Team responsibility

Build is about how we ship GitLab, and making sure everyone can easily install, update and maintain GitLab.

This means:

Our official installations cover:

  1. Omnibus packages for LTS versions of all major Linux operating systems (Ubuntu, Debian,CentOS/RHEL, OpenSUSE, SLES) and instructions for Ubuntu on Windows 10
  2. Docker Images and images for all major clouds (AWS, GCP, Azure)
  3. A helm chart for Kubernetes and instructions for major container schedulers (GKE, OpenShift, Tectonic, kubeadm, Docker Swarm, Mesosphere DC/OS)
  4. Pivotal Cloud Foundry tile.

How to work with Build

Everything that is done in GitLab will end up in the packages that are shipped to users. While that sounds like the last link in the chain, it is one of the most important ones. This means that informing the Build team of a change in an early stage is crucial for releasing your feature. While last minute changes are inevitable and can happen, we should strive to avoid them.

We expect every team to reach out to the Build team before scheduling a feature in an upcoming release in the following cases:

To sum up the above list:

If you need to do install, update, make, mkdir, mv, cp, chown, chmod, compilation or configuration change in any part of GitLab stack, you need to reach out to the Build team for opinion as early as possible.

This will allow us to schedule appropriately the changes (if any) we have to make to the packages.

If a change is reported late in the release cycle or not reported at all, your feature/change might not be shipped within the release.

If you have any doubt whether your change will have an impact on the Build team, don't hesitate to ping us in your issue and we'll gladly help.


  1. Installation page visuals
  2. Lower the barrier of contributing to the Build team task
    • First goal, allow simpler creation of packages:

Internal team training

Every Build team member is responsible for creating a training session for the rest of the team. These trainings will be recorded and available to the whole team.


The purpose of team training is to introduce the work done to the rest of your team. It also allows the rest of the team to easily transition into new features and projects and prepare them for maintenance.

Training should be:

Training should not be:

Simply put, the training is a summation of: notes taken in issues during development, programming challenges, high level overview of written documentation. Your team member should be able to take over the maintenance or build on top of your feature with less effort after they have been part of the training.

Note Do not shy away from being technical in your training. You can ask yourself: What would have been useful for me when I started working on this task? What would have helped me be more efficient?

Efficiency of the training

In order to see whether the training is efficient, Build lead will rotate team members on projects where training was done. For example, if the feature requires regular releases, the person who gave the training will be considered a tutor. Different team member will follow the training and documentation and will ask the original maintainer for help. The new person responsible is now also responsible for improving the feature. They are now also responsible of training other team members.


Q: Isn't this double work? A: No. The training should be prepared while documenting the task.

Q: Won't this slow me down? A: At the beginning, possibly. However, every hour of the training given will multiple the value of it by the amount of team members.

Q: Isn't it more useful to let the team check out the docs and ask questions? A: In an ideal world, possibly. However, everyone has a lot of tasks assigned and they might not be able to go through the docs until they need to do something. This might be months later and you, as a person who would give the training, might not be able help efficiently anymore.

Cloud Images

The process documenting the steps necessary to update the GitLab images available on the various cloud providers is detailed on our Cloud Image Process page.