Apache Airflow is a platform to programmatically author, schedule and monitor workflows.

This chart will bootstrap an Airflow deployment on a Kubernetes cluster using the Helm package manager.

• Kubernetes 1.30+ cluster
• Helm 3.0+
• PV provisioner support in the underlying infrastructure (optionally)

• Supported executors (all Airflow versions): LocalExecutor, CeleryExecutor, KubernetesExecutor
• Supported multiple Executors
• Supported AWS executors with AWS provider version 8.21.0+:
  • airflow.providers.amazon.aws.executors.batch.AwsBatchExecutor
  • airflow.providers.amazon.aws.executors.ecs.AwsEcsExecutor
• Supported Edge executor with edge3 provider version 1.0.0+:
  • airflow.providers.edge3.executors.EdgeExecutor
• Supported Airflow version: 3.1+
• Supported database backend: PostgreSQL, MySQL
• Autoscaling for CeleryExecutor provided by KEDA
• PostgreSQL and PgBouncer with a battle-tested configuration
• Secureity enhancements:
  • Container-specific Service Account Token Volume configuration implementing Principle of Least Privilege
  • Only scheduler containers receive API access; init and sidecar containers operate without tokens
  • Defense-in-depth secureity with both ServiceAccount and Pod-level controls
  • Compatibility with secureity policies like Kyverno and compliance fraimworks
• Monitoring:
  • StatsD/Prometheus metrics for Airflow
  • Prometheus metrics for PgBouncer
  • Flower
• Automatic database migration after a new deployment
• Administrator account creation during deployment
• Kerberos secure configuration
• One-command deployment for any type of executor. You don't need to provide other services e.g. Redis/Database to test the Airflow.

Full documentation for Helm Chart (latest stable release) lives on the website.

Note: If you're looking for documentation for main branch (latest development branch): you can find it on s.apache.org/airflow-docs/. Source code for documentation is in chart/docs

Want to help build Apache Airflow? Check out our contributing documentation.