Posted On: May 11, 2021
Starting today, HAQM EMR on HAQM EKS is now available in the EU (Paris and Stockholm) region.
HAQM EMR on EKS allows customers to automate the provisioning and management of open-source big data frameworks on HAQM EKS. With EMR on EKS, customers can now run Spark applications alongside other types of applications on the same EKS cluster to improve resource utilization and simplify infrastructure management. Customers can deploy EMR applications on the same EKS cluster as other types of applications, which allows them to share resources and standardize on a single solution for operating and managing all their applications. Customers get access to the same EMR capabilities on EKS that they use on HAQM EC2 today, such as access to the latest performance optimized Spark runtime, EMR Studio (preview) for application development, and a persistent Spark UI for debugging.
To get started, register your EKS cluster with HAQM EMR. Then define your job including EMR release version, Spark parameters, and application dependencies. HAQM EMR on HAQM EKS will schedule the pods, containers, and resources onto your HAQM EKS cluster. You can configure your job to run on HAQM EC2 instances, or HAQM Fargate if you want a serverless experience. You can create workflows with HAQM Managed Workflows for Apache Airflow and analyze output with per job logs stored in HAQM S3 or HAQM CloudWatch.
For more information on HAQM on EKS please visit our HAQM on EKS Launch Blog, our HAQM EMR on EKS documentation or view our deep-dive tech talk on HAQM EMR on EKS.