Jobs artifacts administration

Notes:

  • Introduced in GitLab 8.2 and GitLab Runner 0.7.0.
  • Starting with GitLab 8.4 and GitLab Runner 1.0, the artifacts archive format changed to ZIP.
  • Starting with GitLab 8.17, builds are renamed to jobs.
  • This is the administration documentation. For the user guide see pipelines/job_artifacts.

Artifacts is a list of files and directories which are attached to a job after it completes successfully. This feature is enabled by default in all GitLab installations. Keep reading if you want to know how to disable it.

Disabling job artifacts

To disable artifacts site-wide, follow the steps below.


In Omnibus installations:

  1. Edit /etc/gitlab/gitlab.rb and add the following line:

    gitlab_rails['artifacts_enabled'] = false
  2. Save the file and reconfigure GitLab for the changes to take effect.


In installations from source:

  1. Edit /home/git/gitlab/config/gitlab.yml and add or amend the following lines:

    artifacts:
      enabled: false
  2. Save the file and restart GitLab for the changes to take effect.

Storing job artifacts

After a successful job, GitLab Runner uploads an archive containing the job artifacts to GitLab.

Using local storage

To change the location where the artifacts are stored locally, follow the steps below.


In Omnibus installations:

The artifacts are stored by default in /var/opt/gitlab/gitlab-rails/shared/artifacts.

  1. To change the storage path for example to /mnt/storage/artifacts, edit /etc/gitlab/gitlab.rb and add the following line:

    gitlab_rails['artifacts_path'] = "/mnt/storage/artifacts"
  2. Save the file and reconfigure GitLab for the changes to take effect.


In installations from source:

The artifacts are stored by default in /home/git/gitlab/shared/artifacts.

  1. To change the storage path for example to /mnt/storage/artifacts, edit /home/git/gitlab/config/gitlab.yml and add or amend the following lines:

    artifacts:
      enabled: true
      path: /mnt/storage/artifacts
  2. Save the file and restart GitLab for the changes to take effect.

Using object storage

In GitLab Enterprise Edition Premium you can use an object storage like AWS S3 to store the artifacts.

Learn how to use the object storage option.

Expiring artifacts

If an expiry date is used for the artifacts, they are marked for deletion right after that date passes. Artifacts are cleaned up by the expire_build_artifacts_worker cron job which is run by Sidekiq every hour at 50 minutes (50 * * * *).

To change the default schedule on which the artifacts are expired, follow the steps below.


In Omnibus installations:

  1. Edit /etc/gitlab/gitlab.rb and comment out or add the following line

    gitlab_rails['expire_build_artifacts_worker_cron'] = "50 * * * *"
  2. Save the file and reconfigure GitLab for the changes to take effect.


In installations from source:

  1. Edit /home/git/gitlab/config/gitlab.yml and add or amend the following lines:

    expire_build_artifacts_worker:
      cron: "50 * * * *"
  2. Save the file and restart GitLab for the changes to take effect.

Set the maximum file size of the artifacts

Provided the artifacts are enabled, you can change the maximum file size of the artifacts through the Admin area settings.

Storage statistics

You can see the total storage used for job artifacts on groups and projects in the administration area, as well as through the groups and projects APIs.

Implementation details

When GitLab receives an artifacts archive, an archive metadata file is also generated. This metadata file describes all the entries that are located in the artifacts archive itself. The metadata file is in a binary format, with additional GZIP compression.

GitLab does not extract the artifacts archive in order to save space, memory and disk I/O. It instead inspects the metadata file which contains all the relevant information. This is especially important when there is a lot of artifacts, or an archive is a very large file.

When clicking on a specific file, GitLab Workhorse extracts it from the archive and the download begins. This implementation saves space, memory and disk I/O.