EMR Studio provides fully managed Jupyter notebooks, and tools like Spark UI and YARN Timeline Service to simplify debugging. EMR Studio uses AWS Single Sign-On and allows you to log in directly with your corporate credentials without signing in to the AWS Management Console. You can install custom kernels and libraries, collaborate with peers using code repositories such as GitHub and Bitbucket, and run parameterized notebooks as part of scheduled workflows using orchestration services like Apache Airflow and Amazon Managed Workflows for Apache Airflow (Amazon MWAA).
With EMR Studio, you can run notebook code on Amazon EMR on Amazon Elastic Compute Cloud (Amazon EC2) or Amazon EMR on Amazon Elastic Kubernetes Service (Amazon EKS), and take advantage of the performance-optimized EMR runtime for Apache Spark. You can set up EMR Studio to run applications on existing EMR clusters or create new clusters using Cloud Formation templates for Amazon EMR.
Click through for more information.