GitLab plugin

Visit our website to see the data that you can access if you use this plugin to add the data source to SquaredUp:

GitLab

Monitor the CI/CD metrics from your GitLab environment.

How to add a GitLab data source

To create an API token key:

1. Access a GitLab account with access to the target projects.

2. Navigate to https://gitlab.com/-/profile/personal_access_tokens.

3. Ensure the access is at least read_api and read_repository. Please note, read_user and read_registry are optional.

4. Click the Create personal access token button.

5. Copy the provided API token.

Now use the API token to configure the data source in SquaredUp:

1. In SquaredUp browse to Data Sources > Add data source and search for the data source. Alternatively, browse to Settings > Data Sources > Add data source.

2. Display Name:

   Enter a name for your data source. This helps you to identify this data source in the list of your data sources.

3. 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.

4. API Token:

   Paste the API token in here.

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

   Restrict access to this data source?

   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 tenant.

   • 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.

   Data source access levels

   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.

6. Click Save.

Using the GitLab data streams

What is a data stream?

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").

Data streams are installed with the data source

How to create a data stream for this data source:

• Create a data stream using the configurable data stream form see GQL Query

Creating a data stream using the configurable data stream

What is a configurable data stream?

A configurable data stream allows you to easily create new data streams specific to your needs, by entering information into a form, such as metric names or queries. Configurable data streams have a cog icon next to their name in the tile editor.

Any data stream you create can be edited by clicking the edit button (pencil) next to it in the tile editor, and also from Settings > Advanced > Data Streams.

GQL Query

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

1. In the tile editor, filter by the GitLab data source, select GQL Query from the data stream list and then click Next.

2. Query:

   Enter a GQL query.

3. RowPath:

   Optional, focus on results within the GQL query. Target on the array of data that you want to display. For example: projects.nodes.

4. Click Save.

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.

Supports mustache parameters

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, 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.