Best Practices for Running and Managing Apache Airflow® at Scale

Leading companies like Stripe, Uber and OpenAI rely on Airflow to orchestrate hundreds of thousands of tasks every day. But, scaling multiple Airflow deployments effectively requires more than just standing it up.

Resource management, workflow development, and observability are becoming essential to preventing instability, downtime, and unnecessary cost.

This eBook provides practical, hands-on guidance with real code examples to help you confidently scale Airflow in production environments.

You’ll learn best practices for:

• Setting up your Airflow architecture and tuning key configurations
• Optimizing Dag code, including using dynamic tasks and task groups
• Monitoring and troubleshooting your Airflow environment with built-in and external tools

This eBook is written for Platform Engineers, Data Engineers, and anyone responsible for ensuring your Airflow workflows are fast, reliable, and efficient at scale.

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