Getting started ↑

SirModred relies on ElasticSearch, Kibiter and MySQL/MariaDB. The current versions used are:

ElasticSearch 6.8.6
Kibiter 6.8.6
MySQL/MariaDB (5.7.24/10.0)

There are mainly 2 options to get started with SirMordred:

Source code and docker: In this method, the applications (ElasticSearch, Kibiter and MariaDB) are installed using docker and the GrimoireLab Components are installed using the source code.
SirMordred and docker: In this method, the applications (ElasticSearch, Kibiter and MariaDB) are installed using docker and only SirMordred is installed including all the GrimoireLab Components.
Only docker: In this method, the applications (ElasticSearch, Kibiter and MariaDB) and the GrimoireLab Components are installed using docker.

Source code and docker ↑

Getting the containers ↑

You will have to install ElasticSearch (6.8.6), Kibiter (6.8.6) and a MySQL/MariaDB database (5.7.24/10.0). You can use the following docker-compose to have them running.

Help: You need to install docker and docker-compose for this. Please refer to the documentation.

https://docs.docker.com/install/linux/docker-ce/ubuntu/

https://docs.docker.com/compose/install/

Note:

You can omit (comment/remove) the mariadb section in case you have MariaDB or MySQL already installed in your system.

It is not mandatory to use docker to install ElasticSearch, Kibiter and MySQL/MariaDB database. They can be installed by other means too (source code). We are not much concerned about the method they are installed. Docker is the easiest way as it mostly avoids the errors caused by them.

docker-compose (with SearchGuard) ↑

Note: For accessing Kibiter and/or creating indexes login is required, the username:password is admin:admin.

services:
    mariadb:
      restart: on-failure:5
      image: mariadb:10.0
      expose:
        - "3306"
      ports:
        - "3306:3306"
      environment:
        - MYSQL_ROOT_PASSWORD=
        - MYSQL_ALLOW_EMPTY_PASSWORD=yes
        - MYSQL_DATABASE=test_sh
      command: --wait_timeout=2592000 --interactive_timeout=2592000 --max_connections=300
        
    elasticsearch:
      image: bitergia/elasticsearch:6.8.6-secured
      command: elasticsearch -Enetwork.bind_host=0.0.0.0 -Ehttp.max_content_length=2000mb
      ports:
        - 9200:9200
      environment:
        - ES_JAVA_OPTS=-Xms2g -Xmx2g

    kibiter:
      restart: on-failure:5
      image: bitergia/kibiter:secured-v6.8.6-3
      environment:
        - PROJECT_NAME=Demo
        - NODE_OPTIONS=--max-old-space-size=1000
        - ELASTICSEARCH_USER=kibanaserver
        - ELASTICSEARCH_PASSWORD=kibanaserver
        - ELASTICSEARCH_URL=["https://elasticsearch:9200"]
        - LOGIN_SUBTITLE=If you have forgotten your username or password ...
      links:
        - elasticsearch
      ports:
        - 5601:5601

docker-compose (without SearchGuard) ↑

Note: Here, access to kibiter and elasticsearch doesn't need credentials.

version: '2.2'

services:
    elasticsearch:
      image: docker.elastic.co/elasticsearch/elasticsearch-oss:6.8.6
      command: elasticsearch -Enetwork.bind_host=0.0.0.0 -Ehttp.max_content_length=2000mb
      ports:
        - 9200:9200
      environment:
        - ES_JAVA_OPTS=-Xms2g -Xmx2g
        - ANONYMOUS_USER=true

    kibiter:
      restart: on-failure:5
      image: bitergia/kibiter:community-v6.8.6-3
      environment:
        - PROJECT_NAME=Demo
        - NODE_OPTIONS=--max-old-space-size=1000
        - ELASTICSEARCH_URL=http://elasticsearch:9200
      links:
        - elasticsearch
      ports:
        - 5601:5601

    mariadb:
      restart: on-failure:5
      image: mariadb:10.0
      expose:
        - "3306"
      ports:
        - "3306:3306"
      environment:
        - MYSQL_ROOT_PASSWORD=
        - MYSQL_ALLOW_EMPTY_PASSWORD=yes
        - MYSQL_DATABASE=test_sh
      command: --wait_timeout=2592000 --interactive_timeout=2592000 --max_connections=300

Save the above into a docker-compose.yml file and run

$ docker-compose up -d

to get ElasticSearch, Kibiter and MariaDB running on your system.

Cloning the repositories ↑

In the next step, you will need to fork all the GitHub repos below and clone them to a target local folder (e.g., sources).

SirModred
ELK
Graal
Perceval
Perceval for Mozilla
Perceval for OPNFV
Perceval for Puppet
SortingHat
Sigils
Kidash
Toolkit
Cereslib
Manuscripts

Each local repo should have two remotes: origin points to the forked repo, while upstream points to the original CHAOSS repo.

An example is provided below.

$ git remote -v
origin	https://github.com/valeriocos/perceval (fetch)
origin	https://github.com/valeriocos/perceval (push)
upstream	https://github.com/chaoss/grimoirelab-perceval (fetch)
upstream	https://github.com/chaoss/grimoirelab-perceval (push)

In order to add a remote to a Git repository, you can use the following command:

$ git remote add upstream https://github.com/chaoss/grimoirelab-perceval

ProTip ↑

You can use this use this script to automate this whole process.

$ python3 glab-dev-env-setup.py --create --token xxxx --source sources

Setting up PyCharm ↑

Help: You need to install PyCharm (Community Edition) for this. Please refer to the documentation.

https://www.jetbrains.com/help/pycharm/installation-guide.html

You can follow this tutorial to get familiar with PyCharm.

Once PyCharm is installed create a project in the grimoirelab-sirmordred directory. PyCharm will automatically create a virtual env, where you should install the dependencies listed in each requirements.txt, excluding the ones concerning the grimoirelab components.

To install the dependencies, you can click on File -> Settings -> Project -> Project Interpreter, and then the + located on the top right corner (see figure below).

Later, you can add the dependencies to the grimoirelab components via File -> Settings -> Project -> Project Structure. The final results should be something similar to the image below.

Execution ↑

Now that you have the ElasticSearch, Kibiter and MariaDB running on your system and the project configured in the PyCharm, we can execute micro-mordred/sirmordred.

To execute micro-mordred, define a setup.cfg and projects.json, and run the following commands, which will collect and enrich the data coming from the git sections and upload the corresponding panels to Kibiter:

micro.py --raw --enrich --cfg ./setup.cfg --backends git cocom
micro.py --panels --cfg ./setup.cfg

Optionally, you can create a configuration in PyCharm to speed up the executions (Run -> Edit configuration -> +).

The final results should be something similar to the image below.

SirMordred and docker ↑

Follow the instructions in Getting the containers to install ElasticSearch (6.8.6), Kibiter (6.8.6) and a MySQL/MariaDB database (5.7.24/10.0).

There are several ways to install SirMordred on your system: packages or source code using Poetry or pip.

PyPI

SirMordred can be installed using pip, a tool for installing Python packages. To do it, run the next command:

$ pip install sirmordred

Source code

To install from the source code you will need to clone the repository first:

$ git clone https://github.com/chaoss/grimoirelab-sirmordred
$ cd grimoirelab-sirmordred

Then use pip or Poetry to install the package along with its dependencies.

Pip

To install the package from local directory run the following command:
```
$ pip install .
```
In case you are a developer, you should install SirMordred in editable mode:
```
$ pip install -e .
```
Poetry

We use poetry for dependency management and packaging. You can install it following its documentation. Once you have installed it, you can install SirMordred and the dependencies in a project isolated environment using:
```
$ poetry install
```
To spaw a new shell within the virtual environment use:
```
$ poetry shell
```

Usage

Now that you have the ElasticSearch, Kibiter and MariaDB running on your system and SirMordred installed, we can execute micro-mordred/sirmordred.

micro.py

usage: micro.py [--raw] [--enrich] [--identities-load] [--identities-merge] [--panels]
                [--cfg CFG_PATH] [--backends [BACKEND_SECTIONS [BACKEND_SECTIONS ...]]]
                [--repos [REPOS_TO_CHECK [REPOS_TO_CHECK ...]]] [--logs-dir LOGS_DIR]

optional arguments:
  --raw                 Activate raw task
  --enrich              Activate enrich task
  --identities-load     Activate load identities task
  --identities-merge    Activate merge identities task
  --panels              Activate panels task
  --cfg CFG_PATH        Configuration file path
  --backends [BACKEND_SECTIONS [BACKEND_SECTIONS ...]]
                        Backend sections to execute
  --repos [REPOS_TO_CHECK [REPOS_TO_CHECK ...]]
                        Limit which repositories are processed (list of URLs)
  --logs-dir LOGS_DIR   Logs Directory

sirmordred

usage: sirmordred [-h] [-c CONFIG_FILES [CONFIG_FILES ...]] [-t CONFIG_TEMPLATE_FILE]
                  [-p [PHASES [PHASES ...]]]

SirMordred, the friendly friend of GrimoireELK

optional arguments:
  -h, --help            show this help message and exit
  -c CONFIG_FILES [CONFIG_FILES ...], --config CONFIG_FILES [CONFIG_FILES ...]
                        Configuration files
  -t CONFIG_TEMPLATE_FILE, --template CONFIG_TEMPLATE_FILE
                        Create template configuration file
  -p [PHASES [PHASES ...]], --phases [PHASES [PHASES ...]]
                        List of phases to execute (update is set to false)

Software metrics for your peace of mind

Only docker ↑

Follow the instruction in the GrimoireLab tutorial to have SirMordred in a container

Troubleshooting ↑

Following is a list of common problems encountered while setting up GrimoireLab

Low Virtual Memory
Conflicts With Searchguard
Permission Denied
Empty Index
Low File Descriptors
Rate Limit Exhausted
No Swap Space
SSL error
Cloc installation
Not getting a full data set

NOTE: In order to see the logs, run docker-compose up without the -d or --detach option while starting/(re)creating/building/attaching containers for a service.

Low Virtual Memory ↑

Indications:gi Cannot open https://localhost:9200/ in browser. Shows Secure connection Failed, PR_END_OF_FILE_ERROR, SSL_ERROR_SYSCALL in connection to localhost:9200 messages.

Diagnosis: Check for the following log in the output of docker-compose up

elasticsearch_1  | ERROR: [1] bootstrap checks failed
elasticsearch_1  | [1]: max virtual memory areas vm.max_map_count [65530] is too low, increase to at least [262144]

Solution: Increase the kernel max_map_count parameter of vm. Execute the following command sudo sysctl -w vm.max_map_count=262144 Now stop the container services and re-run docker-compose up. Note that this is valid only for current session. To set this value permanently, update the vm.max_map_count setting in /etc/sysctl.conf. To verify after rebooting, run sysctl vm.max_map_count.

Processes have conflicts with SearchGuard ↑

Indications:
- Cannot open localhost:9200 in browser, shows Secure connection Failed
- curl -XGET localhost:9200 -k gives curl: (52) Empty reply from server

Diagnosis: Check for the following log in the output of docker-compose up

elasticsearch_1  | [2020-03-12T13:05:34,959][WARN ][c.f.s.h.SearchGuardHttpServerTransport] [Xrb6LcS] Someone (/172.18.0.1:59838) speaks http plaintext instead of ssl, will close the channel

Check for conflicting processes by running sudo lsof -i:58888 (e.g. 58888 is the port number)

Solution:
1. Try to close the conflicting processes: You can do this easily with fuser (sudo apt-get install fuser), run fuser -k 58888/tcp (e.g. 58888 is the port number). Re-run docker-compose up and check if localhost:9200 shows up.
2. Use a docker-compose without SearchGuard: Use the docker-compose above, this doesn't include SearchGuard. Note: With this docker-compose, access to the Kibiter and ElasticSearch don't require credentials. Re-run docker-compose up and check if localhost:9200 shows up.

Permission Denied ↑

Indications: Can't create indices in Kibana. Nothing happens after clicking create index.

Diagnosis: Check for the following log in the output of docker-compose up

elasticsearch_1 |[INFO ][c.f.s.c.PrivilegesEvaluator] No index-level perm match for User [name=readall, roles=[readall], requestedTenant=null] [IndexType [index=.kibana, type=doc]] [Action [[indices:data/write/index]]] [RolesChecked [sg_own_index, sg_readall]]

elasticsearch_1 | [c.f.s.c.PrivilegesEvaluator] No permissions for {sg_own_index=[IndexType [index=.kibana, type=doc]], sg_readall=[IndexType [index=.kibana, type=doc]]}

kibiter_1 | {"type":"response","@timestamp":CURRENT_TIME,"tags":[],"pid":1,"method":"post","statusCode":403,"req":{"url":"/api/saved_objects/index-pattern?overwrite=false","method":"post","headers":{"host":"localhost:5601","user-agent":YOUR_USER_AGENT,"accept":"application/json, text/plain, /","accept-language":"en-US,en;q=0.5","accept-encoding":"gzip, deflate","referer":"http://localhost:5601/app/kibana","content-type":"application/json;charset=utf-8","kbn-version":"6.1.4-1","content-length":"59","connection":"keep-alive"},"remoteAddress":YOUR_IP,"userAgent":YOUR_IP,"referer":"http://localhost:5601/app/kibana"},"res":{"statusCode":403,"responseTime":25,"contentLength":9},"message":"POST /api/saved_objects/index-pattern?overwrite=false 403 25ms - 9.0B"}

or any type of 403 error.

Solution: This message generally appears when you try to create an index pattern but you are not logged in Kibana. Try logging in to Kibana (the login button is on the bottom left corner). The credentials used for login should be username: admin and password: admin.

Empty Index ↑

Indications and Diagnosis: Check for the following error after executing Micro Mordred using micro.py --raw --enrich --panels --cfg ./setup.cfg --backends git(Here, using git as backend)
```
[git] Problem executing study enrich_areas_of_code:git, RequestError(400, 'search_phase_execution_exception', 'No mapping 
found for [metadata__timestamp] in order to sort on')
```
Solution: This error appears when the index is empty (here, git-aoc_chaoss_enriched index is empty). An index can be empty when the local clone of the repository being analyzed is in sync with the upstream repo, so there will be no new commits to ingest to grimoirelab.

There are 2 methods to solve this problem:

Method 1: Disable the param latest-items by setting it to false.

Method 2: Delete the local clone of the repo (which is stored in ~/.perceval/repositories).

Some extra details to better understand this behavior:

The Git backend of perceval creates a clone of the repository (which is stored in ~/.perceval/repositories) and keeps the local copy in sync with the upstream one. This clone is then used to ingest the commits data to grimoirelab. Grimoirelab periodically collects data from different data sources (in this specific case, a git repository) in an incremental way. A typical execution of grimoirelab for a git repository consists of ingesting only the new commits to the platform. These commits are obtained by comparing the local copy with the upstream one, thus if the two repos are synchronized, then no commits are returned and hence Index will be empty. In the case where all commits need to be extracted even if there is already a local clone, latest-items param should be disabled. Another option is to delete the local clone (which is stored at ~/.perceval/repositories), and by doing so the platform will clone the repo again and extract all commits.

Low File Descriptors ↑

Indications:
- Cannot open localhost:9200 in browser, shows Secure connection Failed
- curl -XGET localhost:9200 -k gives curl: (7) Failed to connect to localhost port 9200: Connection refused

Diagnosis: Check for the following log in the output of docker-compose up

  elasticsearch_1  | ERROR: [1] bootstrap checks failed
  elasticsearch_1  | [1]: max file descriptors [4096] for elasticsearch process is too low, increase to at least [65536]

Solution:
1. Increase the maximum File Descriptors (FD) enforced:
  
  You can do this by running the below command.
```
sysctl -w fs.file-max=65536
```
  To set this value permanently, update /etc/security/limits.conf content to below. To verify after rebooting, run sysctl fs.file-max.
```
elasticsearch   soft    nofile          65536
elasticsearch   hard    nofile          65536
elasticsearch   memlock unlimited
```
2. Override ulimit parameters in the ElasticSearch docker configuration:
  
  Add the below lines to ElasticSearch service in your compose file to override the default configurations of docker.
```
ulimits:
nofile:
  soft: 65536
  hard: 65536
```

Rate Limit Exhausted ↑

Indication: See error message RuntimeError: Rate limit exhausted.; 3581.0 seconds to rate reset
Solution : Enable the sleep-for-rate parameter. It increases rate by sleeping between API call retries.

No Swap Space ↑

Indication: While composing docker, NO SWAP SPACE would be displayed.

Solution: Edit the /etc/default/grub file with sudo previleges.

     GRUB_CMDLINE_LINUX="cgroup_enable=memory swapaccount=1" 
 	sudo update-grub

And restart the system.

SSL error ↑

Indication: localhost:9200 refuses connection error.
Diagnosis:

Retrying (Retry(total=10,connected=21,read=0,redirect=5,status=None)) after connection broken by 
'SSLError(SSLError{1,'[SSL: WRONG_VERSION_NUMBER] wrong version number {_ssl.c:852}'},)': /

Solution:

Change 'https' to 'http' in the setup.cfg file

[es_collection]
# arthur = true
# arthur_url = http://127.0.0.1:8080
# redis_url = redis://localhost/8
url = http://localhost:9200

[es_enrichment]
url = http://localhost:9200

Cloc installation ↑

Diagnosis:

: [Errno 2]No such file or directory : 'cloc': 'cloc'

Solution:

Execute the following command to install cloc (more details are available in the Graal repo)
```
sudo apt-get install cloc
```

Incomplete data ↑

Indication: Not all the data is being retrieved when rebuilding an index - only from a point in time forward.
Diagnosis: After a rebuild of git-based indices you are not receiving a full dataset as expected, but only from the date of the re-index forward. That data is complete, but anything prior to that is missing.
Solution: The setup.cfg file has an option under the Git configuration section: latest-items = true - set this to latest-items = false to pull in all data from the beginning. Once this has been processed, remember to set it back to latest-items = true!

How to ↑

Following are some tutorials for ElasticSearch and Kibiter:

Query data in ElasticSearch
Dump the index mapping/data with elasticdump
Save changes made in dashboard by mounting the volume in ES
Build a data table visualization in Kibiter
Modify the menu
Share a dashboard
Rename titles and resize a panel
Update format of attributes
Edit the name of a Visualization
Share a dashboard
Edit a Visualization
Check that the data is up to date
Handle identities assigned to "Unknown" organization
Add a new organization/domain entry via Hatstall
Remove Dockers and start a fresh environment

Elasticsearch

Query data in ElasticSearch ↑

To query data in ElasticSearch select Dev tools from the navigation menu in Kibiter and write the required query in the console.

The below query counts the number of unique authors on a Git repository from 2018-01-01 until 2019-01-01.

GET _search
{
  "size":"0",
  "query": {
    "range": {
      "author_date": {
        "gte": "2018-01-01T00:00:00",
        "lte": "2019-01-01T00:00:00"
      }
    }
  },
  "aggs": {
    "author_unique": {
       "cardinality": {
        "field": "author_id"
      }
    }
  }
}

The parameter size specifies that we don't need the data fetched from the index, this is included as only count of authors is required and not the data of authors. The parameter query includes the range of the field author_date for which the data is requested. The number of distinct author are calculated using cardinality of author_id.

Output:

{
 "took": 0,
 "timed_out": false,
 "_shards": {
   "total": 16,
   "successful": 16,
   "skipped": 0,
   "failed": 0
 },
 "hits": {
   "total": 128,
   "max_score": 0,
   "hits": []
 },
 "aggregations": {
   "author_unique": {
     "value": 11
   }
 }
}

The value field holds the number of distinct authors during the given time range.

Alternatively, a data table visualization can be created using the steps mentioned here. Then, a request can be generated by clicking the ^ symbol at the bottom. Kibiter then automatically generates a query as shown below.

Dump the index mapping/data with elasticdump ↑

Indexes and mappings can be dumped (or uploaded) using elasticdump. The commands to install elasticdump, dump an index and its index pattern to a file are shown below.

elasticdump installation

sudo apt install npm
sudo -i
npm install elasticdump -g

CTRL+D to logout from root user

Use the 'type' argument to either fetch data or mapping.

Dump the index data

elasticdump --input=http://localhost:9200/git_chaoss/ --output=git_data.json --type=data

Dump the index mapping

elasticdump --input=http://localhost:9200/git_chaoss/ --output=git_mapping.json --type=mapping

Save changes made in dashboard by mounting the volume in ES ↑

Creating new dashboard or new visualisation in the Kibana Dashabord can be saved permanently using volume mount in ElasticSearch

Using docker-compose:

1.Configure the docker-compose yml file:

services:
   elasticsearch:
      image: docker.elastic.co/elasticsearch/elasticsearch-oss:6.8.6
      command: elasticsearch -Enetwork.bind_host=0.0.0.0 -Ehttp.max_content_length=2000mb
      ports:
        - 9200:9200
      environment:
        - ES_JAVA_OPTS=-Xms2g -Xmx2g
        - ANONYMOUS_USER=true
      volumes:
        - <volumename>:/usr/share/elasticsearch/data
volumes:
  <volumename>:

2.Execute docker-compose up -d

3.Go to localhost:5601 and create new dashboard according to your requirements

4.Click on save

5.Save with some new name for the created dashboard

6.Stop the container by docker-compose down command

7.Start again by docker-compose up -d

You can see all the changes are persistently stored in the local folder and hence cannot be deleted even if all the containers are stopped, reason being volumes are created.

Note : If you do not want to use volumes for storage then you should use docker-compose stop instead of docker-compose down , so that none of the containers is removed.

Kibiter

Build a data table visualization in Kibiter ↑

Go to your Kibiter dashboard and select Visualize from the left navigation menu.
Click on the '+' icon next to the search bar to create a new visualization.
Select 'Data Table' to display the values in a table.
Select the index which is to be visualized.
Under the Bucket options click on Split Row to split the table into rows(or Split Table to split the table into additional tables) and set the following options:

Aggregation - Set it to Terms. This selects the fields in the table based on a term present in the index.
Field - Select the fields which are to be included in the table.
Order - Order in which fields are displayed.
Size - Maximum number of fields to be included in the table.

7 . Click the apply changes button to get the data table visualization. You can also save the visualizations for future references.

The below image uses the CHAOSS community dashboard to create a data table visualization on mbox index which is split row by the term body_extract.

Modify the menu ↑

Get the current menu: GET <elasticsearch_url>/.kibana/doc/metadashboard. It will return a json with the following structure:

{
  "metadashboard": [
      {
        "name": "Panel 1",
        "title": "Panel 1"
        "description": "This is a link to a panel",
        "panel_id": "panel_1",
        "type": "entry",
      },
      {
        "name": "Tab 1",
        "title": "Tab 1"
        "description": "This is a tab, when clicked a submenu with the panels will appear",
        "type": "menu",
        "dashboards": [
          {
            "description": "This is a link to a panel",
            "panel_id": "panel_1_tab_1",
            "type": "entry",
            "name": "Panel 1 of the Tab 1",
            "title": "Panel 1 of the Tab 1"
          },
          ...
        ],
      },
      ...
  ]
}

If you want to add an entry (a link to a dashboard) you can do it in two different ways:

Adding a link in the root menu:

{
  "metadashboard": [
      {
        "name": "Panel 1",
        "title": "Panel 1"
        "description": "This is a link to a panel",
        "panel_id": "panel_1",
        "type": "entry",
      },
      //////////New entry///////////
      {
        "name": "New entry",
        "title": "New entry"
        "description": "This is a link to a panel",
        "panel_id": "<id_of_the_dashboard>",
        "type": "entry",
      },
      /////////////////////////////
      {
        "name": "Tab 1",
        "title": "Tab 1"
        "description": "This is a tab, when clicked a submenu with the panels will appear",
        "type": "menu",
        "dashboards": [
          {
            "description": "This is a link to a panel",
            "panel_id": "panel_1_tab_1",
            "type": "entry",
            "name": "Panel 1 of the Tab 1",
            "title": "Panel 1 of the Tab 1"
          },
          ...
        ],
      },
      ...
  ]
}

Adding a link in a submenu of a tab:

{
  "metadashboard": [
      {
        "name": "Panel 1",
        "title": "Panel 1"
        "description": "This is a link to a panel",
        "panel_id": "panel_1",
        "type": "entry",
      },
      {
        "name": "Tab 1",
        "title": "Tab 1"
        "description": "This is a tab, when clicked a submenu with the panels will appear",
        "type": "menu",
        "dashboards": [
          {
            "description": "This is a link to a panel",
            "panel_id": "panel_1_tab_1",
            "type": "entry",
            "name": "Panel 1 of the Tab 1",
            "title": "Panel 1 of the Tab 1"
          },
          //////////New entry///////////
          {
            "name": "New entry",
            "title": "New entry"
            "description": "This is a link to a panel",
            "panel_id": "<id_of_the_dashboard>",
            "type": "entry",
          },
          /////////////////////////////
          ...
        ],
      },
      ...
  ]
}

If you want to add a new tab (item that will show a submenu with entries) you must do it in the root menu:

{
  "metadashboard": [
      {
        "name": "Panel 1",
        "title": "Panel 1"
        "description": "This is a link to a panel",
        "panel_id": "panel_1",
        "type": "entry",
      },
      {
        "name": "Tab 1",https://user-images.githubusercontent.com/35267629/79070495-efc84c80-7cf3-11ea-8543-66989e84c094.gif
        "title": "Tab 1"
        "description": "This is a tab, when clicked a submenu with the panels will appear",
        "type": "menu",
        "dashboards": [
          {
            "description": "This is a link to a panel",
            "panel_id": "panel_1_tab_1",
            "type": "entry",
            "name": "Panel 1 of the Tab 1",
            "title": "Panel 1 of the Tab 1"
          },
          ...
        ],
      },
      //////////New tab///////////
      {
        "name": "New tab",
        "title": "New tab"
        "description": "This is a tab, when clicked a submenu with the panels will appear",
        "type": "menu",
        "dashboards": [
          {
            "description": "This is a link to a panel",
            "panel_id": "<id_of_the_dashboard>",
            "type": "entry",
            "name": "Panel 1 of the New tab",
            "title": "Panel 1 of the New tab"
          },
          ...
        ],
      },
      ////////////////////////////
      ...
  ]
}

Once the json of the menu has been modified, the final step is to upload it updating the version: PUT <elasticsearch_url>/.kibana/doc/metadashboard

⚠️ If you change the structure or delete it you won't see the menu.

Note: the <id_of_the_dashboard> must be the identifier that Kibana/Kibiter put to a saved dashboard.

Rename titles and resize a panel ↑

All the gitter panel titles can be renamed and resized as shown.

Update format of attributes ↑

In order to convert URLs in a table visualization from plain text to a link you need to update the format of the attribute in index pattern as shown.

Plain text URL -

Hyperlink -

Share a dashboard ↑

Click on share on top right corner of the browser.
There will be 2 options: Share saved Dashboard or share snapshot.
Copy the link present under 'Link' under 'Share Saved dashboard' and use it anywhere. This will be a shortened url, and can be easily used across browsers.
You can also extract the embedded iframe and add it to the HTML source.

Edit the name of a visualization ↑

Go to Save visualization on top right of browser window.
Enter the new name. The default name is 'New Visualization'.
Uncheck the option that says 'save as a new visualization'.
Now you can see the changed name of the visualization.

Edit a visualization ↑

Go to 'Visualize' option given on the left sidebar.
Open the saved visualization file.
Make changes as per needs.
Save again by Clicking 'Save'.

Check that the data is up to date ↑

Go to Data Status on top right of browser window.
Check the last retrieval date to know the last date of data retrieval.

Identity management

Handle identities assigned to "Unknown" organization ↑

To provide some context, SortingHat is the GrimoireLab tool behind the scenes which is in charge of managing the identities information from the sources you are analyzing.

SortingHat allows to manage affiliation information too, including the organization(s) a person/user belongs to and the date periods for each of them. The organization a user belongs to can be inferred using the email domains from every user, for instance: if we have a user who contributed to one of the sources with an email with domain @mozilla.com, it will be automatically affiliated to Mozilla organization.

This automatic affiliation works because there is an entry in SortingHat registry matching mozilla.com domain with Mozilla organization. When this automatic affiliation cannot be applied, that user will not have any affiliation information (at least for the period of time you are visualizing on the dashboard after setting a date range with the time-picker), it will appear as Unknown on the dashboard.

This could be happening because:

(1) There is no email domain information for those users.
(2) Their email domain(s) are not linked to any organization in SortingHat.
(3) The same user can have different identities (e.g. contributions coming from different sources or accounts) and they are considered as different individuals.

About possible solutions:

(2) can be solved by adding the corresponding entry to SortingHat, i.e. via Hatstall.
(3) can be solved by merging those identities under the same individual, which can be done via SortingHat too.

Note: by default, SortingHat is importing the list of organizations and domains from this file.

Add a new organization/domain entry via Hatstall ↑

Hatstall is a web interface to interact with SortingHat.

Tip: if you are executing GrimoireLab via docker-compose, you can access Hatstall from http://127.0.0.1:8000/. Default credentials are admin-admin, as explained in this README section.

For adding a new organization domain from Hatstall, you have to click on Organizations tab on the nav bar, and then:

First, look for the organization you are interested in (you can navigate though the pages or you can use the search bar).
- If the organization you are looking for does not appear, click on Add button and add the new organization first.
Once you have located the organization, click on edit and then a menu will pop-up on the right. There, you will be able to add new domains for that organization.

Others

Remove existing dockers and start a fresh environment ↑

Stop and remove all the containers with docker-compose down --remove-orphans.
Run docker ps and ensure that there is no entry in the output.
Remove all unused containers, images, and volumes with docker system prune -a --volumes.
Now, execute docker-compose up -d using the source code (see - https://github.com/chaoss/grimoirelab-sirmordred/blob/master/Getting-Started.md#source-code-and-docker- )
Check connection to Elasticsearch with curl -XGET <elasticsearch-url> -k. The output should be the similar to :

{
"name" : "1STIspn",
"cluster_name" : "bitergia_elasticsearch",
"cluster_uuid" : "NNHIQCbDQHG5sg2MX_WRjA",
"version" : {
 "number" : "6.8.6",
 "build_flavor" : "oss",
 "build_type" : "tar",
 "build_hash" : "3d9f765",
 "build_date" : "2019-12-13T17:11:52.013738Z",
 "build_snapshot" : false,
 "lucene_version" : "7.7.2",
 "minimum_wire_compatibility_version" : "5.6.0",
 "minimum_index_compatibility_version" : "5.0.0"
},
"tagline" : "You Know, for Search"
}

Execute micro mordred (see - https://github.com/chaoss/grimoirelab-sirmordred#micro-mordred-)

Files

Getting-Started.md

Latest commit

History

Getting-Started.md

File metadata and controls

Getting started ↑

Source code and docker ↑

Getting the containers ↑

docker-compose (with SearchGuard) ↑

docker-compose (without SearchGuard) ↑

Cloning the repositories ↑

ProTip ↑

Setting up PyCharm ↑

Execution ↑

SirMordred and docker ↑

PyPI

Source code

Usage

Only docker ↑

Troubleshooting ↑

Low Virtual Memory ↑

Processes have conflicts with SearchGuard ↑

Permission Denied ↑

Empty Index ↑

Low File Descriptors ↑

Rate Limit Exhausted ↑

No Swap Space ↑

SSL error ↑

Cloc installation ↑

Incomplete data ↑

How to ↑

Elasticsearch

Query data in ElasticSearch ↑

Dump the index mapping/data with elasticdump ↑

Save changes made in dashboard by mounting the volume in ES ↑

Kibiter

Build a data table visualization in Kibiter ↑

Modify the menu ↑

Rename titles and resize a panel ↑

Update format of attributes ↑

Share a dashboard ↑

Edit the name of a visualization ↑

Edit a visualization ↑

Check that the data is up to date ↑

Identity management

Handle identities assigned to "Unknown" organization ↑

Add a new organization/domain entry via Hatstall ↑

Others

Remove existing dockers and start a fresh environment ↑