Docker CI — The Mesa 3D Graphics Library latest documentation

# Docker CI

For LLVMpipe and Softpipe CI, we run tests in a container containing VK-GL-CTS, on the shared GitLab runners provided by freedesktop

## Software architecture

The Docker containers are rebuilt using the shell scripts under .gitlab-ci/container/ when the FDO_DISTRIBUTION_TAG changes in .gitlab-ci.yml. The resulting images are around 1 GB, and are expected to change approximately weekly (though an individual developer working on them may produce many more images while trying to come up with a working MR!).

gitlab-runner is a client that polls gitlab.freedesktop.org for available jobs, with no inbound networking requirements. Jobs can have tags, so we can have DUT-specific jobs that only run on runners with that tag marked in the GitLab UI.

Since dEQP takes a long time to run, we mark the job as “parallel” at some level, which spawns multiple jobs from one definition, and then deqp-runner.sh takes the corresponding fraction of the test list for that job.

To reduce dEQP runtime (or avoid tests with unreliable results), a deqp-runner.sh invocation can provide a list of tests to skip. If your driver is not yet conformant, you can pass a list of expected failures, and the job will only fail on tests that aren’t listed (look at the job’s log for which specific tests failed).

## DUT requirements

In addition to the general CI job user expectations, using Docker requires:

- DUTs must have a stable kernel and GPU reset (if applicable).

If the system goes down during a test run, that job will eventually time out and fail (default 1 hour). However, if the kernel can’t reliably reset the GPU on failure, bugs in one MR may leak into spurious failures in another MR. This would be an unacceptable impact on Mesa developers working on other drivers.

- DUTs must be able to run Docker

The Mesa gitlab-runner based test architecture is built around Docker, so that we can cache the Debian package installation and CTS build step across multiple test runs. Since the images are large and change approximately weekly, the DUTs also need to be running some script to prune stale Docker images periodically in order to not run out of disk space as we rev those containers (perhaps this script).

Note that Docker doesn’t allow containers to be stored on NFS, and doesn’t allow multiple Docker daemons to interact with the same network block device, so you will probably need some sort of physical storage on your DUTs.

- DUTs must be public

By including your device in .gitlab-ci.yml, you’re effectively letting anyone on the internet run code on your device. Docker containers may provide some limited protection, but how much you trust that and what you do to mitigate hostile access is up to you.

- DUTs must expose the DRI device nodes to the containers.

Obviously, to get access to the HW, we need to pass the render node through. This is done by adding `devices = ["/dev/dri"]` to the `runners.docker` section of /etc/gitlab-runner/config.toml.