Ruiter-HI1200×1505 93.3 KB

Julian de Ruiter, Ismael Cabral, Kris Geusebroek, Daniel van der Ende, Bas Harenslak

Data Pipelines with Apache Airflow, Second Edition, is fully revised for Airflow 3 and digs into the features and patterns engineers are dealing with today: the Taskflow API, deferrable operators, event-driven scheduling, dynamic task mapping, DAG versioning, and the updated UI.

The book starts from the foundations — how Airflow actually works, how to think about workflow design, how scheduling really behaves — and then moves into the problems teams run into in production. You’ll see practical discussions of irregular schedules with the Dataset API and timetables, building custom components, testing strategies, and operating Airflow in container-native environments.

What makes this edition especially interesting is the expanded coverage of AI-related workflows. The examples walk through orchestrating machine learning tasks, working with LLM-driven systems, and building pipelines that go beyond traditional ETL use cases.

Rather than presenting isolated snippets, the material follows realistic scenarios: data ingestion, transformations across multiple systems, performance considerations, deployment decisions, and long-term maintenance concerns. The goal is to help readers develop intuition about why Airflow behaves the way it does, not just which knobs to turn.

• * Full details: Data Pipelines with Apache Airflow, Second Edition - Julian de Ruiter at all.

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