This post, the second part of a series on the AWS Machine Learning Blog, describes how to attribute and analyze Amazon Bedrock costs using Amazon Athena and CUDOS dashboards. It walks through setting up CUR 2.0 with IAM principal data, querying Bedrock spend by principal, project, and team, and constructing dashboards to monitor AI-related costs across an organization.
Why it matters
As organizations adopt AI services, understanding where spend originates becomes important for financial oversight. Attributing Bedrock costs to specific principals, projects, and teams gives organizations visibility into how AI budgets are consumed.
Who should care
Teams managing Amazon Bedrock usage, along with those responsible for cloud cost tracking and reporting, will find the described setup and querying approach relevant.