How Are You Using Airflow Outside Data Pipelines?

We started using Apache Airflow for repetitive DevOps workflows, not just data pipelines.

Some of the workflows we automated:

GitHub token validation
Kubernetes kubeconfig checks
GitHub secret updates
AWS cost monitoring
Slack notifications

The useful part is having scheduling, retries, dependencies, and visibility around these workflows instead of managing everything with separate scripts and cron jobs.

I wrote about the workflows, implementation, and lessons from using Airflow for these DevOps tasks.

How we use Apache Airflow to optimise our DevOps workflow

See how we use Apache Airflow to automate DevOps workflows, manage secrets, and reduce manual tasks with real-world examples.

kubeblogs.com

Have you used Airflow for DevOps automation? What did you automate first?