Data professionals face the monumental task of managing complex data pipelines, orchestrating workflows across diverse systems, and ensuring scalable, reliable data processing. This definitive guide to mastering Apache Airflow, written by experts in engineering, data strategy, and problem-solving across tech, financial, and life sciences industries, is your key to overcoming these challenges. It covers everything from the basics of Airflow and its core components to advanced topics such as custom plugin development, multi-tenancy, and cloud deployment.
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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Spis treści

Apache Airflow Best Practices. A practical guide to orchestrating data workflow with Apache Airflow eBook -- spis treści

• 1. Getting Started with Airflow 2.0
• 2. Core Airflow Concepts
• 3. Components of Airflow
• 4. Basics of Airflow and DAG Authoring
• 5. Connecting to External Sources
• 6. Extending Functionality with UI Plugins
• 7. Writing and Distributing Custom Providers
• 8. Orchestrating a Machine Learning Workflow
• 9. Using Airflow as a Driving Service
• 10. Airflow Ops: Development and Deployment
• 11. Airflow Ops Best Practices: Observation and Monitoring
• 12. Multi-Tenancy in Airflow
• 13. Migrating Airflow