The Airflow 2.9 release brings significant enhancements to user-favorite features like data-aware scheduling, dynamic task mapping, and object storage.
Our beta cohort of 10 is now joined by 23 hand-selected individuals who, we believe, truly embody what it means to champion the Apache Airflow Project.
A breakdown of the major features incorporated in Apache Airflow 2.0, including a refactored, highly-available Scheduler, over 30 UI/UX improvements, a new REST API and much more.
Using KEDA (Kubernetes Event-Driven Autoscaler), we've developed a robust method to scale Apache Airflow workers to be faster and more versatile than any previous architecture.
Tasks not running? DAG stuck? Logs nowhere to be found? We’ve been there. Here’s a list of common snags and some corresponding fixes to consider when you’re debugging your Airflow deployment.