Organizations running machine learning (ML), analytics, and generative AI workloads on Amazon SageMaker Unified Studio domains and projects face a common cost governance challenge. System tags (AmazonDataZoneDomainId and AmazonDataZoneProject) are automatically propagated to all underlying project resources. However, custom tags such as CostCenter, Team, or Environment are not propagated to dynamic resources created through the Studio UI. This creates a gap when you need to report project costs grouped by custom tags.
In this post, we walk through a serverless solution that bridges this gap by enriching AWS Cost and Usage Report (CUR) data with custom project tags. By the end of this post, you can build an Amazon Quick Sight dashboard to filter and analyze Amazon SageMaker Unified Studio project costs by any custom tag dimension that you define. This gives your team the visibility to make informed spending decisions.
Solution overview
The solution…
