Amazon EMR on EKS adds managed and self-managed node groups support for managed endpoints
We are excited to announce the support for EKS clusters with both managed and self-managed node groups when using interactive Spark workloads via managed managed endpoints. Amazon EMR on EKS enables customers to run open-source big data frameworks such as Apache Spark on Amazon EKS. Amazon EMR on EKS customers setup and use a managed endpoint (available in preview) to run interactive workloads using integrated development environments (IDEs) such as EMR Studio.
We are excited to announce the support for EKS clusters with both managed and self-managed node groups when using interactive Spark workloads via managed managed endpoints. Amazon EMR on EKS enables customers to run open-source big data frameworks such as Apache Spark on Amazon EKS. Amazon EMR on EKS customers setup and use a managed endpoint (available in preview) to run interactive workloads using integrated development environments (IDEs) such as EMR Studio.
Until now, customers who had EKS clusters configured with self-managed node groups were unable to use EMR Studio with EMR on EKS. With this feature, customers using managed endpoints can now specify EKS clusters with managed or self-managed node groups to run their interactive workloads, with the added flexibility of defining aspects such as on-demand or spot instance types, and specify a custom AMI, among others.
To learn more about this feature, please visit our documentation. This feature is supported on Amazon EMR on EKS 6.10 release and above, and available in all regions where Amazon EMR on EKS is currently available.