Scaling Ray Train to 10,000 Kubernetes Nodes on GKE
Learn how Google achieved unprecedented scaling of Ray Train and Ray Data across 10,000 Kubernetes nodes in GKE during this conference talk from Ray Summit 2024. Explore the architectural innovations and technical breakthroughs that enabled massive-scale distributed computing, as speakers Andrew Sy Kim and Saikat Roychowdhury detail the integration between KubeRay and Kubernetes enhancements. Discover the critical role of GKE's GCS Fuse CSI driver in facilitating distributed checkpointing and dataset processing at scale. Master practical insights for scaling distributed machine learning infrastructure, whether working with modest clusters or massive deployments. Gain valuable knowledge about managing enormous distributed workloads and pushing the boundaries of AI model training capabilities through efficient compute cluster scaling.