Split Cost Allocation for Amazon EKS with GPU Support

Starting today, Split Cost Allocation Data now adds support for accelerated-computing workloads running in the Amazon Elastic Kubernetes Service (EKS). The new feature in Split Cost Allocation Data for EKS allows customers to track the costs associated with accelerator-powered (Trainium, Inferentia, NVIDIA and AMD GPUs) container-level resources within their EKS clusters, in addition to the costs for CPU and Memory. This cost data is available in the AWS Cost and Usage Report, including CUR 2.0.

With this new capability, customers get greater visibility over their AI/ML cloud infrastructure expenses. Customers can now allocate application costs to individual business units and teams based on the CPU, memory and accelerator resource reservations of their containerized accelerated-computing workloads. New Split Cost Allocation Data customers can enable this feature in the AWS Billing and Cost Management console. This feature is automatically enabled for existing Split Cost Allocation Data customers. You can use the Containers Cost Allocation dashboard to visualize the costs in Amazon QuickSight and the CUR query library to query the costs using Amazon Athena.

This feature is available in all AWS Regions where Split Cost Allocation Data for Amazon EKS is available. To get started, visit Understanding Split Cost Allocation Data and Improve cost visibility of Machine Learning workloads on Amazon EKS with AWS Split Cost Allocation Data.

Categories: general:products/amazon-eks

Source: Amazon Web Services