Best Practices for Apache Airflow

This page provides a guide to key best practices for efficient and reliable Apache Airflow deployment and operation.

Key Areas

• Data Sources: Plan data source connections meticulously. Use the correct types.
• DAGs: Design and maintain DAGs with clear dependencies and error handling. Use `try...except` blocks.
• Model Training: Utilize efficient data pipelines for training. Consider model deployment as a separate task.
• Monitoring & Alerting: Implement robust monitoring and alerting for critical tasks.
• Scalability: Design for scalability – consider sharding and parallel processing.
• Security: Prioritize security throughout the pipeline – authentication, authorization, and data encryption.
• Testing: Thoroughly test each stage of your pipeline with unit tests, integration tests, and end-to-end tests.