Ray Data on EKS Stack
Production-ready Ray Data for scalable ML and data processing on Amazon EKS. Deploy distributed Python workloads with Ray's unified compute framework.
Getting Started
1
Deploy Infrastructure
Start with the infrastructure deployment guide to set up Ray cluster on EKS
2
Submit Ray Jobs
Deploy distributed ML training or data processing workloads
3
Scale Workloads
Leverage Ray autoscaling for efficient resource utilization
4
Monitor Performance
Use Ray Dashboard and metrics for observability
Infrastructure Deployment
Complete infrastructure deployment guide for Ray Data on EKS with KubeRay operator and distributed computing setup
Spark Logs Processing with Ray Data
Process Spark application logs from S3 and store in Apache Iceberg format using Ray Data for scalable data transformation