Starting with an introduction to data orchestration and the significant updates in Apache Airflow 2.0, this book takes you through the essentials of DAG authoring, managing Airflow components, and connecting to external data sources. Through real-world use cases, you'll gain practical insights into implementing ETL pipelines and machine learning workflows in your environment. You'll also learn how to deploy Airflow in cloud environments, tackle operational considerations for scaling, and apply best practices for CI/CD and monitoring.
By the end of this book, you'll be proficient in operating and using Apache Airflow, authoring high-quality workflows in Python for your specific use cases, and making informed decisions crucial for production-ready implementation.
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