libvirt: GitLab CI Custom (Specific) Runners
Description: libvirt, virtualization, virtualization API

# GitLab CI Custom (Specific) Runners

GitLab's CI allows additional machines to be added to the project's or group's pool of runners (a runner is a machine running the GitLab's gitlab-runner agent service). Upon registering the runner the runner will then be ready accepting CI jobs depending on the pipeline configuration. Unlike the shared runners provided directly by GitLab's hosted SaaS specific runners are only used within the project/group which they were registered to, so you don't need to worry about forks burning CPU cycles on your precious HW resources.

Understandably, we respect your decision to keep your runners only visible to your fork, but for the sake of the community we'd appreciate if you decided to register your runner with the upstream libvirt project instead. As we're only interested in running upstream test workloads (which you can even help defining) maintenance and security of the HW is your own responsibility and so we can promise to never ask for physical or remote access to the machine.

## Machine Setup Howto

The following sections will guide you through the necessary setup of your specific GitLab runners.

### gitlab-runner setup and registration

The gitlab-runner agent needs to be installed on each machine that is supposed to run jobs. The association between a machine and a GitLab project happens with a registration token. To find the registration token for your repository/project, navigate on GitLab's web UI to:

> - Settings (the gears-like icon at the bottom of the left hand side vertical toolbar), then

> - CI/CD, then

> - Runners, and click on the Expand button, then

> - Under Set up a specific Runner manually, look for the value under And this registration token:

Note that in order to register a runner with the upstream libvirt project you'll need to work with the project maintainers to successfully register your machine.

Following the registration process, it's necessary to configure the runner tags, and optionally other configurations on the GitLab UI. Navigate to:

> - Settings (the gears like icon), then

> - CI/CD, then

> - Runners, and click on the Expand button, then

> - Runners activated for this project, then

> - Click on the Edit icon (next to the Lock Icon)

Note: GitLab has changed the runner registration process deprecating the use of registration tokens in future versions, so while the above process is still applicable (though the settings are now a bit more hidden) at the time of writing this note (09/2023), GitLab v18.0+ is planned to completely switch to a new process (see the links below), deleting the use of registration tokens.

> - https://gitlab.com/gitlab-org/gitlab/-/issues/380872

> - https://docs.gitlab.com/ee/ci/runners/new_creation_workflow.html

> - https://docs.gitlab.com/ee/ci/runners/runners_scope.html#create-a-shared-runner-with-a-runner-authentication-token

Don't forget to add a tag to your runner as these are used to route specific jobs to specific runners, e.g. if a job in ci/integration.yml looked like this

    centos-stream-9-tests:
    ...
    variables:
      # needed by libvirt-gitlab-executor
      DISTRO: centos-stream-9
      # can be overridden in forks to set a different runner tag
      LIBVIRT_CI_INTEGRATION_RUNNER_TAG: my-vm-host
    tags:
    - $LIBVIRT_CI_INTEGRATION_RUNNER_TAG

it would mean that the CentOS Stream 9 job would only be scheduled on runners bearing the 'my-vm-host' tag.

### Running integration tests

Libvirt's integration tests run in a nested virtualization environment. So, if you wish to run integration tests on your bare-metal machine, you'll have to make use of GitLab's custom executor feature which allows you to provision any kind of environment for a workload to run - in libvirt's case - a virtual machine. If you need any help with creating VM template images ready to run libvirt's integration test suite, have a look at the libvirt-gitlab-executor project which encapsulates provisioning, execution, and teardown of the virtualized environments in a single tool.