- Who
- AWS
- What
- explains how to configure per-user cost attribution and usage controls for AI developer and productivity tools on Amazon Bedrock
- Quote
This post shows you how to use these capabilities to answer three questions that every FinOps and AI Platform leader asks as AI tool adoption scales: What is the real per-user cost?
What happened
AWS authors explain how to track per-user costs for AI coding and productivity tools that route inference through Amazon Bedrock. The guide configures IAM Identity Center session identities and tags for CUR 2.0, then covers Athena queries and dashboard options. It also compares spending controls, including AWS Budgets, CloudWatch alarms with Lambda, DynamoDB quotas, and LLM gateways.
Read next
See the full storyAWS Details Cost Attribution and Spending Controls for AI Tools on Amazon BedrockThe story so far
AWS explains how to attribute Amazon Bedrock inference costs to individual users of AI coding and productivity tools, then compare ways to control their usage. The guide configures IAM Identity Center session identities and tags for CUR 2.0 reporting, with Athena queries and dashboard options for analyzing per-user costs. It also compares AWS Budgets, CloudWatch alarms with Lambda, DynamoDB quotas, and LLM gateways as spending controls. AWS’s earlier walkthrough covers tracking Bedrock costs by IAM user or role with cost allocation tags, Cost Explorer or CUR 2.0, and AWS Budgets actions that attach a Deny policy. Budgets refresh up to three times a day, so spending can exceed a threshold before an action runs. Newly applied cost allocation tags can take up to 24 hours to appear and another 24 hours after activation to populate billing data. A Deny policy on a shared role blocks everyone using that role.