Amazon SageMaker Unified Studio announces single sign-on support for interactive Spark sessions

Amazon SageMaker Unified Studio announces corporate identity support for interactive Apache Spark sessions through AWS Identity Center’s trusted identity propagation. This new capability enables seamless single sign-on and end-to-end data access traceability for data analytics workflows. Data engineers and scientists can now access data resources in Apache Spark sessions in their JupyterLab environment using their organizational identities, while administrators can implement fine-grained access controls and maintain comprehensive audit trails.

For data administrators, this feature simplifies security management using AWS Lake Formation, Amazon S3 Access Grants, and Amazon Redshift Data APIs, enabling centralized access controls across Amazon EMR on EC2, EMR on EKS, EMR Serverless, and AWS Glue. Organizations can define granular permissions based on identity provider credentials for Spark sessions and SageMaker Studio notebook flows, including training and processing jobs. This integration is complemented by comprehensive AWS CloudTrail logging of all user activities—from interactive JupyterLab sessions to user background sessions - streamlining compliance monitoring and audit requirements.

Identity support for Spark sessions in SageMaker Unified Studio is available in the following AWS Regions: US East (N. Virginia), US East (Ohio), US West (Oregon), Canada (Central), South America (São Paulo), Europe (Ireland), Europe (Frankfurt), Europe (London), Europe (Paris), Europe (Stockholm), Asia Pacific (Mumbai), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Seoul), and Asia Pacific (Tokyo).

To learn more, visit the SageMaker Unified Studio documentation.