In Apache Airflow®, data pipelines are defined as Directed Acyclic Graphs (DAGs) which represent dependencies between individual tasks in a workflow and can be scheduled to run automatically based on conditions such as at certain times and updates to datasets. With Airflow being the open-source standard for workflow orchestration, knowing how to write Airflow DAGs has become an essential skill for every data engineer.

This eBook provides a comprehensive overview of DAG writing features with plenty of example code. You’ll learn how to:

• Understand the building blocks DAGs, combine them in complex pipelines, and schedule your DAG to run exactly when you want it to
• Write DAGs that adapt to your data at runtime and set up alerts and notifications
• Scale your Airflow environment
• Systematically test and debug Airflow DAGs

By the end of this guide, you’ll know how to create and manage reliable, complex DAGs using advanced Airflow features.