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diff --git a/chapters/sec3/3-3-ent-scale.html b/chapters/sec3/3-3-ent-scale.html
@@ -356,9 +356,10 @@ <h1 class="title"><span id="sec-ent-scale" class="quarto-section-identifier"><sp
 
 </header>
 
-<p>Managing compute is no mean feat at enterprise scales. Patterns that might work at smaller scales start to break down when the environment needs to support 100 or 500 or even 1,000 data scientists working on the same platform.</p>
-<p>Supporting that many users involves much more complexity and expense because you absolutely have to have multiple – perhaps many – servers. With so many users, you’re probably supporting a variety of different types of work, which adds complexity. Additionally, downtime becomes very expensive, so the stability of the system becomes paramount and overall expense can be quite high.</p>
-<p>This chapter will help you understand how enterprise IT/Admins think about managing a lot of servers and how to communicate with them about your needs as a data scientist.</p>
+<p>There are two reasons to scale a data science cluster. The first is that you’re doing basically laptop-sized jobs but a lot of them. The second is that you’ve got jobs that exceed the capacity of an individual laptop.</p>
+<p>In an enterprise context, it’s very plausible that your IT/Admin team is confronting both of these problems. A platform that needs to support 100 or 500 or even 1,000 data scientists has scale issues because of the sheer number of users, and also probably has to support a bunch of different use cases.</p>
+<p>Providing that platform to users involves a lot of complexity and expense because the IT/Admin group is managing multiple – perhaps many – servers. And as the number of users and importance of a data science platform rises, downtime becomes very expensive, so the stability of the system becomes paramount.</p>
+<p>This chapter will help you understand how enterprise IT/Admins think about managing and scaling that many servers to create a stable platform. It will also help you figure out what you need to communicate to your organization’s IT/Admins about the scale of your work.</p>
 <section id="devops-best-practices" class="level2" data-number="17.1">
 <h2 data-number="17.1" class="anchored" data-anchor-id="devops-best-practices"><span class="header-section-number">17.1</span> DevOps best practices</h2>
 <p>In an enterprise, the IT/Admin group is managing dozens or hundreds or thousands of servers. In order to keep that many servers manageable, the IT/Admin group tries to keep those servers very standardized and interchangeable. This idea is often encompassed in the adage that “servers should be cattle, not pets”. That means that you almost certainty won’t be allowed to SSH in and just make changes that you might want as a data scientist.</p>

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