As part of my role at Google, maintaining samples for Cloud Composer, hosted managed Airflow, is crucial. It’s not feasible for me to try out every sample every day to check that it’s working. So, how do I do it? Automation! While I won’t let the robots touch everything, they let me know when it’s time to pay attention. Here’s how: Step 0: An update for the operators is released Step 1: A GitHub bot called Renovate Bot opens up a PR to a special requirements file to make this update Step 2: Cloud build runs unit tests to make sure none of my DAGs immediately break Step 3: PR is approved and merged to main Step 4: Cloud Build updates my dev environment Step 5: I look at my DAGs in dev to make sure all is well. If there is a problem, I need to resolve it manually and revert my requirements file. Step 6: I manually update my prod PyPI packages I’ll discuss what automation tools I choose to use and why, and the places where I intentionally leave manual steps to ensure proper oversight.

Rachael, a new Airflow contributor, and Leah, an experienced Airflow contributor, share the story of Rachael’s first contribution, highlighting the importance of contributions from new users and the positive impact that non-code contributions have in an open source community.