airflow-dag-patterns

• Creating data pipeline orchestration with Airflow
• Designing DAG structures and dependencies
• Implementing custom operators and sensors
• Testing Airflow DAGs locally
• Setting up Airflow in production
• Debugging failed DAG runs

• You only need a simple cron job or shell script
• Airflow is not part of the tooling stack
• The task is unrelated to workflow orchestration

1. Identify data sources, schedules, and dependencies.
2. Design idempotent tasks with clear ownership and retries.
3. Implement DAGs with observability and alerting hooks.
4. Validate in staging and document operational runbooks.

Refer to resources/implementation-playbook.md for detailed patterns, checklists, and templates.

• Avoid changing production DAG schedules without approval.
• Test backfills and retries carefully to prevent data duplication.

• resources/implementation-playbook.md for detailed patterns, checklists, and templates.