10 Best Practices for Modern Data Orchestration with Airflow

This article outlines 10 best practices for modern data orchestration using Apache Airflow. Standardizing production and development environments, getting current and keeping current, designing DAGs to take advantage of Airflow's built-in parallel processing, pushing workload processing "out" closer to where the data lives, designing Airflow environments for micro-orchestration, maximizing reuse and reproducibility, integrating Airflow with CI/CD tools and processes, using Airflow's Taskflow API to move data between tasks, and focusing on observability and modern data orchestration are key components. By following these best practices, organizations can create a sustainable enterprise data integration ecosystem that accelerates the flow of trusted data across their organization.

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