Apache Airflow Best Practices
A practical guide to orchestrating data workflow with Apache Airflow
Created by Dylan Intorf, Kendrick van Doorn, Dylan Storey
Master the essentials and advanced features of Apache Airflow 2.x to streamline your data workflows. Learn practical techniques for building, scaling, and managing complex data pipelines across diverse environments. Gain confidence in orchestrating reliable, production-ready workflows for your organization.
Packt | Oct 2024 | 188 min
What You Will Learn
You will work through practical, real-world examples that demonstrate how to design, implement, and scale data workflows using Apache Airflow. By exploring end-to-end use cases and operational scenarios, you will gain hands-on experience that prepares you for real production challenges. Guidance is provided for both technical contributors and team leads.
Key Features
- Build and manage scalable data pipelines using Apache Airflow DAGs
- Optimize and monitor workflows for high availability and operational resilience
- Deploy and maintain Airflow in cloud environments with best practices
Target Audience
This content is designed for data engineers, developers, IT professionals, and data scientists who want to orchestrate data workflows more efficiently. If you have a working knowledge of Python and some experience with DevOps or business processes, you'll benefit most. Prior Airflow experience is helpful but not required, making it suitable for both newcomers and those looking to deepen their expertise.
