Airflow 3 brings several exciting new features that better support MLOps: Native, intuitive backfills Removal of the unique execution date for dag runs Native support for event-driven scheduling These features, combined with the Airflow AI SDK, enable dag authors to easily build scalable, maintainable, and performant LLMOps pipelines. In this talk, we’ll go through a series of workflows that use the Airflow AI SDK to empower Astronomer’s support staff to more quickly resolve problems faced by Astronomer’s customers.

Much of the world sees Airflow as a hammer and ETL tasks as nails, but in reality, Airflow is much more of a sophisticated multitool, capable of orchestrating a wide variety of complex workflows. Astronomer’s Customer Reliability Engineering (CRE) team is leveraging this potential in its development of Airline, a tool powered by Airflow that monitors Airflow deployments and sends alerts proactively when issues arise. In this talk, Ryan Hatter from Astronomer will give an overview of Airline. He’ll explain how it integrates with ZenDesk, Kubernetes, and other services to resolve customers’ problems more quickly, and in many cases, even before customers realize there’s an issue. Join us for a practical exploration of Airflow’s capabilities beyond ETL, and learn how proactive, automated monitoring can enhance your operations.