a CIDR block and each subnet is CIDR blocks within the private network’s block.\nEach CIDR block is defined by a starting address and the size of the network. For example, the address 10.33.0.0 and the /26 CIDR defines the block of 64 addresses from 10.33.0.0 to 10.33.0.63.\nLarger CIDR numbers indicate a smaller block, so you could take the 10.33.0.0/26 CIDR and split it into the 10.33.0.0/27 block that includes 10.33.0.0 to 10.33.0.31 and 10.33.0.32/27 for 10.33.0.32 through 10.33.0.63.\nAs you’ve probably guessed, the number of IPs in each CIDR have to do with powers of two. But the rules are hard to remember and there are online calculators if you ever have to figure a block out for yourself.\n\n\nThe only things you’ll put in the public subnet – often called a demilitarized zone (DMZ) – are servers that exist solely for the purpose of relaying traffic back and forth to the servers in your private network. These servers are called proxy servers or proxies – more on them in a moment.\nThis means that the traffic actually coming to your workbench comes only from other servers you control. It’s easy to see why this is more secure.\n[TODO: image of private networks + proxies]\nIn most cases, you’ll have minimum two servers in the DMZ. You’ll usually have one or more proxies to handle the incoming HTTPS traffic that comes in from the outside world. You’ll also usually have a proxy that is just for passing SSH traffic along to hosts in the private network, often called a bastion host or jump box.\nThe other benefit of using a private network for the things you actually care about is that you can manage the IP Addresses and hostnames of those servers without having to worry about getting public addresses. If you want to name one of the servers in your private subnet google.com, you can do that (I wouldn’t recommend it), because the only time that name will be used is when traffic is coming past your proxy servers and into the private network.\nThere’s a device sitting on the boundary of all networks that provide translations between private IP Addresses and public ones. For your private subnet, you’ll only have an outbound one available. In AWS, it’s called a Network Address Translation (NAT) Gateway. For your private network as a whole, there’ll be another gateway that provides both inbound and outbout support, it’s called an Internet Gateway by AWS.\n\n16.1.1 What proxies do\nAs a data scientist, this may be the first time you’re encountering the term proxy, but for IT/Admins – especially ones who specialize in networking – configuring proxies is an everyday activity.\nProxies can be either in software or hardware. For example, in our workbench server, we installed the nginx software proxy on the same server as our workbench to allow people to go to any of the different services we installed on that server. In enterprise use cases, proxies are most often on standalone pieces of hardware. They may run nginx or Apache – the other popular open source option. Popular paid enterprise options include F5, Citrix, Fortinet, and Cloudflare.\nProxies can deal with traffic coming into the private network, called an inbound proxy or they can deal with traffic going out from the private network, called an outbound proxy.\n\n\n\n\n\n\nNote\n\n\n\nInbound and outbound are not industry standard terms for proxies. The terms you’ll hear from IT/Admins are forward and reverse. Proxies are discussed from the perspective of being inside the network, so forward equals outbound and reverse equals inbound.\nI find it nearly impossible to remember which is which and IT/Admins will absolutely know what you mean with the terms inbound and outbound, so I recommend you use them instead.\n\n\nProxies are usually used for redirection, port management and firewalling.\nRedirection is when the proxy accepts traffic at the public DNS record and passes (proxies) it along to the actual server. One great thing about this configuration is that only the proxy needs to know the real hostname for your server. For example, you could configure the proxy so example.com/rstudio routes to the RStudio Server that’s at my-rstudio-1 inside the private network. If you want to change it to my-rstudio-2 later on, you just change the proxy routing, which is much easier than changing the public DNS record.\nOne advantage of doing redirection is making it easy to manage ports. For example, RStudio Server runs on port 8787 by default. Generally, you don’t want people to have to remember to go to a random port to access RStudio Server so it’s standard practices to keep standard ports (80 for HTTP, 443 for HTTPS, and 22 for SSH) open on the proxy and have the proxy just redirect the traffic coming into it on 443 to 8787 on the server with RStudio Server.\n\n\n\n\n\n\nNote\n\n\n\nFor our workbench server, we did path rewriting and port management in our nginx proxy.\nIf you recall, by the time we were done, our nginx config was set to only allow HTTPS traffic on 443, redirect all HTTP traffic on 80 to HTTPS on 443, and to take traffic at /rstudio to port 8787 on the same server, /jupyter to port 8000, and /palmer to 8080.\n\n\n[TODO: image of path rewriting + load-balancing]\nProxies are additionally sometimes configured to block traffic that isn’t explicitly allowed. In a data science environment, this means that you’ll have to configure the inbound proxy with all the locations you need. If you’ve got an outbound proxy that blocks traffic, you’re in an airgapped/offline situation.\nThere are a few other things a proxy may be used for. These use cases are less common in a data science environment.\nSometimes proxies terminate SSL. Because the proxy is the last server that is accessible from the public network, many organizations don’t bother to implement SSL/HTTPS inside the private network so they don’t have to worry about managing SSL certificates inside their private network. This is getting rarer as tooling for managing SSL certificates gets better, but it’s common enough that you might start seeing HTTP addresses if you’re doing server-to-server things inside the private network.\nOccasionally proxies also do authentication. In most cases, proxies pass along any traffic that comes in to where it’s supposed to go. If there’s authentication, it’s often at the server itself.\nSometimes the proxy is actually where authentication happens, so you have to provide the credentials at the edge of the network. Once those credentials have been supplied, the proxy will let you through. Depending on the configuration, the proxy may also add some sort of token or header to your incoming traffic to let the servers inside know that your authentication is good and to pass along identification for authorization purposes.\nTODO: image of auth at proxy\nLastly, there’s a special kind of reverse proxy called a load-balancer. A load-balancer is used to scale a service across a pool of servers on the back end. We’ll get more into how this works in Chapter 18."
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-    "title": "17  Enterprise Networking",
-    "section": "17.2 What data science needs from the network",
-    "text": "17.2 What data science needs from the network\nAs you’ve probably grasped, enterprise networking can be complex. And your IT/Admin group knows a lot about it. What they don’t know a lot about is the interaction of networking and data science, so it’s helpful for you to be able to clearly state what you need.\n\n\n\n\n\n\nWhat ports do I need?\n\n\n\nOne of the first questions IT/Admins ask is what ports need to be open. Depending on what ports you choose for the services you’re running those ports need to be open.\nThe good news is that almost all traffic for data science purposes is standard HTTP(S) traffic, so it can happily run over 80 or 443 if there are limitations on what ports can be open.\n\n\nOne of the most common issues with data science environments in an enterprise is proxy behavior. If you’re experiencing weird behavior in your data science environment – files failing to upload or download, sessions getting cutoff strangely, or data not transferring right – asking your IT/Admin about whether there are proxies and their behavior should be suspect number one.\nWhen you’re talking to your IT/Admin about the proxies, it’s really helpful to have a good mental model of what traffic might be hitting an inbound proxy and what traffic might be hitting an outbound one.\nAs we went over in Chapter 12, network traffic always operates on a call and response model. So whether your traffic is inbound or outbound is dependent on who makes the call. Inbound means that the call is coming from a computer outside the private network directed to a server inside the private network, and outbound is the opposite.\nTODO: image inbound vs outbound connection\nSo basically, anything that originates on your laptop – including the actual session into the server is an inbound connection, while anything that originates on the server – including everything in code that runs on the server is an outbound connection.\n\n17.2.1 Issues with inbound proxies\nInbound proxies affect the connection you’re making from your personal computer to the server. There are two ways this might affect your experience doing data science on a server.\nIt’s reasonably common for organizations to have settings that limit file sizes for uploads and downloads or implementing timeouts on file uploads, downloads, and sessions. In data science contexts, files tend to be big and session lengths long.\nIf you’re trying to work in a data science context and weird things are happening with file uploads or downloads or sessions ending unexpectedly, checking on inbound proxy settings is a good first step.\nSome data science app frameworks (including Shiny and Streamlit) use a technology called Websockets for maintaining the connection between the user and the app session. Most modern proxies (including those you’ll get from a cloud provider) support Websockets, but some older on-prem proxies don’t and you may have to figure out a workaround if you can’t get Websockets enabled on your proxy.\n\n\n17.2.2 Issues with forward/outbound proxies\nAlmost all enterprise networks have inbound proxies. Outbound ones are somewhat rarer. That’s because outbound proxies limit connections made from inside the network to the outside. It’s obvious why you’d need to protect your data science environment from the entire outside world.\nMany organizations don’t feel the need to limit what external resources people can interact with from inside their firewall, but limitations on outbound access have long been common in highly regulated industries with strong requirements around data security and governance and are becoming increasingly common in many different industries. Many organizations have these proxies to reduce the risk of someone getting in and then being able to exfiltrate valuable resource.\nOrganizations who limit outbound access from their data science environment usually refer to the environment as offline or airgapped. The term airgapped indicates that there is a physical gap – air – between the internet and the environment. It is very rare for this to be the case. In most cases, airgapping is accomplished by putting in an outbound proxy that disallows (nearly) all connections.\nThe good news is that once you’re working on your data science server, you don’t need to go out much. The bad news is that you will have to go out sometimes. It’s important you work with your IT/Admin to develop a plan for how to handle when outbound connectivity is needed.\nHere are the four most common reasons you’ll need to make outbound connections from inside your data science environment.\n\nDownloading Packages Downloading a package from a public repository requires a network connection to that repository. So you’ll need outbound access when you want to install R or Python packages from CRAN, BioConductor, public Posit Package Manager, Conda, PyPI, or GitHub.\nAccessing External Data In most data science work, you’re mostly just working on data from databases or files inside your private network, so you don’t really need access to data or resources outside. On the other hand, if you’re consuming data from public APIs or scraping data from the web, that may require external connections. You also may need an external connection if you’re accessing private data that lives in an external location – for example you might have data in an AWS S3 bucket you need to access from an on-prem workbench or data in Google Sheets that you need to access from AWS.\nSystem Libraries In addition to the R and Python packages, there are also system libraries you’ll need installed, like the versions of R and Python themselves, and other packages used by the system. Generally it’ll be the IT/Admin managing and installing these, so they probably have a strategy for doing it. This comes up in the context of data science if you’re using R or Python packages that are basically just wrappers around system libraries, like the R and Python packages that use the GDAL system library for geospatial work.\nSoftware Licensing If you’re using all open source software, this probably won’t be an issue. But if you’re buying licenses to a professional product, you’ll have to figure out how to activate the software licensing. This usually involves reaching out to servers owned by the software vendor. They should have a method for activating servers that can’t reach the internet, but your IT/Admins will appreciate if you’ve done your homework on this before asking them to activate some new software.\n\nWhat if your organization doesn’t default to allowing all of these things to be available? In some cases, ameliorating these issues is as easy as talking to your IT/Admin and asking them to open the outbound proxy to the right server.\nBefore you go ahead treating your environment as truly offline/airgapped, it’s almost always worth asking if narrow exceptions can be made to a network that is offline/airgapped. The answer may surprise you. Especially if it’s just a URL or two that are protected by HTTPS – for example CRAN, PyPI, or public RStudio Package Manager, it’s generally pretty safe and many organizations are happy to allow-list a limited number of outbound addresses.\nIf not, you’ll have to have a deeper conversation with the IT/Admin.\nYour organization probably has standard practices around managing system libraries and software licenses in their environment.\nExternal data connections and package management are the areas where you’ll have to have a conversation to make them accessible.\nIT/Admins often do not understand how crucial R and Python packages are to doing data science work. It will be on you to make them understand that your offline environment is useless if you can’t come up with a plan to manage packages together.\nThe best plans for offline package operations involve the IT/Admin curating a repository of allowed packages inside the private network using a professional tool like Posit Package Manager, Jfrog Artifactory, or Sonatype Nexus and then giving data scientists free reign to install those packages as needed inside the environment.\nThis can take a lot of convincing. Good luck."
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+    "title": "16  Enterprise Networking",
+    "section": "16.2 What data science needs from the network",
+    "text": "16.2 What data science needs from the network\nAs you’ve probably grasped, enterprise networking can be complex. And your IT/Admin group knows a lot about it. What they don’t know a lot about is the interaction of networking and data science, so it’s helpful for you to be able to clearly state what you need.\n\n\n\n\n\n\nWhat ports do I need?\n\n\n\nOne of the first questions IT/Admins ask is what ports need to be open. Depending on what ports you choose for the services you’re running those ports need to be open.\nThe good news is that almost all traffic for data science purposes is standard HTTP(S) traffic, so it can happily run over 80 or 443 if there are limitations on what ports can be open.\n\n\nOne of the most common issues with data science environments in an enterprise is proxy behavior. If you’re experiencing weird behavior in your data science environment – files failing to upload or download, sessions getting cutoff strangely, or data not transferring right – asking your IT/Admin about whether there are proxies and their behavior should be suspect number one.\nWhen you’re talking to your IT/Admin about the proxies, it’s really helpful to have a good mental model of what traffic might be hitting an inbound proxy and what traffic might be hitting an outbound one.\nAs we went over in Chapter 12, network traffic always operates on a call and response model. So whether your traffic is inbound or outbound is dependent on who makes the call. Inbound means that the call is coming from a computer outside the private network directed to a server inside the private network, and outbound is the opposite.\nTODO: image inbound vs outbound connection\nSo basically, anything that originates on your laptop – including the actual session into the server is an inbound connection, while anything that originates on the server – including everything in code that runs on the server is an outbound connection.\n\n16.2.1 Issues with inbound proxies\nInbound proxies affect the connection you’re making from your personal computer to the server. There are two ways this might affect your experience doing data science on a server.\nIt’s reasonably common for organizations to have settings that limit file sizes for uploads and downloads or implementing timeouts on file uploads, downloads, and sessions. In data science contexts, files tend to be big and session lengths long.\nIf you’re trying to work in a data science context and weird things are happening with file uploads or downloads or sessions ending unexpectedly, checking on inbound proxy settings is a good first step.\nSome data science app frameworks (including Shiny and Streamlit) use a technology called Websockets for maintaining the connection between the user and the app session. Most modern proxies (including those you’ll get from a cloud provider) support Websockets, but some older on-prem proxies don’t and you may have to figure out a workaround if you can’t get Websockets enabled on your proxy.\n\n\n16.2.2 Issues with forward/outbound proxies\nAlmost all enterprise networks have inbound proxies. Outbound ones are somewhat rarer. That’s because outbound proxies limit connections made from inside the network to the outside. It’s obvious why you’d need to protect your data science environment from the entire outside world.\nMany organizations don’t feel the need to limit what external resources people can interact with from inside their firewall, but limitations on outbound access have long been common in highly regulated industries with strong requirements around data security and governance and are becoming increasingly common in many different industries. Many organizations have these proxies to reduce the risk of someone getting in and then being able to exfiltrate valuable resource.\nOrganizations who limit outbound access from their data science environment usually refer to the environment as offline or airgapped. The term airgapped indicates that there is a physical gap – air – between the internet and the environment. It is very rare for this to be the case. In most cases, airgapping is accomplished by putting in an outbound proxy that disallows (nearly) all connections.\nThe good news is that once you’re working on your data science server, you don’t need to go out much. The bad news is that you will have to go out sometimes. It’s important you work with your IT/Admin to develop a plan for how to handle when outbound connectivity is needed.\nHere are the four most common reasons you’ll need to make outbound connections from inside your data science environment.\n\nDownloading Packages Downloading a package from a public repository requires a network connection to that repository. So you’ll need outbound access when you want to install R or Python packages from CRAN, BioConductor, public Posit Package Manager, Conda, PyPI, or GitHub.\nAccessing External Data In most data science work, you’re mostly just working on data from databases or files inside your private network, so you don’t really need access to data or resources outside. On the other hand, if you’re consuming data from public APIs or scraping data from the web, that may require external connections. You also may need an external connection if you’re accessing private data that lives in an external location – for example you might have data in an AWS S3 bucket you need to access from an on-prem workbench or data in Google Sheets that you need to access from AWS.\nSystem Libraries In addition to the R and Python packages, there are also system libraries you’ll need installed, like the versions of R and Python themselves, and other packages used by the system. Generally it’ll be the IT/Admin managing and installing these, so they probably have a strategy for doing it. This comes up in the context of data science if you’re using R or Python packages that are basically just wrappers around system libraries, like the R and Python packages that use the GDAL system library for geospatial work.\nSoftware Licensing If you’re using all open source software, this probably won’t be an issue. But if you’re buying licenses to a professional product, you’ll have to figure out how to activate the software licensing. This usually involves reaching out to servers owned by the software vendor. They should have a method for activating servers that can’t reach the internet, but your IT/Admins will appreciate if you’ve done your homework on this before asking them to activate some new software.\n\nWhat if your organization doesn’t default to allowing all of these things to be available? In some cases, ameliorating these issues is as easy as talking to your IT/Admin and asking them to open the outbound proxy to the right server.\nBefore you go ahead treating your environment as truly offline/airgapped, it’s almost always worth asking if narrow exceptions can be made to a network that is offline/airgapped. The answer may surprise you. Especially if it’s just a URL or two that are protected by HTTPS – for example CRAN, PyPI, or public RStudio Package Manager, it’s generally pretty safe and many organizations are happy to allow-list a limited number of outbound addresses.\nIf not, you’ll have to have a deeper conversation with the IT/Admin.\nYour organization probably has standard practices around managing system libraries and software licenses in their environment.\nExternal data connections and package management are the areas where you’ll have to have a conversation to make them accessible.\nIT/Admins often do not understand how crucial R and Python packages are to doing data science work. It will be on you to make them understand that your offline environment is useless if you can’t come up with a plan to manage packages together.\nThe best plans for offline package operations involve the IT/Admin curating a repository of allowed packages inside the private network using a professional tool like Posit Package Manager, Jfrog Artifactory, or Sonatype Nexus and then giving data scientists free reign to install those packages as needed inside the environment.\nThis can take a lot of convincing. Good luck."
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-    "section": "17.3 Comprehension Questions",
-    "text": "17.3 Comprehension Questions\n\nWhat is the advantage of adopting a more complex networking setup than a server just deployed directly on the internet? Are there advantages other than security?\nDraw a mental map with the following entities: inbound traffic, outbound traffic, proxy, DMZ, private subnet, public subnet, VPC\nOur workbench server has an nginx proxy that redirects inbound traffic on a few different paths to the right port on the same server. Looking at your nginx.conf, what would have to change if you moved each of those services to different servers? Is there anything you’d have to check on the server itself?\nLet’s say you’ve got a private VPC that hosts an instance of RStudio Server, an instance of JupyterHub, and a Shiny Server that has an app deployed. Here are a few examples of traffic – are they outbound, inbound, or within the network?\n\nSomeone connecting to and starting a session on RStudio Server.\nSomeone SFTP-ing an app and packages from RStudio Server to Shiny Server.\nSomeone installing a package to the Shiny Server.\nSomeone uploading a file to JupyterHub.\nA call in a Shiny app using httr2 or requests to a public API that hosts data.\nAccessing a private corporate database from a Shiny for Python app using sqlalchemy.\n\nWhat are the most likely pain points for running a data science workbench that is fully offline/airgapped?"
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+    "section": "16.3 Comprehension Questions",
+    "text": "16.3 Comprehension Questions\n\nWhat is the advantage of adopting a more complex networking setup than a server just deployed directly on the internet? Are there advantages other than security?\nDraw a mental map with the following entities: inbound traffic, outbound traffic, proxy, DMZ, private subnet, public subnet, VPC\nOur workbench server has an nginx proxy that redirects inbound traffic on a few different paths to the right port on the same server. Looking at your nginx.conf, what would have to change if you moved each of those services to different servers? Is there anything you’d have to check on the server itself?\nLet’s say you’ve got a private VPC that hosts an instance of RStudio Server, an instance of JupyterHub, and a Shiny Server that has an app deployed. Here are a few examples of traffic – are they outbound, inbound, or within the network?\n\nSomeone connecting to and starting a session on RStudio Server.\nSomeone SFTP-ing an app and packages from RStudio Server to Shiny Server.\nSomeone installing a package to the Shiny Server.\nSomeone uploading a file to JupyterHub.\nA call in a Shiny app using httr2 or requests to a public API that hosts data.\nAccessing a private corporate database from a Shiny for Python app using sqlalchemy.\n\nWhat are the most likely pain points for running a data science workbench that is fully offline/airgapped?"
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-    "title": "18  Auth in Enterprise",
-    "section": "18.1 How IT/Admins think about auth",
-    "text": "18.1 How IT/Admins think about auth\nLet’s start with an analogy to the real world. Imagine all the different services your company’s IT/Admin team manages as rooms in a building. Email, databases, data science workbenches, social media accounts, HR systems, and more. Each one is a room in the building.\nIn order to comply with the principle of least privilege, people are given access only to the rooms they need. Now imagine you’re the one who has to figure out how to keep it all secure.\nWhen someone tries to enter a room, you’ll need a way to know who’s asking – to ascertain and validate their identity. This process is called authentication.\nBut just knowing who they are is insufficient. Remember, not everyone gets to access every room. So you’ll also need a way to check whether they have permission to access that room. That process is called authorization.\nTogether, the whole system of authenticating and authorizing people to take actions is called auth.\nMany organizations start out simply. They just add IT systems one at a time and use their built-in auth functionality. That’d be like posting a guard at the door to each room who don’t talk to each other.\nEach guard would issue some sort of credential that can be used to verify that the person approaching is who they say they are. For computer systems, the most common type of credential is a username and password combination.\nIncreasingly, organizations are moving towards other kinds of credentials instead of or in addition to usernames and passwords, including biometrics like fingerprints and facial identification, multi-factor codes or a push notification on your phone, or ID cards of some sort.\nBut just having each guard keep their own list of who’s allowed in and hand out their own credential is kinda a mess. As someone walking around the building, you’ve gotta keep all your credentials straight. Moreover, adding new people to the different systems or removing old people is a huge pain. You’ve gotta run around and tell each guard and then the guard has to revoke their credential.\nThis is a common scenario in small organizations without much central IT/Admin expertise. They tend to just use whatever auth comes with the systems they’re adopting.\nIn the labs in section 3, this is how we configured our server. We created a standalone server with standalone credentials. And while that’s secure enough on its own, it doesn’t integrate with any central IT/Admin capabilities.\nObviously, among enterprise organizations, this pattern doesn’t fly. If you’re only a team of 20 and you have 5 systems, it’s ok to metaphorically run around to each room. But a team of 2,000 or 20,000 with 50 or 500 systems can’t be managed this way.\nSo let’s start thinking about how we could make the management of this system simpler and easier.\n\n18.1.1 Centralizing user management with LDAP/AD\nThe first thing would be to standardize on a single set of credentials. No more letting each guard issue their own. You’ll create a central security booth where you’ll manage all the credentials. Whenever someone approaches a door, the guard will radio in the credential, you’ll verify that all is well and tell the guard, “yep, that’s Heather!”\nThis makes life easier for someone using the system since they have only one set of credentials. It’s also somewhat more secure. We know now that all of the doors are using a similar level of security and if someone loses their card or gets it stolen, we just have to do one trade.\nThis is basically the situation that many companies have been in from the mid 1990s onwards and many still use.\nAn open protocol called Lightweight Directory Access Protocol (LDAP – pronounced ell-dap) and the Microsoft implementation of LDAP called Active Directory (AD) allow organizations to maintain central lists of users and the groups to which they belong.\nThey configure their systems to query their LDAP/AD servers. LDAP/AD would sends back information on the user including their username and groups and the service could use that information to authorize the user.\nThis is a huge improvement over each system having its own set of credentials, but there are still three big issues.\nFirst, we haven’t done anything to make authorization easier. You’re now centrally verifying identities, but each guard still needs to maintain their own list of who’s allowed into their room. Changing those lists still requires running around to each room, which is time-consuming and error-prone.\nSecond, just how much do you trust those guards? The guards are radioing in the credentials. There’s nothing to stop them from writing them down for themselves.\nLastly, it’s kinda a pain. Having to re-authenticate at every door is a pain. If you’re logging into a lot of different systems, you’re going to have to authenticate dozens of times a day.\nOver time, these problems have only gotten keener. A few decades ago, most companies had only a few systems and they were probably all on-premise systems, reducing both the hassle of changes and the risk of credentials actually being entered to those systems.\nThese days, even modestly-sized organizations have dozens or hundreds of IT systems and many of them are SaaS services. That means the risk of sharing credentials with those services is much higher.\nWouldn’t it be nice if there were a way to solve all these problems? A solution would allow for centralized authorization, never sharing credentials with the guards, and authenticating only once.\nEnter the world of Single-Sign On (SSO).\n\n\n18.1.2 Single Sign On (SSO)\nOk, so let’s revamp the system one more time.\nNow, when someone enters the building, they’ll stop at the central security office and provide their credentials. In exchange, they’ll get a building access pass that’s unique to them and they cannot share.\nMoreover, you’ll equip each room with a machine to swipe a building access pass. Swiping the access pass sends a request back to the central security office with the person’s name and the room number. You can check whether they’re allowed in and send back the allow signal if so and the red disallow signal if not.\nNow, the guards don’t need to know anything about the people approaching and don’t need to be trusted to do anything other than appropriately respond to the allow/disallow indicator.\nMoreover, you can now manage authorization in the central security office. No more running around to each room when you need to onboard or offboard someone or change their role.\nThis is basically how SSO works – your building access pass is a token in your computer’s web browser, and the allow/disallow decision comes from the centralized auth management system.\nNow, SSO isn’t a description of a technology – it’s a description of a user and administrator experience. People have been making SSO work for a long time, but two main standards for doing SSO have arisen in the past 15 years or so.1\nThe most common option in enterprises is Security Assertion Markup Language (SAML), which is an XML-based standard.2 The current standard, SAML 2.0 was finalized in 2005.\nThe other option is Open Identity Connect (OIDC)/OAuth2.0, which used JSON-based tokens.3 It’s slightly newer than SAML, originally created by engineers at Google and Twitter in 2007. OAuth2 – the current standard – was released in 2012.\nFor nearly all SAML or OAuth implementations, organizations use an external identity manager. The most common ones to use are Okta, OneLogin, and Azure Active Directory (AAD).4\nThese days, almost all enterprises are moving quickly towards implementing SSO using either SAML or OAuth (or both).\nThere’s a lot more detail on the technical details of how LDAP, OAuth, SAML, and more work in Appendix A.\n\n\n18.1.3 Managing permissions\nIrrespective of what kind of auth technology you’re using, you have to actually manage permissions somehow. It’s worth learning a little about the options.\nThe simplest option is just to maintain a list of who’s allowed to enter each room. This is called an Access Control List (ACL).5\nACLs are a simple kind of permissions management that make a lot of intuitive sense.\nBut, as you can imagine, if your building has hundreds of rooms, that’s a lot of different rooms to keep individual lists for. Additionally, if you have permissions changing a lot, having to change individual user permissions is a pain.\nInstead, you might want to create a role that has certain permissions and then assign people to that role. For example, maybe there’s the role of manager, who has access to certain rooms. There might be another role that’s executive who has access to different rooms. Managing permissions in this way is called Role Based Access Control (RBAC), and many organizations have a requirement to be able to implement RBAC to adopt a new system.\n\nRBAC has the advantage of allowing more flexibility in creating roles and managing them relative to ACLs. You can also see how it’d be relatively simple to hook up something like your centralized HR database to an RBAC system by mapping actual users to a set of roles that is appropriate for them.\nBut RBAC has its own drawbacks. RBAC can result in role explosion over time – if people need specialized permissions, it’s often easier to create tons and tons of special roles rather than figure out how to harmonize them into a system.\nIt also can’t accommodate certain kinds of highly specific permissions scenarios. For example, what if you have a situation where room 4242 should only allow managers except from 9-12 on Tuesdays when it should allow maintenance services? That’s not something RBAC can accommodate.\nIf you have the need for even more granular permissions than RBAC can provide, you can create rules based on the room, the person, and the environment. This highly-flexible system is called Attribute Based Access Control (ABAC). The downside of ABAC is that it can be a real pain to set up because it is so powerful.\nTODO: ABAC diagram (mapping room 4242 to person/manager to environment)\nThe most well-known ABAC system is the AWS Identity and Access Management (IAM) system. If you’ve ever been utterly befuddled by applying permissions to resources in AWS, you can thank the complexity of ABAC. That complexity is the tradeoff for the very high degree of flexibility ABAC provides."
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+    "text": "17.1 How IT/Admins think about auth\nLet’s start with an analogy to the real world. Imagine all the different services your company’s IT/Admin team manages as rooms in a building. Email, databases, data science workbenches, social media accounts, HR systems, and more. Each one is a room in the building.\nIn order to comply with the principle of least privilege, people are given access only to the rooms they need. Now imagine you’re the one who has to figure out how to keep it all secure.\nWhen someone tries to enter a room, you’ll need a way to know who’s asking – to ascertain and validate their identity. This process is called authentication.\nBut just knowing who they are is insufficient. Remember, not everyone gets to access every room. So you’ll also need a way to check whether they have permission to access that room. That process is called authorization.\nTogether, the whole system of authenticating and authorizing people to take actions is called auth.\nMany organizations start out simply. They just add IT systems one at a time and use their built-in auth functionality. That’d be like posting a guard at the door to each room who don’t talk to each other.\nEach guard would issue some sort of credential that can be used to verify that the person approaching is who they say they are. For computer systems, the most common type of credential is a username and password combination.\nIncreasingly, organizations are moving towards other kinds of credentials instead of or in addition to usernames and passwords, including biometrics like fingerprints and facial identification, multi-factor codes or a push notification on your phone, or ID cards of some sort.\nBut just having each guard keep their own list of who’s allowed in and hand out their own credential is kinda a mess. As someone walking around the building, you’ve gotta keep all your credentials straight. Moreover, adding new people to the different systems or removing old people is a huge pain. You’ve gotta run around and tell each guard and then the guard has to revoke their credential.\nThis is a common scenario in small organizations without much central IT/Admin expertise. They tend to just use whatever auth comes with the systems they’re adopting.\nIn the labs in section 3, this is how we configured our server. We created a standalone server with standalone credentials. And while that’s secure enough on its own, it doesn’t integrate with any central IT/Admin capabilities.\nObviously, among enterprise organizations, this pattern doesn’t fly. If you’re only a team of 20 and you have 5 systems, it’s ok to metaphorically run around to each room. But a team of 2,000 or 20,000 with 50 or 500 systems can’t be managed this way.\nSo let’s start thinking about how we could make the management of this system simpler and easier.\n\n17.1.1 Centralizing user management with LDAP/AD\nThe first thing would be to standardize on a single set of credentials. No more letting each guard issue their own. You’ll create a central security booth where you’ll manage all the credentials. Whenever someone approaches a door, the guard will radio in the credential, you’ll verify that all is well and tell the guard, “yep, that’s Heather!”\nThis makes life easier for someone using the system since they have only one set of credentials. It’s also somewhat more secure. We know now that all of the doors are using a similar level of security and if someone loses their card or gets it stolen, we just have to do one trade.\nThis is basically the situation that many companies have been in from the mid 1990s onwards and many still use.\nAn open protocol called Lightweight Directory Access Protocol (LDAP – pronounced ell-dap) and the Microsoft implementation of LDAP called Active Directory (AD) allow organizations to maintain central lists of users and the groups to which they belong.\nThey configure their systems to query their LDAP/AD servers. LDAP/AD would sends back information on the user including their username and groups and the service could use that information to authorize the user.\nThis is a huge improvement over each system having its own set of credentials, but there are still three big issues.\nFirst, we haven’t done anything to make authorization easier. You’re now centrally verifying identities, but each guard still needs to maintain their own list of who’s allowed into their room. Changing those lists still requires running around to each room, which is time-consuming and error-prone.\nSecond, just how much do you trust those guards? The guards are radioing in the credentials. There’s nothing to stop them from writing them down for themselves.\nLastly, it’s kinda a pain. Having to re-authenticate at every door is a pain. If you’re logging into a lot of different systems, you’re going to have to authenticate dozens of times a day.\nOver time, these problems have only gotten keener. A few decades ago, most companies had only a few systems and they were probably all on-premise systems, reducing both the hassle of changes and the risk of credentials actually being entered to those systems.\nThese days, even modestly-sized organizations have dozens or hundreds of IT systems and many of them are SaaS services. That means the risk of sharing credentials with those services is much higher.\nWouldn’t it be nice if there were a way to solve all these problems? A solution would allow for centralized authorization, never sharing credentials with the guards, and authenticating only once.\nEnter the world of Single-Sign On (SSO).\n\n\n17.1.2 Single Sign On (SSO)\nOk, so let’s revamp the system one more time.\nNow, when someone enters the building, they’ll stop at the central security office and provide their credentials. In exchange, they’ll get a building access pass that’s unique to them and they cannot share.\nMoreover, you’ll equip each room with a machine to swipe a building access pass. Swiping the access pass sends a request back to the central security office with the person’s name and the room number. You can check whether they’re allowed in and send back the allow signal if so and the red disallow signal if not.\nNow, the guards don’t need to know anything about the people approaching and don’t need to be trusted to do anything other than appropriately respond to the allow/disallow indicator.\nMoreover, you can now manage authorization in the central security office. No more running around to each room when you need to onboard or offboard someone or change their role.\nThis is basically how SSO works – your building access pass is a token in your computer’s web browser, and the allow/disallow decision comes from the centralized auth management system.\nNow, SSO isn’t a description of a technology – it’s a description of a user and administrator experience. People have been making SSO work for a long time, but two main standards for doing SSO have arisen in the past 15 years or so.1\nThe most common option in enterprises is Security Assertion Markup Language (SAML), which is an XML-based standard.2 The current standard, SAML 2.0 was finalized in 2005.\nThe other option is Open Identity Connect (OIDC)/OAuth2.0, which used JSON-based tokens.3 It’s slightly newer than SAML, originally created by engineers at Google and Twitter in 2007. OAuth2 – the current standard – was released in 2012.\nFor nearly all SAML or OAuth implementations, organizations use an external identity manager. The most common ones to use are Okta, OneLogin, and Azure Active Directory (AAD).4\nThese days, almost all enterprises are moving quickly towards implementing SSO using either SAML or OAuth (or both).\nThere’s a lot more detail on the technical details of how LDAP, OAuth, SAML, and more work in Appendix A.\n\n\n17.1.3 Managing permissions\nIrrespective of what kind of auth technology you’re using, you have to actually manage permissions somehow. It’s worth learning a little about the options.\nThe simplest option is just to maintain a list of who’s allowed to enter each room. This is called an Access Control List (ACL).5\nACLs are a simple kind of permissions management that make a lot of intuitive sense.\nBut, as you can imagine, if your building has hundreds of rooms, that’s a lot of different rooms to keep individual lists for. Additionally, if you have permissions changing a lot, having to change individual user permissions is a pain.\nInstead, you might want to create a role that has certain permissions and then assign people to that role. For example, maybe there’s the role of manager, who has access to certain rooms. There might be another role that’s executive who has access to different rooms. Managing permissions in this way is called Role Based Access Control (RBAC), and many organizations have a requirement to be able to implement RBAC to adopt a new system.\n\nRBAC has the advantage of allowing more flexibility in creating roles and managing them relative to ACLs. You can also see how it’d be relatively simple to hook up something like your centralized HR database to an RBAC system by mapping actual users to a set of roles that is appropriate for them.\nBut RBAC has its own drawbacks. RBAC can result in role explosion over time – if people need specialized permissions, it’s often easier to create tons and tons of special roles rather than figure out how to harmonize them into a system.\nIt also can’t accommodate certain kinds of highly specific permissions scenarios. For example, what if you have a situation where room 4242 should only allow managers except from 9-12 on Tuesdays when it should allow maintenance services? That’s not something RBAC can accommodate.\nIf you have the need for even more granular permissions than RBAC can provide, you can create rules based on the room, the person, and the environment. This highly-flexible system is called Attribute Based Access Control (ABAC). The downside of ABAC is that it can be a real pain to set up because it is so powerful.\nTODO: ABAC diagram (mapping room 4242 to person/manager to environment)\nThe most well-known ABAC system is the AWS Identity and Access Management (IAM) system. If you’ve ever been utterly befuddled by applying permissions to resources in AWS, you can thank the complexity of ABAC. That complexity is the tradeoff for the very high degree of flexibility ABAC provides."
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-    "text": "18.2 Data Science Auth Concerns\nThe first and simplest concern that comes up for a new data science workbench is that it needs to support whatever auth mechanism your IT/Admin group has decided your organization is going to use. Hopefully you now have some context on what those various mechanisms are.\nThese days, most data science tools you might want to use support all of the standard SSO mechanisms – though many of them reserve that functionality for paid tiers.\n\n18.2.1 Data Access\nThe second concern that comes up is how to get access to data. In our building metaphor, this would be like sending a note from one room asking for a resource in another room.\nThis kind of access is actually easier to configure in a non-SSO configuration. If your database can be accessed with a username and password, it’s the equivalent of being able to just put your request on a piece of paper and append your credentials. The guard can verify the credentials and send back the proper information.\nIt’s worth noting that this configuration is still quite common. Most organizations have implemented SSO for their external-facing services, but internal data sources are often available with username and password auth. This is mostly because relatively few databases have implemented SSO configurations. I expect this will change quickly in the next few years.\nIn an SSO configuration, getting access to data is kinda complicated. Remember, you’re sitting in a room and you’ve got your building access pass, which you can’t give to anyone, and you can’t get access to another room without swiping your pass at the door.\nThe main way this is accomplished is by giving people the ability to remotely acquire the data room access token without actually going there with the building access pass. Depending on the tool you’re using and the type of technology being used, it may be able to automatically do this exchange for you or you may have to do it manually in your code.\nThe first technology used to authenticate to data services is a Windows-based system called a Kerberos ticket. Kerberos is a relatively old – but highly secure system. Kerberos is mainly used in Windows-based environments, so it’s mostly used when accessing a Microsoft SQL Server.\nIf your organization uses Kerberos for database access, you’ll need to work with your organization’s IT/Admin group to get everything configured.\nThe second way to accomplish SSO into a data source is to pass along an JSON Web Token (JWT, pronounced jot). JWTs are the technology that underlies OAuth/OIDC. They’re accepted by relatively few databases these days, but I expect that will change in the next few years.\nFor more technical details on how this experience is implemented, and some of the technical difficulties you may run into, see the appendix section on OAuth and SAML.\nThe last way to access a data source seamlessly is via integration with cloud IAM services. This will only work if you’re trying to access a cloud resource from another cloud resource. So you could allow access from an EC2 instance to an S3 bucket, but not from your on-prem compute cluster to an S3 bucket.\nThe patterns for doing this vary a lot by cloud and by the data science tooling you’re using. Configuring a cloud instance to “just know” who’s making a request is possible, but requires some savvy with managing cloud services.\n\n\n18.2.2 Service Accounts\nThe last concern that comes up a lot is what entity is doing the access. In workbench environments, it’s common for humans to have credentials to data sources and to login as themselves. However, when those resources go to production, it’s very common to introduce service accounts.\nA service account is a non-human entity that has permissions of its own. For example, maybe you’ve got a Shiny app that users use to visualize data that’s in a database. Very often, you don’t want the app to have the same permisions as the app’s author, or to inherit the permissions of the people viewing the app.\nOne important reason you might want this is that you want to manage the permissions of the app itself even if the author were to leave the company or change roles.\nInstead, you want the app to be able to have permissions to do certain database operations. In that case, you would create a service account to give to the Shiny app that has exactly those permissions.\nThere’s no particular magic to service accounts, but you’ll need to figure out how to make your app or report run as the right user and have the correct service account credentials."
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+    "text": "17.2 Data Science Auth Concerns\nThe first and simplest concern that comes up for a new data science workbench is that it needs to support whatever auth mechanism your IT/Admin group has decided your organization is going to use. Hopefully you now have some context on what those various mechanisms are.\nThese days, most data science tools you might want to use support all of the standard SSO mechanisms – though many of them reserve that functionality for paid tiers.\n\n17.2.1 Data Access\nThe second concern that comes up is how to get access to data. In our building metaphor, this would be like sending a note from one room asking for a resource in another room.\nThis kind of access is actually easier to configure in a non-SSO configuration. If your database can be accessed with a username and password, it’s the equivalent of being able to just put your request on a piece of paper and append your credentials. The guard can verify the credentials and send back the proper information.\nIt’s worth noting that this configuration is still quite common. Most organizations have implemented SSO for their external-facing services, but internal data sources are often available with username and password auth. This is mostly because relatively few databases have implemented SSO configurations. I expect this will change quickly in the next few years.\nIn an SSO configuration, getting access to data is kinda complicated. Remember, you’re sitting in a room and you’ve got your building access pass, which you can’t give to anyone, and you can’t get access to another room without swiping your pass at the door.\nThe main way this is accomplished is by giving people the ability to remotely acquire the data room access token without actually going there with the building access pass. Depending on the tool you’re using and the type of technology being used, it may be able to automatically do this exchange for you or you may have to do it manually in your code.\nThe first technology used to authenticate to data services is a Windows-based system called a Kerberos ticket. Kerberos is a relatively old – but highly secure system. Kerberos is mainly used in Windows-based environments, so it’s mostly used when accessing a Microsoft SQL Server.\nIf your organization uses Kerberos for database access, you’ll need to work with your organization’s IT/Admin group to get everything configured.\nThe second way to accomplish SSO into a data source is to pass along an JSON Web Token (JWT, pronounced jot). JWTs are the technology that underlies OAuth/OIDC. They’re accepted by relatively few databases these days, but I expect that will change in the next few years.\nFor more technical details on how this experience is implemented, and some of the technical difficulties you may run into, see the appendix section on OAuth and SAML.\nThe last way to access a data source seamlessly is via integration with cloud IAM services. This will only work if you’re trying to access a cloud resource from another cloud resource. So you could allow access from an EC2 instance to an S3 bucket, but not from your on-prem compute cluster to an S3 bucket.\nThe patterns for doing this vary a lot by cloud and by the data science tooling you’re using. Configuring a cloud instance to “just know” who’s making a request is possible, but requires some savvy with managing cloud services.\n\n\n17.2.2 Service Accounts\nThe last concern that comes up a lot is what entity is doing the access. In workbench environments, it’s common for humans to have credentials to data sources and to login as themselves. However, when those resources go to production, it’s very common to introduce service accounts.\nA service account is a non-human entity that has permissions of its own. For example, maybe you’ve got a Shiny app that users use to visualize data that’s in a database. Very often, you don’t want the app to have the same permisions as the app’s author, or to inherit the permissions of the people viewing the app.\nOne important reason you might want this is that you want to manage the permissions of the app itself even if the author were to leave the company or change roles.\nInstead, you want the app to be able to have permissions to do certain database operations. In that case, you would create a service account to give to the Shiny app that has exactly those permissions.\nThere’s no particular magic to service accounts, but you’ll need to figure out how to make your app or report run as the right user and have the correct service account credentials."
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-    "text": "18.3 Comprehension Questions\n\nWhat is the difference between authentication and authorization?\nWhat are some different ways to manage permissions? What are the advantages and drawbacks of each?\nWhat is some advantages of token-based auth? Why are most organizations adopting it? Are there any drawbacks?\nFor each of the following, is it a username + password method or a token method? PAM, LDAP, Kerberos, SAML, ODIC/OAuth"
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+    "text": "17.3 Comprehension Questions\n\nWhat is the difference between authentication and authorization?\nWhat are some different ways to manage permissions? What are the advantages and drawbacks of each?\nWhat is some advantages of token-based auth? Why are most organizations adopting it? Are there any drawbacks?\nFor each of the following, is it a username + password method or a token method? PAM, LDAP, Kerberos, SAML, ODIC/OAuth"
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-    "text": "Aside from the options below, some organizations use a system called Kerberos to accomplish SSO. This is quite rare.↩︎\nXML is a markup language, much like HTML. The good thing about XML is that it’s very flexible. The bad thing is that it’s relatively hard for a human to easily read.↩︎\nTechnically, OIDC is an authentication standard and OAuth is an authorization standard. You’ll usually just hear it all referred to as OAuth.↩︎\nYes, AAD is used for SAML/OAuth, not for LDAP. It’s confusing.↩︎\nStandard Linux permissions (POSIX permissons) that were discussed in Chapter 11 are basically a special case of ACLs. ACLs allow setting individual-level permissions for any number of users and groups, as opposed to the one owner, one group, and everyone else permissions set for POSIX.\nLinux distros now have support for ACLs on top of the standard POSIX permissions.↩︎"
+    "text": "Aside from the options below, some organizations use a system called Kerberos to accomplish SSO. This is quite rare.↩︎\nXML is a markup language, much like HTML. The good thing about XML is that it’s very flexible. The bad thing is that it’s relatively hard for a human to easily read.↩︎\nTechnically, OIDC is an authentication standard and OAuth is an authorization standard. You’ll usually just hear it all referred to as OAuth.↩︎\nYes, AAD is used for SAML/OAuth, not for LDAP. It’s confusing.↩︎\nStandard Linux permissions (POSIX permissons) that were discussed in Chapter 9 are basically a special case of ACLs. ACLs allow setting individual-level permissions for any number of users and groups, as opposed to the one owner, one group, and everyone else permissions set for POSIX.\nLinux distros now have support for ACLs on top of the standard POSIX permissions.↩︎"
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-    "section": "19.1 Managing complexity with Infrastructure as Code",
-    "text": "19.1 Managing complexity with Infrastructure as Code\nHere’s where you don’t want to be an an enterprise IT/Admin. You stand up a server for the data science team in a known good state – with versions of R and Python and the applications they need. But then, over time, more stuff gets installed. Maybe they needed some more versions of R. And that package they installed required some updated system libraries.\nIf you just ssh in and do these things — or let the data science team do it themselves, you’ll quickly lose track of what the current state of the server is. You can’t just tear down the server and stand it back up, because none of the changes you’ve made are documented. In DevOps language, the server has become stateful – and that’s a no-no.\nNow, when you’ve just got one server like this, it’s annoying, but not the end of the world. If you’re an IT/Admin organization with 40 or 400 servers it is much more troublesome. And moreover, if you have many servers that need to be configured identically – for example because they’re treated as one cluster – this is impossible. In many enterprises, this whole though experiment would just never fly because production servers can’t be changed. They’re validated from top to bottom for compliance or security reasons and then have to be completely re-validated if any changes are needed.\nIT/Admin organizations want to avoid server state drift and make sure the environment is always in a known good state. If it ever needs to be torn down or moved, it should be a painless activity to re-create the exact same environment with a minimum of fuss.\nThere’s a DevOps adage to encompass this need to manage servers as a herd, rather than individually – servers should be cattle, not pets.\nTo restart an entire server environment from nothing, there are two general steps. Provisioning is about creating and configuring the (virtualized) hardware including the servers and networking configuration. Once the servers are provisioned, they need to be configured including installing things on them and getting them running.\nIf you’re thinking of restarting an environment from scratch, you need to\n\nCreate the networking environment for servers (VPC)\nStand up the actual servers and networking facilities\nConfigure servers (create users, groups, mount storage, etc)\nConfigure networking hardware (ports, firewalls, etc)\nInstall system libraries and operating system dependencies\nInstall R and/or Python\nInstall application layer (RStudio Server, JupyterLab, Shiny Server, etc)\nConfigure application layer (write config files)\nConfigure application layer networking (SSL, DNS)\nStart application\n\nAs an R or Python-loving data scientist, you know that the best way to create this kind of setup is with code. Much like you can use packages like renv and venv to document the state of your R or Python environment and restore it somewhere else (see Chapter 1), IT/Admin professionals use Infrastructure as Code (IaC) tooling to stand up and manage their servers.\nIt’s not always the case that organizations need to put all of this in code. For example, while servers should be re-create-able in code, it’s quite rare that you need to re-create a VPC, so it may well be the case that step remains manual.\nEither way, some names you’ll hear a lot if you’re looking into IaC are Terraform, Ansible, CloudFormation (AWS’s IaC tool), Chef, Puppet, and Pulumi. The other option, which we’ll discuss in more detail below, is using Docker in Kubernetes.\n\n\n\n\n\n\nNo Code IaC\n\n\n\nThere are also ways to manage enterprise servers that don’t involve IaC. These usually involve writing extensive “run-books” for how to configure servers or point-and-click graphical interfaces for server administration. If your spidey sense is tingling that this probably isn’t nearly as good, you’re right. Enterprise IT/Admin organizations that don’t use IaC tooling is definitely a red flag.\n\n\nWe’re not going to get into any more detail on how these IaC tools work – there are books on all of them you should feel free to read if you’re interested. But now you’ll understand what you’re hearing when the IT/Admin team says they need to write a Terraform script or a Chef recipe to be able to stand up a particular service.\n\n19.1.1 Dev/Test/Prod for IT/Admins\nLike you want a Dev/Test/Prod setup for your data science projects as discussed in Chapter 5, IT/Admins usually use a Dev/Test/Prod setup for themselves. They want an environment to test changes before promoting them for testing and eventually into production. In ideal states, even changes in Dev are only attempted with IaC tools to make sure it’s easy to move forward once the changes are final.\nIn enterprises, upgrades and migrations are major to-dos. Planning for a “lift-and-shift” to the cloud is a multi-year affair in many organizations. Even just upgrading operating systems can be a major undertaking.\nFor enterprises, I recommend a two-dimensional Dev/Test/Prod setup where the IT/Admin group make changes to the platform in a staging environment.1 Data scientists never get access to the Staging environments and do all their work in the IT/Admin prod environment.\n\nLooking back to Chapter 5, it should be obvious that the best way to move servers and applications from staging to prod is using IaC and CI/CD to make sure that changes to code always make it into production at the right time."
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+    "text": "18.1 Managing complexity with Infrastructure as Code\nHere’s where you don’t want to be an an enterprise IT/Admin. You stand up a server for the data science team in a known good state – with versions of R and Python and the applications they need. But then, over time, more stuff gets installed. Maybe they needed some more versions of R. And that package they installed required some updated system libraries.\nIf you just ssh in and do these things — or let the data science team do it themselves, you’ll quickly lose track of what the current state of the server is. You can’t just tear down the server and stand it back up, because none of the changes you’ve made are documented. In DevOps language, the server has become stateful – and that’s a no-no.\nNow, when you’ve just got one server like this, it’s annoying, but not the end of the world. If you’re an IT/Admin organization with 40 or 400 servers it is much more troublesome. And moreover, if you have many servers that need to be configured identically – for example because they’re treated as one cluster – this is impossible. In many enterprises, this whole though experiment would just never fly because production servers can’t be changed. They’re validated from top to bottom for compliance or security reasons and then have to be completely re-validated if any changes are needed.\nIT/Admin organizations want to avoid server state drift and make sure the environment is always in a known good state. If it ever needs to be torn down or moved, it should be a painless activity to re-create the exact same environment with a minimum of fuss.\nThere’s a DevOps adage to encompass this need to manage servers as a herd, rather than individually – servers should be cattle, not pets.\nTo restart an entire server environment from nothing, there are two general steps. Provisioning is about creating and configuring the (virtualized) hardware including the servers and networking configuration. Once the servers are provisioned, they need to be configured including installing things on them and getting them running.\nIf you’re thinking of restarting an environment from scratch, you need to\n\nCreate the networking environment for servers (VPC)\nStand up the actual servers and networking facilities\nConfigure servers (create users, groups, mount storage, etc)\nConfigure networking hardware (ports, firewalls, etc)\nInstall system libraries and operating system dependencies\nInstall R and/or Python\nInstall application layer (RStudio Server, JupyterLab, Shiny Server, etc)\nConfigure application layer (write config files)\nConfigure application layer networking (SSL, DNS)\nStart application\n\nAs an R or Python-loving data scientist, you know that the best way to create this kind of setup is with code. Much like you can use packages like renv and venv to document the state of your R or Python environment and restore it somewhere else (see Chapter 1), IT/Admin professionals use Infrastructure as Code (IaC) tooling to stand up and manage their servers.\nIt’s not always the case that organizations need to put all of this in code. For example, while servers should be re-create-able in code, it’s quite rare that you need to re-create a VPC, so it may well be the case that step remains manual.\nEither way, some names you’ll hear a lot if you’re looking into IaC are Terraform, Ansible, CloudFormation (AWS’s IaC tool), Chef, Puppet, and Pulumi. The other option, which we’ll discuss in more detail below, is using Docker in Kubernetes.\n\n\n\n\n\n\nNo Code IaC\n\n\n\nThere are also ways to manage enterprise servers that don’t involve IaC. These usually involve writing extensive “run-books” for how to configure servers or point-and-click graphical interfaces for server administration. If your spidey sense is tingling that this probably isn’t nearly as good, you’re right. Enterprise IT/Admin organizations that don’t use IaC tooling is definitely a red flag.\n\n\nWe’re not going to get into any more detail on how these IaC tools work – there are books on all of them you should feel free to read if you’re interested. But now you’ll understand what you’re hearing when the IT/Admin team says they need to write a Terraform script or a Chef recipe to be able to stand up a particular service.\n\n18.1.1 Dev/Test/Prod for IT/Admins\nLike you want a Dev/Test/Prod setup for your data science projects as discussed in Chapter 5, IT/Admins usually use a Dev/Test/Prod setup for themselves. They want an environment to test changes before promoting them for testing and eventually into production. In ideal states, even changes in Dev are only attempted with IaC tools to make sure it’s easy to move forward once the changes are final.\nIn enterprises, upgrades and migrations are major to-dos. Planning for a “lift-and-shift” to the cloud is a multi-year affair in many organizations. Even just upgrading operating systems can be a major undertaking.\nFor enterprises, I recommend a two-dimensional Dev/Test/Prod setup where the IT/Admin group make changes to the platform in a staging environment.1 Data scientists never get access to the Staging environments and do all their work in the IT/Admin prod environment.\n\nLooking back to Chapter 5, it should be obvious that the best way to move servers and applications from staging to prod is using IaC and CI/CD to make sure that changes to code always make it into production at the right time."
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-    "text": "19.2 Enterprise scale and stability\nNeeding to scale data science environments for large jobs is a common need across large and small organizations. But the enterprise need to support many data scientists often requires a different kind of approach to scaling.\nIn Chapter 15, we discussed how just making a single server bigger with vertical scaling can take you a long way. But there are limits. For example, I was recently working with a large customer of Posit’s who needed to support up to 2,000 data scientists in their environment.\nAt that scale, there is no server that is nearly large enough. The way to accomplish this kind of scale isto spread the workload out across many servers with horizontal scaling.\nAdditionally, when you’re operating at that scale, the stability of the system gets really important. When you’ve got 2,000 data scientists using your platform, each hour of lost time costs more than $100,000.2\nFor some organizations, this necessitates the creation of a disaster recovery plan. This may mean that there are frequent snapshots of the state of the server (often nightly) so the IT/Admins can just roll back to a previous known good state in the event of a failure. Sometimes it also means that there is actually a copy of the server waiting on standby to be activated at all times.\nOther times, there are stiffer requirements such that nodes in the cluster could fail and the users wouldn’t be meaningfully affected. This requirement for limited cluster downtime is often called high availability. High availability is not a description of a particular technology or technical approach – though it is sometimes treated as such. High availability is a description of a desired outcome for a cluster and different organizations have different definitions.\n\n\n\n\n\n\nMeasuring Uptime\n\n\n\nDowntime limits are often measured in nines of uptime. Nines of uptime refers to the proportion of the time that the service is guaranteed to be online out of a year. So a one-nine service is guaranteed to be up 90% of the time, allowing for 36 days of downtime a year. A five-nine service is up for 99.999% of the time, allowing for only about 5 1/4 minutes of downtime a year.\n\n\nHorizontal scaling and high availability are different of requirements with different implications. Depending on your organization, you may have horizontal scaling requirements or high availability requirements or both.\nOne option, where you have horizontal scaling requirements, but not high availability is to just put different users or team on their own server. The upside to this is that the team gets ownership of the server. The downside is fragmentation and that the team has to manage your own servers. In organizations that allow this kind of fragmentation, each team is usually on their own to support those servers and you’re basically back in non-enterprise land.\nIn enterprises, this usually isn’t the way things get done. Most enterprises want to run one centralized service that everyone in the company – or at least across a large group – come to.\nIf you’re trying to run a large centralized service, it’s going to be run as a load-balanced cluster. In this context, you don’t want to think about individual servers. Instead, you want to manage the cluster as a whole and make it really easy to add individual servers, called nodes.\nIn order to go from a single server to a cluster, you add two requirements – there needs to be one front door to all the servers, called a load-balancer – and any state users care about needs to move from the individual server to a shared location all of the nodes can access. Usually that state is stored in a database or network attached storage (NAS), which is just a filesystem that lives on its own server.\n\nIf you are a solo data scientist reading this – please do not try to run your own data science cluster. When you undertake load balancing, you’ve taken on a distributed systems problem and those are inherently difficult. When done for scaling reasons, it is almost always worthwhile to exhaust the part of vertical scaling where costs grow linearly with compute before undertaking horizontal scaling.\nIf your organization has high availability requirements, it’s worth considering that just adding more nodes may not be sufficient. As the requirements for high availability get steeper, the engineering cost to make sure the service really is that resilient rise exponentially. In addition to considering what to do if a node goes offline, you also have to have backup for the load-balancer and the database/NAS, as well as any other part of the system.\nIn fact, it’s totally possible to make your system less stable by just doing horizontal scaling in one spot without thinking through the implications.\n\n19.2.1 Load-balancing requirements\nLoad-balancers are just a special kind of proxy that routes sessions among the nodes in the cluster. A simple load-balancer just rotates sending traffic to the different nodes using a round-robin configuration.\nAt a minimum, your load-balancer has to know what nodes are accepting traffic. This is accomplished by configuring a health check/heartbeat endpoint for your product. A health check is a feature of an application. The load-balancer periodically pings the health check. If it gets a response, it knows it can send traffic to that node. If no response comes back, it treats that node as unhealthy and doesn’t send traffic there.\nIt is sometimes necessary to do more complicated load-balancing that pays attention to how loaded different nodes are. Additionally, some products feature internal load-balancers, so it really doesn’t matter what your load-balancer does.\nOne other feature that may come up is sticky sessions or sticky cookies. For stateful applications – like Shiny apps – you want to get back to the same node in the cluster so you can resume a previous session. In most load-balancers, this is a simple option you can just turn on.\nThere are a few different ways to configure load balancing for servers. The first is called active/active. This just means that all of the servers are online all of the time. So if I have two RStudio Server instances, they’re both accepting traffic all the time.\nIn active/passive configurations, you have two or more servers, with one set accepting traffing all the time, and the other set remaining inert until or unless the first set goes offline. This is sometimes called a blue/green or red/black configuration.\nPeople often really like this configuration if they have high requirements for uptime, and want to be able to do upgrades to the system behind the scenes and then just cut the traffic over at some point without an interruption in service. It is a nice idea. It is often very hard to pull off.\nFor an application, there are basically two ways it can store data – in a database or in files on the filesystem. Now, this isn’t data you need to access, but it’s needed for the internal workings of the application. For example, it may need to save log information or counts of the number of active users.\nWhen you’re in a single-server configuration, all this can just go somewhere on the server with the application. Very often the database is just a sqlite file that sits in a file on the filesystem.\nBut when you go to to a load-balanced cluster, all of the nodes need symmetric access to read and write. You need an actual database (like postgres) for the application to use. Additionally, anything on the filesystem now needs to move off of an individual server onto a networked system that all the nodes can access.\n\n\n19.2.2 Accommodating different kinds of workloads\nWhen you’re doing horizontal-scaling, people often want to accomodate a variety of workloads. For example, they might want to be able to incorporate several different sizes of jobs that might require a few different sized nodes. Or maybe they want to run a mixture of GPU-backed and non-GPU workloads in the cluster and want to reserve GPU nodes for the jobs that need it.\nIn general, it’s not trivial to set up a single cluster that can support different kinds of workloads, and it’s often easier to set up, for example, a standalone GPU cluster.\nThese days, people are often reaching for Kubernetes for clusters that need to support varies workloads. While it’s true that Kubernetes can theoretically support different kinds of nodes within one cluster, this often isn’t trivial to configure.\nOften, a better option for data science workloads is to use use a high-performance computing (HPC) framework. HPC is particularly appropriate when you need very large machines. In Kubernetes, it is not possible to schedule pods larger than the size of the actual nodes in the cluster. In contrast, most HPC frameworks allow you to combine an arbitrary number of nodes into what acts like a single machine with thousands or tens of thousands of nodes.\nFor example, Slurm is an HPC framework that support multiple queues for different sets of machines. AWS has a service called ParallelCluster that allows users to easily set up a Slurm cluster – and with no additional cost relative to the cost of the underlying AWS hardware.\n\n\n19.2.3 Adding Autoscaling\nSometimes people also undertake horizontal scaling to be able to do autoscaling. The idea here is that the organization could maintain a small amount of “always-on” capacity and scale out other capacity as needed to maintain costs. This is possible – but it requires nontrivial engineering work.\nIn particular, autoscaling a data science workbench down is quite hard. The main reason for this is that many autoscaling routines assume you can easily move someone’s job from one node to another just keeping track of the long-term state. This is a bad assumption for a data science workbench and autoscaling a data science workbench downwards is a difficult challenge.\nLet’s think about a relatively stateless workload. For example, let’s imagine a search engine – every time you put in a search, it spins up a job, does your search, and then spins down.\nIf you come back in a minute or two, it can just spin up another job. It only needs to remember your last query, but that’s a pretty simple bit to state to pass around. If you’re on a different node, no big deal!\nThat’s not the case with a data science workbench. Many autoscaling frameworks these days assume that applications are mostly stateless. In a stateless applications, every interaction is standalone – there’s very little path dependence. The line between statefulness and statelessness are pretty blurry, but working inside a development environment like RStudio or a Jupyter Notebook is about as stateful as it gets. You have long-term state like the files you need and your preferences and short-term state like the recent commands you’ve typed and the packages loaded into your R and Python environment."
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+    "text": "18.2 Enterprise scale and stability\nNeeding to scale data science environments for large jobs is a common need across large and small organizations. But the enterprise need to support many data scientists often requires a different kind of approach to scaling.\nIn Chapter 11, we discussed how just making a single server bigger with vertical scaling can take you a long way. But there are limits. For example, I was recently working with a large customer of Posit’s who needed to support up to 2,000 data scientists in their environment.\nAt that scale, there is no server that is nearly large enough. The way to accomplish this kind of scale isto spread the workload out across many servers with horizontal scaling.\nAdditionally, when you’re operating at that scale, the stability of the system gets really important. When you’ve got 2,000 data scientists using your platform, each hour of lost time costs more than $100,000.2\nFor some organizations, this necessitates the creation of a disaster recovery plan. This may mean that there are frequent snapshots of the state of the server (often nightly) so the IT/Admins can just roll back to a previous known good state in the event of a failure. Sometimes it also means that there is actually a copy of the server waiting on standby to be activated at all times.\nOther times, there are stiffer requirements such that nodes in the cluster could fail and the users wouldn’t be meaningfully affected. This requirement for limited cluster downtime is often called high availability. High availability is not a description of a particular technology or technical approach – though it is sometimes treated as such. High availability is a description of a desired outcome for a cluster and different organizations have different definitions.\n\n\n\n\n\n\nMeasuring Uptime\n\n\n\nDowntime limits are often measured in nines of uptime. Nines of uptime refers to the proportion of the time that the service is guaranteed to be online out of a year. So a one-nine service is guaranteed to be up 90% of the time, allowing for 36 days of downtime a year. A five-nine service is up for 99.999% of the time, allowing for only about 5 1/4 minutes of downtime a year.\n\n\nHorizontal scaling and high availability are different of requirements with different implications. Depending on your organization, you may have horizontal scaling requirements or high availability requirements or both.\nOne option, where you have horizontal scaling requirements, but not high availability is to just put different users or team on their own server. The upside to this is that the team gets ownership of the server. The downside is fragmentation and that the team has to manage your own servers. In organizations that allow this kind of fragmentation, each team is usually on their own to support those servers and you’re basically back in non-enterprise land.\nIn enterprises, this usually isn’t the way things get done. Most enterprises want to run one centralized service that everyone in the company – or at least across a large group – come to.\nIf you’re trying to run a large centralized service, it’s going to be run as a load-balanced cluster. In this context, you don’t want to think about individual servers. Instead, you want to manage the cluster as a whole and make it really easy to add individual servers, called nodes.\nIn order to go from a single server to a cluster, you add two requirements – there needs to be one front door to all the servers, called a load-balancer – and any state users care about needs to move from the individual server to a shared location all of the nodes can access. Usually that state is stored in a database or network attached storage (NAS), which is just a filesystem that lives on its own server.\n\nIf you are a solo data scientist reading this – please do not try to run your own data science cluster. When you undertake load balancing, you’ve taken on a distributed systems problem and those are inherently difficult. When done for scaling reasons, it is almost always worthwhile to exhaust the part of vertical scaling where costs grow linearly with compute before undertaking horizontal scaling.\nIf your organization has high availability requirements, it’s worth considering that just adding more nodes may not be sufficient. As the requirements for high availability get steeper, the engineering cost to make sure the service really is that resilient rise exponentially. In addition to considering what to do if a node goes offline, you also have to have backup for the load-balancer and the database/NAS, as well as any other part of the system.\nIn fact, it’s totally possible to make your system less stable by just doing horizontal scaling in one spot without thinking through the implications.\n\n18.2.1 Load-balancing requirements\nLoad-balancers are just a special kind of proxy that routes sessions among the nodes in the cluster. A simple load-balancer just rotates sending traffic to the different nodes using a round-robin configuration.\nAt a minimum, your load-balancer has to know what nodes are accepting traffic. This is accomplished by configuring a health check/heartbeat endpoint for your product. A health check is a feature of an application. The load-balancer periodically pings the health check. If it gets a response, it knows it can send traffic to that node. If no response comes back, it treats that node as unhealthy and doesn’t send traffic there.\nIt is sometimes necessary to do more complicated load-balancing that pays attention to how loaded different nodes are. Additionally, some products feature internal load-balancers, so it really doesn’t matter what your load-balancer does.\nOne other feature that may come up is sticky sessions or sticky cookies. For stateful applications – like Shiny apps – you want to get back to the same node in the cluster so you can resume a previous session. In most load-balancers, this is a simple option you can just turn on.\nThere are a few different ways to configure load balancing for servers. The first is called active/active. This just means that all of the servers are online all of the time. So if I have two RStudio Server instances, they’re both accepting traffic all the time.\nIn active/passive configurations, you have two or more servers, with one set accepting traffing all the time, and the other set remaining inert until or unless the first set goes offline. This is sometimes called a blue/green or red/black configuration.\nPeople often really like this configuration if they have high requirements for uptime, and want to be able to do upgrades to the system behind the scenes and then just cut the traffic over at some point without an interruption in service. It is a nice idea. It is often very hard to pull off.\nFor an application, there are basically two ways it can store data – in a database or in files on the filesystem. Now, this isn’t data you need to access, but it’s needed for the internal workings of the application. For example, it may need to save log information or counts of the number of active users.\nWhen you’re in a single-server configuration, all this can just go somewhere on the server with the application. Very often the database is just a sqlite file that sits in a file on the filesystem.\nBut when you go to to a load-balanced cluster, all of the nodes need symmetric access to read and write. You need an actual database (like postgres) for the application to use. Additionally, anything on the filesystem now needs to move off of an individual server onto a networked system that all the nodes can access.\n\n\n18.2.2 Accommodating different kinds of workloads\nWhen you’re doing horizontal-scaling, people often want to accomodate a variety of workloads. For example, they might want to be able to incorporate several different sizes of jobs that might require a few different sized nodes. Or maybe they want to run a mixture of GPU-backed and non-GPU workloads in the cluster and want to reserve GPU nodes for the jobs that need it.\nIn general, it’s not trivial to set up a single cluster that can support different kinds of workloads, and it’s often easier to set up, for example, a standalone GPU cluster.\nThese days, people are often reaching for Kubernetes for clusters that need to support varies workloads. While it’s true that Kubernetes can theoretically support different kinds of nodes within one cluster, this often isn’t trivial to configure.\nOften, a better option for data science workloads is to use use a high-performance computing (HPC) framework. HPC is particularly appropriate when you need very large machines. In Kubernetes, it is not possible to schedule pods larger than the size of the actual nodes in the cluster. In contrast, most HPC frameworks allow you to combine an arbitrary number of nodes into what acts like a single machine with thousands or tens of thousands of nodes.\nFor example, Slurm is an HPC framework that support multiple queues for different sets of machines. AWS has a service called ParallelCluster that allows users to easily set up a Slurm cluster – and with no additional cost relative to the cost of the underlying AWS hardware.\n\n\n18.2.3 Adding Autoscaling\nSometimes people also undertake horizontal scaling to be able to do autoscaling. The idea here is that the organization could maintain a small amount of “always-on” capacity and scale out other capacity as needed to maintain costs. This is possible – but it requires nontrivial engineering work.\nIn particular, autoscaling a data science workbench down is quite hard. The main reason for this is that many autoscaling routines assume you can easily move someone’s job from one node to another just keeping track of the long-term state. This is a bad assumption for a data science workbench and autoscaling a data science workbench downwards is a difficult challenge.\nLet’s think about a relatively stateless workload. For example, let’s imagine a search engine – every time you put in a search, it spins up a job, does your search, and then spins down.\nIf you come back in a minute or two, it can just spin up another job. It only needs to remember your last query, but that’s a pretty simple bit to state to pass around. If you’re on a different node, no big deal!\nThat’s not the case with a data science workbench. Many autoscaling frameworks these days assume that applications are mostly stateless. In a stateless applications, every interaction is standalone – there’s very little path dependence. The line between statefulness and statelessness are pretty blurry, but working inside a development environment like RStudio or a Jupyter Notebook is about as stateful as it gets. You have long-term state like the files you need and your preferences and short-term state like the recent commands you’ve typed and the packages loaded into your R and Python environment."
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-    "section": "19.3 Docker/Kubernetes in Enterprise",
-    "text": "19.3 Docker/Kubernetes in Enterprise\nOriginally created at Google and released in 2014, Kubernetes is the way to run production services out of Docker containers.3 It is an open source project. If you’re confused by the name, apparently Kubernetes is an ancient Greek word for “helmsman”.\nMany organizations are moving towards using Docker and Kubernetes for their server-based infrastructure. Kubernetes solves all three of the key enterprise IT/Admin challenges with running servers because you manage a single cluster, you can scale rather effortlessly, and app-level administration is extremely simple.\nThe elegance of using Kubernetes is that it completely separates provisioning and configuration challenges. The main unit of analysis in Kubernetes is a pod, which is the term for a Docker container that is running in Kubernetes.\nThe elegance of Kubernetes is that you create a cluster of a certain number of nodes and separately request a certian number of pods with a certain amount of horsepower. Kubernetes takes care of scheduling the pods on the nodes.\nTODO: Graphic of Kubernetes\nThis is amazing, because unlike running services on a regular VM, you just make sure you’ve got enough horsepower in the cluster and then all the app-level requirements go in the container. Then when you declare how many pods you want, you don’t have to worry about what’s going on with each of the nodes in the cluster because it is just running Kubernetes and Docker.\nThis really is extremely powerful – it’s pretty easy to tell Kubernetes, “I want one instance of my load balancer container connected to three instances of my Workbench container with the same storage volume connected to all three.”\nIn practice, unless you’re part of a very sophisticated IT organization, you’ll almost certainly use Kubernetes via one of the cloud providers’ Kubernetes clusters as a service. AWS’s is called Elastic Kubernetes Service (EKS).4\nOne really nice thing about using these Kubernetes clusters as a service is that adding more compute power to your cluster is generally as easy as a few button clicks. On the other hand, that also makes it dangerous from a cost perspective.\nIt is possible to define a Kubernetes cluster “on the fly” and deploy things to a cluster in an ad hoc way. But then you’re back out of IaC world. You can use any standard IaC tooling to stand up a Kubernetes cluster in any of the three major clouds. Once you’ve got the cluster up, Helm is the standard tool for defining what’s running in the cluster.\nThere’s a reason Kubernetes is taking the world by storm – it makes managing complicated enterprise workloads way easier. For example, let’s say you want to stand up a new service in a Kubernetes cluster using IaC. I listed 10 steps above for doing this in a standard server-based configuration. For Kubernetes, there are only three steps:\n\nProvision the cluster itself using IaC or add nodes to an existing cluster (usually trivially easy)\nGet the Docker containers to run in the cluster (often provided by vendors)\nDeclare what container configuration you want in the environment using Helm\n\nOne really nice thing about this is that it’s really clear where the state lies. The applications themselves are installed in the Docker containers and because the containers themselves are ephemeral, state has to be mounted in from somewhere external.\nRelative to more stateful server-based configuration, Kubernetes-based configurations rest a lot more heavily on environment variables, so a lot of configuring application setup is the same as configuring the environment variables in the running container.\nIn the extreme version, some enterprises are going to “we just run a single kubernetes cluster for our entire organzation”. In my opinion, this will someday be a great pattern, but it’s still a little immature. In particular, Kubernetes kinda makes the underlying assumption that all of the resources for the cluster are shared across the cluster. There are ways to use namespaces and other things – but not all Kubernetes resources can be split into namespaces, and managing a Kubernetes cluster for multiple use cases or groups isn’t at all trivial.\nIt’s easy to look at the power of Kubernetes and think it will make everything easy. This is not the case. While the high-level outlines of Kubernetes are super appealing, it is still a complex tool and a data science workbench is a particularly difficult fit for Kubernetes.\nIn many organizations, adopting Kubernetes is synonymous with trying to do autoscaling. As previously discussed, autoscaling a data science workbench is a particularly difficult task – and Kubernetes is particularly friendly to stateless workloads. Autoscaling in Kubernetes with a data science workbench really requires a highly competent Kubernetes admin.\nNetworking in Kubernetes can also be quite complicated. For anything that lives fully in Kubernetes, like your Workbench nodes and load-balancer, it’s quite simple. But getting things into and out of the Kubernetes cluster – like the filesystem you probably need to mount in and accessing databases is a real challenge.\nAll this to say – these are solvable problems for an experienced Kubernetes admin. But they will probably need some guidance around specific requirements for a data science workbench."
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+    "text": "18.3 Docker/Kubernetes in Enterprise\nOriginally created at Google and released in 2014, Kubernetes is the way to run production services out of Docker containers.3 It is an open source project. If you’re confused by the name, apparently Kubernetes is an ancient Greek word for “helmsman”.\nMany organizations are moving towards using Docker and Kubernetes for their server-based infrastructure. Kubernetes solves all three of the key enterprise IT/Admin challenges with running servers because you manage a single cluster, you can scale rather effortlessly, and app-level administration is extremely simple.\nThe elegance of using Kubernetes is that it completely separates provisioning and configuration challenges. The main unit of analysis in Kubernetes is a pod, which is the term for a Docker container that is running in Kubernetes.\nThe elegance of Kubernetes is that you create a cluster of a certain number of nodes and separately request a certian number of pods with a certain amount of horsepower. Kubernetes takes care of scheduling the pods on the nodes.\nTODO: Graphic of Kubernetes\nThis is amazing, because unlike running services on a regular VM, you just make sure you’ve got enough horsepower in the cluster and then all the app-level requirements go in the container. Then when you declare how many pods you want, you don’t have to worry about what’s going on with each of the nodes in the cluster because it is just running Kubernetes and Docker.\nThis really is extremely powerful – it’s pretty easy to tell Kubernetes, “I want one instance of my load balancer container connected to three instances of my Workbench container with the same storage volume connected to all three.”\nIn practice, unless you’re part of a very sophisticated IT organization, you’ll almost certainly use Kubernetes via one of the cloud providers’ Kubernetes clusters as a service. AWS’s is called Elastic Kubernetes Service (EKS).4\nOne really nice thing about using these Kubernetes clusters as a service is that adding more compute power to your cluster is generally as easy as a few button clicks. On the other hand, that also makes it dangerous from a cost perspective.\nIt is possible to define a Kubernetes cluster “on the fly” and deploy things to a cluster in an ad hoc way. But then you’re back out of IaC world. You can use any standard IaC tooling to stand up a Kubernetes cluster in any of the three major clouds. Once you’ve got the cluster up, Helm is the standard tool for defining what’s running in the cluster.\nThere’s a reason Kubernetes is taking the world by storm – it makes managing complicated enterprise workloads way easier. For example, let’s say you want to stand up a new service in a Kubernetes cluster using IaC. I listed 10 steps above for doing this in a standard server-based configuration. For Kubernetes, there are only three steps:\n\nProvision the cluster itself using IaC or add nodes to an existing cluster (usually trivially easy)\nGet the Docker containers to run in the cluster (often provided by vendors)\nDeclare what container configuration you want in the environment using Helm\n\nOne really nice thing about this is that it’s really clear where the state lies. The applications themselves are installed in the Docker containers and because the containers themselves are ephemeral, state has to be mounted in from somewhere external.\nRelative to more stateful server-based configuration, Kubernetes-based configurations rest a lot more heavily on environment variables, so a lot of configuring application setup is the same as configuring the environment variables in the running container.\nIn the extreme version, some enterprises are going to “we just run a single kubernetes cluster for our entire organzation”. In my opinion, this will someday be a great pattern, but it’s still a little immature. In particular, Kubernetes kinda makes the underlying assumption that all of the resources for the cluster are shared across the cluster. There are ways to use namespaces and other things – but not all Kubernetes resources can be split into namespaces, and managing a Kubernetes cluster for multiple use cases or groups isn’t at all trivial.\nIt’s easy to look at the power of Kubernetes and think it will make everything easy. This is not the case. While the high-level outlines of Kubernetes are super appealing, it is still a complex tool and a data science workbench is a particularly difficult fit for Kubernetes.\nIn many organizations, adopting Kubernetes is synonymous with trying to do autoscaling. As previously discussed, autoscaling a data science workbench is a particularly difficult task – and Kubernetes is particularly friendly to stateless workloads. Autoscaling in Kubernetes with a data science workbench really requires a highly competent Kubernetes admin.\nNetworking in Kubernetes can also be quite complicated. For anything that lives fully in Kubernetes, like your Workbench nodes and load-balancer, it’s quite simple. But getting things into and out of the Kubernetes cluster – like the filesystem you probably need to mount in and accessing databases is a real challenge.\nAll this to say – these are solvable problems for an experienced Kubernetes admin. But they will probably need some guidance around specific requirements for a data science workbench."
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-    "text": "19.4 Comprehension Questions\n\nWhat is the difference between horizontal and vertical scaling? For each of the following examples, which one would be more appropriate?\n\nYou’re the only person using your data science workbench and run out of RAM because you’re working with very large data sets in memory.\nYour company doubles the size of the team that will be working in your data science workbench. Each person will be working with reasonably small data, but there’s going to be a lot more of them.\nYou have a big modeling project that’s too large for your existing machine. The modeling you’re doing is highly parallelizable.\n\nWhat is the role of the load balancer in horizontal scaling? When do you really need a load balancer and when can you go without?\nWhat are the biggest strengths of Kubernetes as a scaling tool? What are some drawbacks?"
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+    "section": "18.4 Comprehension Questions",
+    "text": "18.4 Comprehension Questions\n\nWhat is the difference between horizontal and vertical scaling? For each of the following examples, which one would be more appropriate?\n\nYou’re the only person using your data science workbench and run out of RAM because you’re working with very large data sets in memory.\nYour company doubles the size of the team that will be working in your data science workbench. Each person will be working with reasonably small data, but there’s going to be a lot more of them.\nYou have a big modeling project that’s too large for your existing machine. The modeling you’re doing is highly parallelizable.\n\nWhat is the role of the load balancer in horizontal scaling? When do you really need a load balancer and when can you go without?\nWhat are the biggest strengths of Kubernetes as a scaling tool? What are some drawbacks?"
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     "text": "I call it staging because I call the data science environments Dev/Test/Prod. You’ll have to work out language with your IT/Admin group.↩︎\nA low-end estimate of $100,000 fully-loaded cost for one data scientist FTE and 2,000 hours is $50 per hour.↩︎\nIf you are pedantic, there are other tools for deploying Docker containers like Docker Swarm and Kubernetes is not limited to Docker containers. But those are corner cases.↩︎\nIf you aren’t using EKS, Azures AKS, or Google’s GKE, the main other competitor is Oracle’s OpenShift, which some organizations have running in on-prem Kubernetes clusters.↩︎"
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     "title": "Appendix B — Lab Map",
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-    "text": "This section aims to clarify the relationship between the assets you’ll make in each portfolio exercise and labs in this book.\n\n\n\n\n\n\n\nChapter\nLab Activity\n\n\n\n\nChapter 1: Environments as Code\nCreate a Quarto side that uses {renv} and {venv} to create standalone R and Python virtual environments, create a page on the website for each.\n\n\nChapter 3: Data Architecture\nMove data into a DuckDB database.\n\n\nChapter 2: Project Architecture\nCreate an API that serves a Python machine-learning model using {vetiver} and {fastAPI}. Call that API from a Shiny App in both R and Python.\n\n\nChapter 4: Logging and Monitoring\nAdd logging to the app from Chapter 2.\n\n\nChapter 5: Code Promotion\nPut a static Quarto site up on GitHub Pages using GitHub Actions that renders the project.\n\n\nChapter 9: Docker\nPut API from Chapter 2 into Docker container.\n\n\nChapter 10: Cloud\nStand up an EC2 instance. Put model into S3.\n\n\nChapter 11: Linux Admin\nAdd R, Python, RStudio Server, JupyterHub, palmer penguin fastAPI + App.\n\n\nChapter 12: Networking\nAdd proxy (nginx) to reach all services from the web.\n\n\nChapter 13: DNS\nAdd a real URL to the EC2 instance. Put the Shiny app into an iFrame on the site.\n\n\nChapter 14: SSL\nAdd SSL/HTTPS to the EC2 instance.\n\n\nChapter 15: Servers\nResize servers."
+    "text": "This section aims to clarify the relationship between the assets you’ll make in each portfolio exercise and labs in this book.\n\n\n\n\n\n\n\nChapter\nLab Activity\n\n\n\n\nChapter 1: Environments as Code\nCreate a Quarto side that uses {renv} and {venv} to create standalone R and Python virtual environments, create a page on the website for each.\n\n\nChapter 3: Data Architecture\nMove data into a DuckDB database.\n\n\nChapter 2: Project Architecture\nCreate an API that serves a Python machine-learning model using {vetiver} and {fastAPI}. Call that API from a Shiny App in both R and Python.\n\n\nChapter 4: Logging and Monitoring\nAdd logging to the app from Chapter 2.\n\n\nChapter 5: Code Promotion\nPut a static Quarto site up on GitHub Pages using GitHub Actions that renders the project.\n\n\nChapter 6: Docker\nPut API from Chapter 2 into Docker container.\n\n\nChapter 7: Servers\nStand up an EC2 instance. Put model from [Chapter @sec-proj-arch] into an S3 bucket.\n\n\nChapter 8: Command Line\nLog into your server with a .pem key and create an SSH key.\n\n\nChapter 9: Linux Admin\nCreate a user on the server and add the SSH key from Chapter 8.\n\n\nChapter 10: App Admin\nAdd R, Python, RStudio Server, JupyterHub, palmer penguin fastAPI + App to the server.\n\n\nChapter 11: Servers\nResize servers.\n\n\nChapter 12: Networking\nSet up a proxy (NGINX) to reach all services from the web.\n\n\nChapter 13: DNS\nAdd a real URL to the EC2 instance. Put the Shiny app into an iFrame on the Quarto site.\n\n\nChapter 14: SSL\nAdd SSL/HTTPS to the EC2 instance."
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+    "title": "Appendix C — Cheatsheets",
+    "section": "C.1 Docker",
+    "text": "C.1 Docker\n\nC.1.1 Docker CLI Commands\n\n\n\n\n\n\n\n\n\nStage\nCommand\nWhat it does\nNotes and helpful options\n\n\n\n\nBuild\ndocker build &lt;directory&gt;\nBuilds a directory containing a Dockerfile into an image.\n-t &lt;name:tag&gt; provide a name to the container. tag is optional, defaults to latest.\n\n\nMove\ndocker push &lt;image&gt;\nPush a container to a registry.\n\n\n\nMove\ndocker pull &lt;image&gt;\nPull a container from a registry.\nRarely used because run pulls the container if needed.\n\n\nRun\ndocker run &lt;image&gt;\nRun a container.\nSee flags in next table.\n\n\nRun\ndocker stop &lt;container&gt;\nStop a running container.\ndocker kill can be used if stop fails.\n\n\nRun\ndocker ps\nList containers.\nUseful to get running container id to do things to it.\n\n\nRun\ndocker exec &lt;container&gt; &lt;command&gt;\nRun a command inside a running container.\nBasically always used to open a shell in a container with docker exec -it &lt;container&gt; /bin/bash\n\n\nRun\ndocker logs &lt;container&gt;\nViews logs for a container.\n\n\n\n\n\n\nC.1.2 Flags for docker run\n\nReminder: Order for -p and -v is &lt;host&gt;:&lt;container&gt;\n\n\n\n\n\n\n\nFlag\nEffect\nNotes\n\n\n\n\n--name &lt;name&gt;\nGive a name to the running container.\nOptional. Will be auto-assigned if not provided.\n\n\n--rm\nRemove container when its stopped.\nDon’t use in production. You probably want to inspect failed containers.\n\n\n-d\nDetach container (don’t block the terminal).\nAlmost always used in production.\n\n\n-p &lt;port&gt;:&lt;port&gt;\nPublish port from inside container to outside.\nNeeded if you want to access an app or API running inside the container.\n\n\n-v &lt;dir&gt;:&lt;dir&gt;\nMount volume into the container.\n\n\n\n\n\n\nC.1.3 Dockerfile Commands\nThese are the commands that go in a Dockerfile when you’re building it.\n\n\n\n\n\n\n\n\nCommand\nPurpose\nExample\n\n\n\n\nFROM\nIndicate base container.\nFROM rocker/r-ver:4.1.0\n\n\nRUN\nRun a command when building.\nRUN apt-get update\n\n\nCOPY\nCopy from build directory into the container.\nCOPY . /app/\n\n\nCMD\nSpecify the command to run when the container starts.\nCMD quarto render ."
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+    "title": "Appendix C — Cheatsheets",
+    "section": "C.2 Cloud Services",
+    "text": "C.2 Cloud Services\n\n\n\n\n\n\n\n\n\nService\nAWS\nAzure\nGCP\n\n\n\n\nKubernetes cluster\nEKS (Elastic Kubernetes Service) or Fargate\nAKS (Azure Kubernetes Service)\nGKE (Google Kubernetes Engine)\n\n\nRun a container /application\nECS (Elastic Container Service) or Elastic Beanstalk\nAzure Container Apps\nGoogle App Engine\n\n\nRun an API\nLambda\nAzure Functions\nGoogle Cloud Functions\n\n\nDatabase\nRDS or Reds hift[^2-1-cloud-8]\nAzure Database\nGoogle Cloud SQL\n\n\nML Platform\nSageMaker\nAzure ML\nVertex AI"
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+    "title": "Appendix C — Cheatsheets",
+    "section": "C.3 Command Line",
+    "text": "C.3 Command Line\n\nC.3.1 General Command Line\n\n\n\nSymbol\nWhat it is\n\n\n\n\nman &lt;command&gt;\nOpen manual for command\n\n\nq\nQuit the current screen\n\n\n\\\nContinue bash command on new line\n\n\nctrl + c\nQuit current execution\n\n\n\n\n\nC.3.2 Linux Navigation\n\n\n\n\n\n\n\n\nCommand\nWhat it does/is\nNotes + Helpful options\n\n\n\n\n/\nSystem root or file path separator\n\n\n\n.\ncurrent working directory\n\n\n\n..\nParent of working directory\n\n\n\n~\nHome directory of the current user\n\n\n\nls &lt;dir&gt;\nList objects in a directory\n-l - format as list\n-a - all (include hidden files that start with .)\n\n\npwd\nPrint working directory\n\n\n\ncd &lt;dir&gt;\nChange directory\nCan use relative or absolute paths\n\n\n\n\n\nC.3.3 Reading Text Files\n\n\n\n\n\n\n\n\nCommand\nWhat it does\nNotes + Helpful options\n\n\n\n\ncat &lt;file&gt;\nPrint a file from the top.\n\n\n\nless &lt;file&gt;\nPrint a file, but just a little.\nCan be very helpful to look at a few rows of csv.\nLazily reads lines, so can be much faster than cat for big files.\n\n\nhead &lt;file&gt;\nLook at the beginning of a file.\nDefaults to 10 lines, can specify a different number with -n &lt;n&gt;.\n\n\ntail &lt;file&gt;\nLook at the end of a file.\nUseful for logs where the newest part is last.\nThe -f flag is useful to follow for a live view.\n\n\ng r    e p &lt;expression&gt;\nSearch a file using regex.\nWriting regex can be a pain. I suggest testing expressions on regex101.com.\nOften useful in combination with the pipe.\n\n\n|\nThe pipe\n\n\n\n\n\n\nC.3.4 Manipulating Files\n\n\n\n\n\n\n\n\nCommand\nWhat it does/is\nNotes + Helpful Options\n\n\n\n\nrm &lt;path&gt;\nRemove\n-r - recursively remove everything below a file path\n-f - force - don’t ask for each file\nBe very careful, it’s permanent\n\n\nc  p &lt;from&gt; &lt;to&gt;\nCopy\n\n\n\nm  v &lt;from&gt; &lt;to&gt;\nMove\n\n\n\n*\nWildcard\n\n\n\nmkdir/rmdir\nMake/remove directory\n-p - create any parts of path that don’t exist\n\n\n\n\n\nC.3.5 Move things to/from server\n\n\n\n\n\n\n\n\nCommand\nWhat it does\nNotes + Helpful options\n\n\n\n\ntar\nCreate/extract archive file\nAlmost always used with flags.\nCreate is usually\ntar -czf &lt; a  r c hive name&gt; &lt;file(s)&gt;\nExtract is usually\nt  a r  -xfv &lt;archive name&gt;\n\n\nscp\nSecure copy via ssh\nRun on laptop to server\nCan use most ssh flags (like -i and -v)\n\n\n\n\n\nC.3.6 Write files from the command line\n\n\n\n\n\n\n\n\nCommand\nWhat it does\nNotes\n\n\n\n\ntouch\nCreates file if doesn’t already exist.\nUpdates last updated to current time if it does exist.\n\n\n&gt;\nOverwrite file contents\nCreates a new file if it doesn’t exist\n\n\n&gt;&gt;\nConcatenate to end of file\nCreates a new file if it doesn’t exist\n\n\n\n\n\nC.3.7 Command Line Text Editors (Vim + Nano)\n\n\n\n\n\n\n\n\nCommand\nWhat it does\nNotes + Helpful options\n\n\n\n\n^\nPrefix for file command in nano editor.\nIts the ⌘ or Ctrl key, not the caret symbol.\n\n\ni\nEnter insert mode (able to type) in vim\n\n\n\nescape\nEnter normal mode (navigation) in vim.\n\n\n\n:w\nWrite the current file in vim (from normal mode)\nCan be combined to save and quit in one, :wq\n\n\n:q\nQuit vim (from normal mode)\n:q! quit without saving"
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+    "title": "Appendix C — Cheatsheets",
+    "section": "C.4 Cheatsheet: Users and Permissions",
+    "text": "C.4 Cheatsheet: Users and Permissions\n\nC.4.1 Users\n\n\n\n\n\n\n\nCommand\nWhat it does\n\n\n\n\nsu &lt;username&gt;\nChange to be a different user.\n\n\nwhoami\nGet username of current user.\n\n\nid\nGet full user + group info on current user.\n\n\npasswd\nChange password.\n\n\nuseradd\nAdd a new user.\n\n\nu sermod &lt;username&gt;\nModify user username. -aG &lt;group&gt; adds to a group\n\n\n\n\n\nC.4.2 Permissions\n\n\n\n\n\n\n\n\nCommand\nWhat it does\nHelpful options + notes\n\n\n\n\nchm o d &lt;permissi ons&gt; &lt;file&gt;\nModifies permissions on a file.\nNumber indicates permissions for user, group, others: add 4 for read, 2 for write, 1 for execute, 0 for nothing.\n\n\ncho w n  &lt;user/gr oup&gt; &lt;file&gt;\nChange the owner of a file.\nCan be used for user or group, e.g. :my-group.\n\n\nsu  &lt;username&gt;\nChange active user to username.\n\n\n\nsud o &lt;command&gt;\nAdopt super user permissions for the following command."
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+    "title": "Appendix C — Cheatsheets",
+    "section": "C.5 Cheatsheet: ssh",
+    "text": "C.5 Cheatsheet: ssh\nssh &lt;user&gt;@&lt;host&gt;\n\n\n\n\n\n\n\n\nFlag\nWhat it does\nNotes\n\n\n\n\n-v\nVerbose, good for debugging.\nAdd more vs as you please, -vv or -vvv.\n\n\n-i\nChoose identity file (private key)\nNot necessary with default key names."
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+    "title": "Appendix C — Cheatsheets",
+    "section": "C.6 Cheatsheet: Linux Admin Commands",
+    "text": "C.6 Cheatsheet: Linux Admin Commands\n\nC.6.1 Users\n\n\n\n\n\n\n\nCommand\nWhat it does\n\n\n\n\nsu &lt;username&gt;\nChange to be a different user.\n\n\nwhoami\nGet username of current user.\n\n\nid\nGet full user + group info on current user.\n\n\npasswd\nChange password.\n\n\nuseradd\nAdd a new user.\n\n\nuse   r m od &lt;username&gt;\nModify user username. -aG &lt;group&gt; adds to a group\n\n\n\n\n\nC.6.2 Permissions\n\n\n\n\n\n\n\n\nCommand\nWhat it does\nHelpful options + notes\n\n\n\n\nch m od &lt;per m i s s ions&gt; &lt;file&gt;\nModifies permissions on a file.\nNumber indicates permissions for user, group, others: add 4 for read, 2 for write, 1 for execute, 0 for nothing.\n\n\nc h ow n  &lt;us e r / g roup&gt; &lt;file&gt;\nChange the owner of a file.\nCan be used for user or group, e.g. :my-group.\n\n\ns u &lt;username&gt;\nChange active user to username.\n\n\n\ns u do &lt;command&gt;\nAdopt super user permissions for the following command.\n\n\n\n\n\n\nC.6.3 Install applications (Ubuntu)\n\n\n\n\n\n\n\nCommand\nWhat it does\n\n\napt-get u p d a t e && apt-get upgrade -y\nFetch and install upgrades to system packages\n\n\na p t-get install &lt;package&gt;\nInstall a system package.\n\n\nwget\nDownload a file from a URL.\n\n\ngdebi\nInstall local .deb file.\n\n\n\n\n\nC.6.4 Storage\n\n\n\n\n\n\n\n\nCommand\nWhat it does\nHelpful options\n\n\n\n\ndf\nCheck storage space on device.\n-h for human readable file sizes.\n\n\ndu\nCheck size of files.\nMost likely to be used as d  u - h &lt;dir&gt; | sort -h\nAlso useful to combine with head.\n\n\n\n\n\nC.6.5 Processes\n\n\n\n\n\n\n\n\nCommand\nWhat it does\nHelpful options\n\n\n\n\ntop\nSee what’s running on the system.\n\n\n\nps aux\nSee all system processes.\nConsider using --sort and pipe into head or grep\n\n\nkill\nKill a system process.\n-9 to force kill immediately\n\n\n\n\n\nC.6.6 Networking\n\n\n\n\n\n\n\n\nCommand\nWhat it does\nHelpful options\n\n\n\n\nnetstat\nSee ports and services using them.\nUsually used with -tlp, for tcp listening applications, including pid\n\n\nssh - L  &lt;port&gt;:&lt;ip&gt;: &lt;port&gt; &lt;host&gt;\nPort forwards a remote port on host to local.\nChoose local port to match remote port. Remote ip is usually localhost.\n\n\n\n\n\nC.6.7 The path\n\n\n\n\n\n\n\nCommand\nWhat it does\n\n\n\n\nwhich &lt;command&gt;\nFinds the location of the binary that runs when you run command.\n\n\n\n`ln -s &lt; lo cation to link&gt;\n\n&lt; l ocation of symlink&gt;`\n\n\nCreates a symlink from file at location to link to location of symlink."
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+    "href": "chapters/append/cheatsheets.html#cheat-ports",
+    "title": "Appendix C — Cheatsheets",
+    "section": "C.7 Cheatsheet: IP Addresses and Ports",
+    "text": "C.7 Cheatsheet: IP Addresses and Ports\n\nC.7.1 Special IP Addresses\n\n\n\n\n\n\n\nCode\nMeaning\n\n\n\n\n127.0.0.1\nlocalhost or loopback – the machine that originated the request\n\n\n192.168.x.x\n172.16.x.x.x\n10.x.x.x\nProtected address blocks used for private IP addresses.\n\n\n\n\n\nC.7.2 Special Ports\nAll ports below 1024 are reserved for server tasks and cannot be assigned to admin-controlled services.\n\n\n\nProtocol/Application\nDefault Port\n\n\n\n\nHTTP\n80\n\n\nHTTPS\n443\n\n\nSSH\n22\n\n\nPostgreSQL\n5432\n\n\nRStudio Server\n\n\n\nShiny Server\n\n\n\nJupyterHub"
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+  {
+    "objectID": "chapters/append/cheatsheets.html#cheatsheet-debugging-tips",
+    "href": "chapters/append/cheatsheets.html#cheatsheet-debugging-tips",
+    "title": "Appendix C — Cheatsheets",
+    "section": "C.8 Cheatsheet: Debugging Tips",
+    "text": "C.8 Cheatsheet: Debugging Tips\nIf things are going poorly on your server, here are some steps you might take to try to troubleshoot.\n\nC.8.1 Check storage usage\nA common culprit for weird server behavior is running out of storage space. There are two handy commands for monitoring the amount of storage you’ve got – du and df. These commands are almost always used with the -h flag to put file sizes in human-readable formats.\ndf, for disk free, shows the capacity left on the device where the directory sits.\nFor example, here’s the result of running the df command on the chapters directory on my laptop that includes this chapter.\n ❯ df -h chapters                                                    \nFilesystem     Size   Used  Avail Capacity iused      ifree %iused  Mounted on\n/dev/disk3s5  926Gi  163Gi  750Gi    18% 1205880 7863468480    0%   /System/Volumes/Data\nSo you can see that the chapters folder lives on a disk called /dev/disk3s5 that’s a little less than 1Tb and is 18% full – no problem. On a server this can be really useful to know, because it’s quite easy to switch a disk out for a bigger one in the same spot.\nIf you’ve figured out that a disk is full and need to figure out where the culprits are, the du can be useful. du, short for disk usage, gives you the size of individual files inside a directory. It’s particularly useful in combination with the sort command.\nFor example, here’s the result of running du on the chapters directory where the text files for this book live.\n ❯ du -h chapters | sort -h                                      \n 44K    chapters/sec2/images-servers\n124K    chapters/sec3/images-scaling\n156K    chapters/sec2/images\n428K    chapters/sec2/images-traffic\n656K    chapters/sec1/images-code-promotion\n664K    chapters/sec1/images-docker\n1.9M    chapters/sec1/images-repro\n3.4M    chapters/sec1\n3.9M    chapters/sec3/images-auth\n4.1M    chapters/sec3\n4.5M    chapters/sec2/images-networking\n5.3M    chapters/sec2\n 13M    chapters\nSo if I were thinking about cleaning up this directory, I could see that my images-networking directory in sec2 is the biggest single bottom-level directory. If you find yourself needing to find big files on your Linux server, it’s worth spending some time with the help pages for du. There are lots of really useful options.\ndu is useful for identifying large files and directories on a server.\n\n\nC.8.2 Look at what’s running\nA running program is a process. For example, when you type python on the command line to open a REPL, that starts a single Python process. If you were to start a second terminal session and run python again, you’d have a second Python process.\nComplicated programs often involves multiple than one process. For example, running the RStudio IDE involves (at minimum) one process for the IDE itself and one for the R session that it uses in the background. The relationships between these different processes is mostly hidden from you – the end user.\nAs a server admin, finding runaway processes, killing them, and figuring out how to prevent the them from happening again is a pretty common task. Runaway processes usually misbehave by using up the entire CPU or filling up the entire machine’s RAM.\nLike users and groups have ids, each process has a numeric process id (pid). Each process also has an owner – this can be either a service account or a real user. If you’ve got a rogue process, the pattern is to try to find the process and make note of its pid. Then you can immediately end the process by pid with the kill command.\nSo, how do you find a troublesome process?\nThe top command is a good first stop. top shows the top CPU-consuming processes in real time. Here’s the top output from my machine as I write this sentence.\nPID    COMMAND      %CPU TIME     #TH    #WQ  #PORT MEM    PURG   CMPRS PGRP\n0      kernel_task  16.1 03:56:53 530/10 0    0     2272K  0B     0B    0\n16329  WindowServer 16.0 01:53:20 23     6    3717  941M-  16M+   124M  16329\n24484  iTerm2       11.3 00:38.20 5      2    266-  71M-   128K   18M-  24484\n29519  top          9.7  00:04.30 1/1    0    36    9729K  0B     0B    29519\n16795  Magnet       3.1  00:39.16 3      1    206   82M    0B     39M   16795\n16934  Arc          1.8  18:18.49 45     6    938   310M   144K   61M   16934\n16456  Messages     1.7  06:58.27 4      1    603   138M   2752K  63M   16456\n1      launchd      1.7  13:41.03 4/1    3/1  3394+ 29M    0B     6080K 1\n573    diagnosticd  1.4  04:31.97 3      2    49    2417K  0B     816K  573\n16459  zoom.us      1.3  66:38.37 30     3    2148  214M   384K   125M  16459\n16575  UniversalCon 1.3  01:15.89 2      1    131   12M    0B     2704K 16575\nIn most instances, the first three columns are the most useful. You’ve got the name of the process (COMMAND) and how much CPU its using. Right now, nothing is using very much CPU. If I were to find something concerning – perhaps an R process that is using 500% of CPU – I would want to take notice of its pid to kill it with kill.\n\n\n\n\n\n\nSo much CPU?\n\n\n\nFor top (and most other commands), CPU is expressed as a percent of single core availability. So, on a modern machine with multiple cores, it’s very common to see CPU totals well over 100%. Seeing a single process using over 100% of CPU is rarer.\n\n\nThe top command takes over your whole terminal. You can exit with Ctrl + c.\nAnother useful command for finding runaway processes is ps aux. It lists a snapshot of all processes running on the system, along with how much CPU and RAM they’re using. You can sort the output with the --sort flag and specify sorting by cpu with --sort -%cpu or by memory with --sort -%mem.\nBecause ps aux returns every running process on the system, you’ll probably want to pipe the output into head.\nAnother useful way to use ps aux is in combination with grep. If you pretty much know what the problem is – often this might be a runaway R or Python process – ps aux | grep &lt;name&gt; can be super useful to get the pid.\nFor example, here are the RStudio processes currently running on my system.1\n &gt; ps aux | grep \"RStudio\"                                                                                      [10:21:18]\nUSER               PID  %CPU %MEM      VSZ    RSS   TT  STAT STARTED      TIME COMMAND\nalexkgold        23583   0.9  1.7 37513368 564880   ??  S    Sat09AM  17:15.27 /Applications/RStudio.app/Contents/MacOS/RStudio\nalexkgold        23605   0.5  0.4 36134976 150828   ??  S    Sat09AM   1:58.16 /Applications/RStudio.app/Contents/MacOS/rsession --config-file none --program-mode desktop \n\n\nC.8.3 Make sure the right ports are open\nNetworking is a complicated topic, which we’ll approach with great detail in Chapter 12. Most often, you’ll want to check that the application you’re running is actually accessible to the outside world, assuming you want it to be.\nThe main command to help you see what ports are being used and by what services is the netstat command. netstat returns the services that are running and their associated ports. netstat is generally most useful with the -tlp flags to show programs that are listening and the programs associated.\nSometimes you know you’ve got a service running on your machine, but you just can’t seem to get the networking working. It can be useful to access the service directly without having to deal with networking.\nSSH port forwarding allows you to take the output of a port on a remote server, route it through SSH, and display it as if it were on a local port. For example, let’s say you’ve got RStudio Server running on my server but the web interface isn’t working. If you’ve got SSH working properly, you can double check that the service is working and the issue really is networking.\nI find that the syntax for port forwarding completely defies my memory and I have to google it every time I use it. For the kind of port forwarding you’ll use most often in debugging, you’ll use the -L flag to get a remote port locally.\nssh -L &lt;local port&gt;:&lt;remote ip&gt;:&lt;remote port&gt; &lt;ssh hostname&gt;\nThe local would be your laptop and the remote your server, so if you had RStudio Server running on a server on port 3939. Then you could run ssh -L 3939:localhost:3939 my-user@my-ds-workbench.com. To get whatever is at port 3939 on the server (hopefully RStudio Workbench!) by going to localhost:3939 in the laptop’s browser.\nMost often, you’ll use the same port locally and on the remote and the remote ip will be localhost.\n\n\nC.8.4 Check your path\nLet’s say you want to open Python on your command line. One option would be to type the complete path to a Python install every time. For example, I’ve got a version of Python in /usr/bin, so /usr/bin/python3 works.\nBut in most cases, it’s nice to just type python3 and have the right version open up.\n$ python3\nPython 3.9.6 (default, May  7 2023, 23:32:45) \n[Clang 14.0.3 (clang-1403.0.22.14.1)] on darwin\nType \"help\", \"copyright\", \"credits\" or \"license\" for more information.\n&gt;&gt;&gt; \nIn some cases, this isn’t optional. Certain applications will rely on others being available, like RStudio needing to find R. Or Jupyter Notebook finding your Python kernels.\nSo how does the operating system know where to find those applications and files?\nIf you ever want to check which actual executable is being used by a command, you can use the which command. For example, on my system this is the result of which python3.\n ❯ which python3                                                    \n/usr/bin/python3\nThe operating system knows how to find the actual runnable programs on your system via the path. The path is a set of directories that the system knows to search when it tries to run a path. The path is stored in an environment variable conveniently named PATH.\nYou can check your path at any time by echoing the PATH environment variable with echo $PATH. On my MacBook, this is what the path looks like.\n ❯ echo $PATH                                                      \n/opt/homebrew/bin:/opt/homebrew/sbin:/usr/local/bin:/System/Cryptexes/App/usr/bin:/usr/bin:/bin:/usr/sbin:/sbin\nWhen you install a new piece of software you’ll need to add it two the path. Say I was to install a new version of Python in /opt/python. That’s not on my PATH, so my system wouldn’t be able to find it.\nI can get it on the path in one of two ways – the first option would be to add /opt/python to my PATH every time a terminal session starts usually via a file in /etc or the .zshrc. The other option is to create a symlink to the new application in a directory already on the PATH. A symlink does what it sounds like – creates a way to link to a file from a different directory without moving it.\nSymlinks are created with the ln command."
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+    "href": "chapters/append/cheatsheets.html#comprehension-questions",
+    "title": "Appendix C — Cheatsheets",
+    "section": "C.9 Comprehension Questions",
+    "text": "C.9 Comprehension Questions\n\nHow would you do the following?\n\nFind and kill the process IDs for all running rstudio-server processes.\nFigure out which port JupyterHub is running on.\nCreate a file called secrets.txt, open it with vim, write something in, close and save it, and make it so that only you can read it."
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+    "text": "This command actually cuts off the header line of the table. What I actually ran was ps aux | grep \"RStudio\\|USER\".↩︎"
   }
 ]
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