Airflow Dag Patterns

If you're building data pipelines in Airflow, this gives you production patterns for DAG design, custom operators, sensors, and testing strategies. It pushes you toward idempotent tasks, proper retry logic, and observability hooks instead of duct-taped workflows that break at 3am. The implementation playbook covers detailed patterns and checklists you can actually follow. Honestly, most Airflow pain comes from skipping fundamentals like backfill testing and clear task ownership, so having a structured approach here saves you from learning those lessons the hard way. It won't help if you're just scheduling a simple cron job, but for orchestrating real data workflows, it's a solid foundation.