# Amazon EMR on EKS in Amazon SageMaker Unified Studio Amazon EMR on EKS You can connect to Amazon EMR on EKS in Amazon SageMaker Unified Studio. Amazon EMR on EKS allows you to run open-source big data frameworks on Amazon EKS. With Amazon EMR on EKS, you can focus on running analytics workloads while Amazon EMR on EKS builds, configures, and manages containers for open-source applications. Amazon EMR on EKS virtual clusters require an Amazon EKS cluster with compatible configurations. Amazon EMR on EKS operates by creating an Amazon EMR on EKS virtual cluster on top of your existing Amazon EKS cluster. You then interact with the Amazon EMR on EKS virtual cluster directly for interactive session management. For more information, see [What is Amazon EMR on EKS?](https://docs.aws.amazon.com/emr/latest/EMR-on-EKS-DevelopmentGuide/emr-eks.html) ## Spark History Server for Amazon EMR on EKS in Amazon SageMaker Unified Studio You can use the Spark History Server in a notebook session to view details such as tasks, executors and logs about Spark queries. You can explore the Spark History Server for an active Amazon EMR on EKS interactive session. To do this, navigate to your project's JupyterLab IDE and select your Amazon EMR on EKS connection. After any Spark query is executed, choose the **Spark History Server** embedded link. # Adding a new Amazon EMR on EKS virtual cluster in Amazon SageMaker Unified Studio Adding a new Amazon EMR on EKS virtual cluster As a data worker, you can make use of Amazon EMR on EKS by adding new Amazon EMR on EKS virtual clusters as compute instances to a Amazon SageMaker Unified Studio project. However, in order to create new Amazon EMR on EKS virtual clusters, your admin must enable and configure blueprints. After your admin has enabled and configured blueprints: 1. From inside the project management view, select **Compute** from the navigation bar. 1. In the Compute panel, select the **Data processing** tab. 1. To create a new Amazon EMR on EKS virtual cluster, select the **Add compute** dropdown menu and then choose **New compute**. 1. In the **Add compute** modal, you can select the type of compute you would like to add to your project. Select **Create new compute resources**. 1. Select **Amazon EMR on EKS virtual cluster**. 1. The **Add compute** dialog box allows you to select your admin created Amazon EKS cluster configuration, specify the name of the Amazon EMR on EKS virtual cluster, provide a description, and choose a release of Amazon EMR (such as EMR 7.11.0-latest) that you want to install on your managed endpoint. 1. After configuring these settings, select **Add compute**. After some time, your Amazon EMR on EKS virtual cluster will be added to your project. # Using an Amazon EMR on EKS virtual cluster in Amazon SageMaker Unified Studio Using an Amazon EMR on EKS virtual cluster After creating your Amazon EMR on EKS virtual cluster, you can begin using your compute. **Note** Amazon EMR on EKS in Amazon SageMaker Unified Studio is only available for SageMaker distributions >=2.10 and >=3.5. 1. From inside the project management view, select **Compute** from the navigation bar. 1. In the Compute panel, select the **Data processing** tab. 1. In the data processing panel, select your target Amazon EMR on EKS virtual cluster. 1. In the compute details panel, select **Actions** and **Open JupyterLab IDE**. 1. In the JupyterLab IDE, select a compatible **Connection type** and select the name of the **Compute**. ## Configuration for additional functionality in Amazon SageMaker Unified Studio Some native Amazon EMR on EKS functionality requires additional configuration by your administrator for your Amazon SageMaker Unified Studio projects. Contact your administrator to review documentation for additional functionality. + [ Configuring monitoring with Spark History Server for Amazon EMR on EKS ](https://docs.aws.amazon.com/sagemaker-unified-studio/latest/adminguide/configuring-monitoring-with-spark-history-server-for-emr-on-eks.html) + [ Configuring fine-grained access controls for Amazon EMR on EKS ](https://docs.aws.amazon.com/sagemaker-unified-studio/latest/adminguide/configuring-fine-grained-access-controls-for-emr-on-eks.html) + [ Configuring trusted identity propagation for Amazon EMR on EKS ](https://docs.aws.amazon.com/sagemaker-unified-studio/latest/adminguide/configuring-trusted-identity-propagation-for-emr-on-eks.html) + [ Configuring user background sessions for Amazon EMR on EKS ](https://docs.aws.amazon.com/sagemaker-unified-studio/latest/adminguide/configuring-user-background-sessions-for-emr-on-eks.html) # Removing an Amazon EMR on EKS virtual cluster in Amazon SageMaker Unified Studio Removing an Amazon EMR on EKS virtual cluster When you no longer need an Amazon EMR on EKS virtual cluster, the Amazon EMR on EKS resources can be deleted. **Note** The Amazon EKS cluster used to create Amazon EMR on EKS resources is never deleted by SageMaker. 1. From inside the project management view, select **Compute** from the navigation bar. 1. In the Compute panel, select the **Data processing** tab. 1. In the data processing panel, select your target Amazon EMR on EKS virtual cluster. 1. In the compute details panel, select **Actions** and **Remove compute**. 1. In the confirmation modal, select **Remove compute**. 1. After a short time, your Amazon EMR on EKS virtual cluster will be removed.