GitLab plugin

For more information about what this plugin does and the data streams it retrieves, see:

Monitor the CI/CD metrics from your GitLab environment.

How to add the data source

To add a data source click on the + next to Data Sources on the left-hand menu in SquaredUp. Search for the data source and click on it to open the Configure data source page.

Before you start

Create a GitLab API Token

Access a GitLab account with access to the target projects.
Navigate to https://gitlab.com/-/profile/personal_access_tokens.
Ensure the access is at least read_api and read_repository. Please note, read_user and read_registry are optional.
Click the Create personal access token button.
Copy the provided API token.

Configuring the data source

Display Name:
Enter a name for your data source. This helps you to identify this data source in the list of your data sources.
Instance URL:
Enter a URL if you wish to use your own instance of GitLab.
If you leave this section blank, https://gitlab.com will be used by default.
API Token:
Paste the API token in here.

Optionally, select whether you would like to restrict access to this data source instance. By default, restricted access is set to off.

The term data source here really means data source instance. For example, a user may configure two instances of the AWS data source, one for their development environment and one for production. In that case, each data source instance has its own access control settings.

By default, Restrict access to this data source is set to off. The data source can be viewed, edited and administered by anyone. If you would like to control who has access to this data source, switch Restrict access to this data source to on.

Use the Restrict access to this data source dropdown to control who has access to the workspace:

By default, the user setting the permissions for the data source will be given Full Control and the Everyone group will be given Link to workspace permissions.
Tailor access to the data source, as required, by selecting individual users or user groups from the dropdown and giving them Link to workspace or Full Control permissions.
If the user is not available from the dropdown, you are able to invite them to the data source by typing in their email address and then clicking Add. The new user will then receive an email inviting them to create an account on SquaredUp. Once the account has been created, they will gain access to the organization.
At least one user or group must be given Full Control.
Admin users can edit the configuration, modify the Access Control List (ACL) and delete the data source, regardless of the ACL chosen.

Access Level:

Link to workspace	User can link the data source to any workspace they have at least Editor permissions for. Data from the data source can then be viewed by anyone with any access to the workspace. User can share the data source data with anyone they want. User cannot configure the data source in any way, or delete it.
Full Control	User can change the data source configuration, ACL, and delete the data source.

See Access control for more information.

Click Test and add to validate the data source configuration.
- Testing passed – a success message will be displayed and then the configuration will be saved.
- Testing passed with warnings – warnings will be listed and potential fixes suggested. You can still use the data source with warnings. Select Save with warnings if you believe that you can still use the data source as required with the warnings listed. Alternatively, address the issues listed and then select Rerun tests to validate the data source configuration again. If the validation now passes, click Save.
- Testing Failed – errors will be listed and potential fixes suggested. You cannot use the data source with errors. You are able to select Save with errors if you believe that a system outside of SquaredUp is causing the error that you need to fix. Alternatively, address the issues listed and then select Rerun tests to validate the data source configuration again. If the validation now passes, click Save.
You can edit any data source configurations at any time from Settings > Data Sources.
You can also add a data source from Settings > Data Sources > Add data source, but sample dashboards are not added when using this method.

Using the GitLab data streams

Data streams standardize data from all the different shapes and formats your tools use into a straightforward tabular format. While creating a tile you can tweak data streams by grouping or aggregating specific columns. Depending on the kind of data, SquaredUp will automatically suggest how to visualize the result, for example as a table or line graph.

Data streams can be either global or scoped:

Global data streams are unscoped and return information of a general nature (e.g. "Get the current number of unused hosts").
A scoped data stream gets information relevant to the specific set objects supplied in the tile scope (e.g. "Get the current session count for these hosts").

See Data Streams for more information.

Data streams

The following data streams are installed with this plugin.

The GitLab data source allows you to set up configurable data streams for any kind of GQL query. If you need help using GQL, please refer to: GraphQL

Scope to an object that supports a GQL query.
Select + GQL Query from the data stream list.
Display Name:
Enter a name for the new data stream.
Query:
Enter a GQL query.
RowPath:
Optional, focus on results within the GQL query. Target on the array of data that you want to display. For example: projects.nodes.

This example query shows you how to get the details about the current user, the groups it has access to and the project IDs in those groups.
```
query{
  currentUser{
    groups{
      nodes
      {
        projects {
          edges {
            node {
              id
              name
            }
          }
        }
        fullName
        id
      }
      
    }
    name
    id
  }
}
```
You’ll need to inform the cloud platform where the rows start. It must be a value returned as an array, such as edges (in the above example) or nodes.

You can use mustache to alter the query with values from the scope.
A mustache parameter is a dynamic value, the actual value will be inserted to replace the field in curly braces. For example, {{timeframe.start}} will insert the start time based on the timeframe configured within the tile, or {{name}} will insert the name of the object(s) in scope.
This data stream supplies scoped objects individually for mustache parameters. When there are multiple objects in scope this data source will send the query multiple times, once for each object. The results are then displayed together, for example in a single table.
You can use properties of objects and write them in between curly braces e.g {{name}} to use them as mustache parameters. Whenever you use mustache parameters, you need to use a scope of objects that contain the property you're referencing.
For example, if objects of type "host" have a property called name, you can use {{name}}. This will resolve {{name}} to the value of the name property of the different "host" objects used in the scope.

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