Managed Airflow: MWAA and Cloud Composer

Architecture Diagram

Formal Definitions

Detailed Explanation

Managed Airflow Services

Managed Airflow services handle infrastructure management while you focus on DAG development. The three major providers are AWS MWAA, Google Cloud Composer, and Azure Managed Apache Airflow.

Key Insight: Managed services reduce operational overhead but you're still responsible for writing idempotent, well-tested DAGs.

Service Comparison

When to Use Managed vs Self-Managed

MWAA Setup

Cloud Composer Setup

MWAA DAG with S3 Storage

Service Comparison

Scaling Thresholds

Best Practices

Security

1. Use managed secrets: Leverage AWS Secrets Manager, GCP Secret Manager, or Azure Key Vault instead of environment variables for sensitive data.
2. Enable VPC peering: Run MWAA/Composer in private subnets with VPC peering for secure database and storage access.

Scaling and Performance

1. Monitor worker utilization: Scale workers based on task queue depth and execution time, not just DAG count.
2. Use Airflow variables for environment-specific configuration — avoid hardcoding in DAG files.
3. Optimize parse time: Use dynamic DAG generation and minimize imports at module level.

Operations

1. Implement CI/CD: Use S3 sync, GCS sync, or Git-based deployment for DAG updates.
2. Enable logging: Configure all log types (scheduler, task, webserver) for debugging.
3. Test upgrades: Use staging environments to test Airflow version upgrades before production.

Cost Optimization

See Also

• Airflow Architecture — Core architecture and component overview
• Executors Comparison — Sequential, Local, Celery, and Kubernetes executors
• Databricks Provider — Databricks cluster and job management
• BigQuery Provider — Google BigQuery integration patterns