Registering a GitLab Data Source


Before synchronizing data from a GitLab project (e.g. for deploying algorithm models), you need to register the data source to configure the connection information of the GitLab server.


This section shows the steps to register a GitLab data source in EnOS.

Prerequisites

Before registering a GitLab data source connection, ensure that the OU administrator has configured the Git server whitelist through the Git White List page.

Procedure

  1. In the EnOS Management Console, click Data Source Registration from the left navigation menu.

  2. Click Add Data Source and provide information for the following.

    • Data Source Type: Select GitLab.

    • Data Source Name: Enter a name for the data source. The maximum length is 50 characters and can be a combination of the following characters.

      • a through z
      • A through Z
      • 0 through 9
      • _ (underscore)
      • -(hyphen)


    • Data Source Description: Enter a description for the data source.

    • Token: Enter the access token for accessing the GitLab repository. The steps for getting the access token are as per the below.

      • Log in to the GitLab project, click the User drop-down list in the upper right corner, and select Settings.
      • On the User Settings page, select Access Tokens from the left navigation bar.
      • Enter a name for the access token to be created, select an expiring date, select the api, read_user, read_repository permission options, and click Create personal access token.
      • In the Your New Personal Access Token field, copy the generated access token.


    • Git URL: Enter the URL of the GitLab project, using the format http://hostname:port/namespace.


  3. Click Test to test the data source connection.

    _images/gitlab_connection.png
  4. Click Done to save the configuration.

Results

The data source will be shown in the Data Source Registration table.

Next Step

When the connection is successfully established, you can add files from the GitLab project to data processing jobs, such as developing scripts and creating job resource versions.