Amazon EMR Serverless adds support for job run level cost allocation

Amazon EMR Serverless now supports job run-level cost allocation that provides better visibility into charges for individual job runs by allowing you to configure granular billing attribution at the individual job run level. You can get granular cost visibility by filtering and tracking costs in AWS Cost Explorer and Cost and Usage Reports by specific job run IDs and cost allocation tags associated with job runs.

Amazon EMR Serverless is a deployment option in Amazon EMR that makes it simple for data engineers and data scientists to run open-source big data analytics frameworks without configuring, managing, and scaling clusters or servers. Previously, you could assign cost allocation tags to EMR Serverless applications, with cost attribution limited to the application level. With job run-level cost allocation, now you can assign cost allocation tags to each job run, enabling fine-grained billing attribution at the individual job run level. Cost allocation tags at the job run level also allow you to track costs by domains within a single application. For example, a single application could support jobs for finance and marketing domains, allowing you to track costs separately for each domain. Tracking costs for individual job runs makes it easier to conduct benchmarks that assess the costs of each job run as well as focus cost optimization efforts more precisely, allowing deeper insights into resource utilization and spending patterns across different jobs and domains.

This feature is available in all AWS Regions where Amazon EMR Serverless is available including AWS GovCloud (US) and China regions. To learn more, see Enabling Job Level Cost Allocation in the Amazon EMR Serverless User Guide