Apache Airflow’s Kubernetes integration enables flexible workload execution on Kubernetes but lacks advanced resource management features including application queueing, tenant isolation and gang scheduling. These features are increasingly critical for data engineering as well as AI/ML use cases, particularly GPU utilization optimization. Apache Yunikorn, a Kubernetes-native scheduler, addresses these gaps by offering a high-performance alternative to Kubernetes default scheduler. In this talk, we’ll demonstrate how to conveniently leverage Yunikorn’s power in Airflow, along with practical use cases and examples.

Xiaodong Deng

Apache Airflow PMC member & Committer; Software Engineer at Apple

Chaoran Yu

Engineering Manager, Apple