What changed
AWS has released a detailed playbook for managing costs associated with Amazon Bedrock, focusing on cost attribution, observability, and optimization. The guide outlines a five-stage operating model designed to help FinOps teams and platform engineers track and control spending effectively.
What this means in practice
The playbook emphasizes that cost management for generative AI is a shared responsibility between application teams and cloud spend accountability teams. It highlights the importance of granular cost attribution, which is automatically handled by Amazon Bedrock through IAM principals. This allows for detailed tracking of costs down to the user, team, and application level.
The guide also addresses the 'shared-role problem,' where a single IAM role can lead to loss of per-user visibility. The solution involves per-user session management, where the gateway assumes the Amazon Bedrock invocation role once per user, passing the user's identity and attributes as session tags. This ensures per-user and per-tenant attribution even behind a shared gateway.
For bedrock-runtime workloads, AWS recommends using IAM principal attribution through session tags as the primary mechanism. This approach scales with the identity system and requires no pre-created resources. Application inference profiles are suggested for teams with a small and stable set of applications and models, while projects are recommended for bedrock-mantle workloads using the Responses API or Chat Completions API.
Limitations and availability
The playbook is designed for FinOps practitioners and platform engineering teams. It is based on AWS building blocks and can be customized for different environments. The guide does not specify any particular hardware requirements or license conditions. The approach is built on AWS services and is available to all users with access to Amazon Bedrock. The supplied announcement does not specify any particular release date or availability timeline for the playbook itself.
