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Since running our functional test suite in GitLab cannot make use of the shared resources it makes sense to document the process of adding own HW to run the custom libvirt executor that powers the integration suite. This article will likely make even more sense in the future with GitLab severely cutting down on shared CI resources. Signed-off-by: Erik Skultety <eskultet@redhat.com> Reviewed-by: Daniel P. Berrangé <berrange@redhat.com>
87 lines
3.7 KiB
ReStructuredText
87 lines
3.7 KiB
ReStructuredText
GitLab CI Custom (Specific) Runners
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===================================
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.. contents::
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GitLab's CI allows additional machines to be added to the project's or group's
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pool of runners (a runner is a machine running the GitLab's
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`gitlab-runner <https://gitlab.com/gitlab-org/gitlab-runner/>`__ agent service).
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Upon registering the runner the runner will then be ready accepting CI jobs
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depending on the pipeline configuration. Unlike the shared runners provided
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directly by GitLab's hosted SaaS specific runners are only used within the
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project/group which they were registered to, so you don't need to worry about
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forks burning CPU cycles on your precious HW resources.
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Understandably, we respect your decision to keep your runners only visible to
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your fork, but for the sake of the community we'd appreciate if you decided to
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register your runner with the upstream libvirt project instead. As we're only
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interested in running upstream test workloads (which you can even help
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defining) maintenance and security of the HW is your own responsibility and so
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we can promise to never ask for physical or remote access to the machine.
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Machine Setup Howto
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-------------------
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The following sections will guide you through the necessary setup of your
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specific GitLab runners.
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gitlab-runner setup and registration
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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The gitlab-runner agent needs to be installed on each machine that is supposed
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to run jobs. The association between a machine and a GitLab project
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happens with a registration token. To find the registration token for
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your repository/project, navigate on GitLab's web UI to:
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* Settings (the gears-like icon at the bottom of the left hand side
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vertical toolbar), then
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* CI/CD, then
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* Runners, and click on the *Expand* button, then
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* Under *Set up a specific Runner manually*, look for the value under
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*And this registration token:*
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Note that in order to register a runner with the upstream libvirt project
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you'll need to work with the project maintainers to successfully register your
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machine.
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Following the `registration <https://docs.gitlab.com/runner/register/>`__
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process, it's necessary to configure the runner tags, and optionally other
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configurations on the GitLab UI. Navigate to:
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* Settings (the gears like icon), then
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* CI/CD, then
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* Runners, and click on the *Expand* button, then
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* *Runners activated for this project*, then
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* Click on the *Edit* icon (next to the *Lock* Icon)
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Don't forget to add a tag to your runner as these are used to route specific
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jobs to specific runners, e.g. if a job in ``ci/integration.yml`` looked like
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this ::
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centos-stream-9-tests:
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...
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variables:
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# needed by libvirt-gitlab-executor
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DISTRO: centos-stream-9
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# can be overridden in forks to set a different runner tag
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LIBVIRT_CI_INTEGRATION_RUNNER_TAG: my-vm-host
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tags:
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- $LIBVIRT_CI_INTEGRATION_RUNNER_TAG
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it would mean that the CentOS Stream 9 job would only be scheduled on runners
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bearing the 'my-vm-host' tag.
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Running integration tests
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~~~~~~~~~~~~~~~~~~~~~~~~~
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Libvirt's integration tests run in a nested virtualization environment. So, if
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you wish to run integration tests on your bare-metal machine, you'll have to
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make use of GitLab's
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`custom executor <https://docs.gitlab.com/runner/executors/custom.html>`__
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feature which allows you to provision any kind of environment for a workload to
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run - in libvirt's case - a virtual machine. If you need any help with creating
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VM template images ready to run libvirt's integration test suite, have a look
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at the `libvirt-gitlab-executor <https://gitlab.com/libvirt/libvirt-custom-executor>`__
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project which encapsulates provisioning, execution, and teardown of the
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virtualized environments in a single tool.
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