Continuous Integration is important component of making Apache Airflow robust and stable. We are running a lot of tests for every pull request, for master and v1-10-test branches and regularly as CRON jobs.
Our execution environment for CI is GitHub Actions. GitHub Actions (GA) are very well integrated with GitHub code and Workflow and it has evolved fast in 2019/202 to become a fully-fledged CI environment, easy to use and develop for, so we decided to switch to it. Our previous CI system is Travis CI.
However part of the philosophy we have is that we are not tightly coupled with any of the CI environments we use. Most of our CI jobs are written as bash scripts which are executed as steps in the CI jobs and we are mapping all the CI-specific environment variables to generic "CI" variables. The only two places where CI-specific code might be are:
- CI-specific declaration file (for example it is .github/workflow/ci.yml for GitHub Actions
- The
get_ci_environmentfunction in scripts/ci/_utils.sh where mapping is performed from the CI-environment specific to generic values. Example for that is CI_EVENT_TYPE variable which determines whether we are running apush.scheduleorpull_requestkind of CI job. For GitHub Action those are values mapped fromGITHUB_EVENT_NAMEvariable, for Travis several other variables were used to determine it (TRAVIS_PULL_REQUEST,TRAVIS_EVENT_TYPE).
The following components are part of the CI infrastructure
- Apache Airflow Code Repository - our code repository at https://github.com/apache/airflow
- Apache Airflow Forks - forks of the Apache Airflow Code Repository from which contributors make Pull Requests
- GitHub Actions - (GA) UI + execution engine for our jobs
- GA CRON trigger - GitHub Actions CRON triggering our jobs
- GA Workers - virtual machines running our jobs at GitHub Actions (max 20 in parallel)
- GitHub Private Image Registry- image registry used as build cache for CI jobs. It is at https://docker.pkg.github.com/apache/airflow/airflow
- DockerHub Public Image Registry - publicly available image registry at DockerHub. It is at https://hub.docker.com/repository/docker/apache/airflow
- DockerHub Build Workers - virtual machines running build jibs at DockerHub
- Official Images (future) - these are official images that are prominently visible in DockerHub.
We aim our images to become official images so that you will be able to pull them
with
docker pull apache-airflow
The following CI Job runs are currently run for Apache Airflow, and each of the runs have different purpose and context.
- Pull Request Run - Those runs are results of PR from the forks made by contributors. Most builds for Apache Airflow fall into this category. They are executed in the context of the "Fork", not main Airflow Code Repository which means that they have only "read" permission to all the GitHub resources (container registry, code repository). This is necessary as the code in those PRs (including CI job definition) might be modified by people who are not committers for the Apache Airflow Code Repository. The main purpose of those jobs is to check if PR builds cleanly, if the test run properly and if the PR is ready to review and merge. The runs are using cached images from the Private GitHub registry - CI, Production Images as well as base Python images that are also cached in the Private GitHub registry.
- Direct Push/Merge Run - Those runs are results of direct pushes done by the committers or as result of merge of a Pull Request by the committers. Those runs execute in the context of the Apache Airflow Code Repository and have also write permission for GitHub resources (container registry, code repository). The main purpose for the run is to check if the code after merge still holds all the assertions - like whether it still builds, all tests are green. This is needed because some of the conflicting changes from multiple PRs might cause build and test failures after merge even if they do not fail in isolation. Also those runs are already reviewed and confirmed by the committers so they can be used to do some housekeeping - for now they are pushing most recent image build in the PR to the Github Private Registry - which is our image cache for all the builds. Another purpose of those runs is to refresh latest Python base images. Python base images are refreshed with varying frequency (once every few months usually but sometimes several times per week) with the latest security and bug fixes. Those patch level images releases can occasionally break Airflow builds (specifically Docker image builds based on those images) therefore in PRs we always use latest "good" python image that we store in the private GitHub cache. The direct push/master builds are not using registry cache to pull the python images - they are directly pulling the images from DockerHub, therefore they will try the latest images after they are released and in case they are fine, CI Docker image is build and tests are passing - those jobs will push the base images to the private GitHub Registry so that they be used by subsequent PR runs.
- Scheduled Run - those runs are results of (nightly) triggered job - only for
masterbranch. The main purpose of the job is to check if there was no impact of external dependency changes on the Apache Airflow code (for example transitive dependencies released that fail the build). It also checks if the Docker images can be build from the scratch (again - to see if some dependencies have not changed - for example downloaded package releases etc. Another reason for the nightly build is that the builds tags most recent master withnightly-mastertag so that DockerHub build can pick up the moved tag and prepare a nightly public master build in the DockerHub registry. Thev1-10-testbranch images are build in DockerHub when pushingv1-10-stablemanually.
All runs consist of the same jobs, but the jobs behave slightly differently or they are skipped in different run categories. Here is a summary of the run categories with regards of the jobs they are running. Those jobs often have matrix run strategy which runs several different variations of the jobs (with different Backend type / Python version, type of the tests to run for example)
| Job | Description | Pull Request Run | Direct Push/Merge Run |
|
|---|---|---|---|---|
| Static checks 1 | Performs first set of static checks | Yes | Yes | Yes * |
| Static checks 2 | Performs second set of static checks | Yes | Yes | Yes * |
| Docs | Builds documentation | Yes | Yes | Yes * |
| Build Prod Image | Builds production image | Yes | Yes | Yes * |
| Prepare Backport packages | Prepares Backport Packages for 1.10.* | Yes | Yes | Yes * |
| Pyfiles | Counts how many python files changed in the change.Used to determine if tests should be run | Yes | Yes (but it is not used) | Yes (but it is not used) |
| Tests | Run all the combinations of Pytest tests for Python code | Yes (if pyfiles count >0) | Yes | Yes* |
| Quarantined tests | Those are tests that are flaky and we need to fix them | Yes (if pyfiles count >0) | Yes | Yes * |
| Requirements | Checks if requirement constraints in the code are up-to-date | Yes (fails if missing requirement) | Yes (fails missing requirement) | Yes (Eager dependency upgrade - does not fail changed requirements) |
| Pull python from cache | Pulls Python base images from Github Private Image registry to keep the last good python image used in PRs | Yes | No | |
| Push python to cache | Pushes Python base images to Github Private Image registry - checks if latest image is fine and pushes if so | No | Yes | |
| Push Prod image | Pushes production images to GitHub Private Image Registry to cache the build images for following runs | Yes | ||
| Push CI image | Pushes CI images to GitHub Private Image Registry to cache the build images for following runs | Yes | ||
| Tag Repo nightly | Tags the repository with nightly tagIt is a lightweight tag that moves nightly | Yes. Triggers DockerHub build for public registry |