Build a proactive AI cost management system for Amazon Bedrock – Part 2

In Part 1 of our series, we introduced a proactive cost management solution for Amazon Bedrock, featuring a robust cost sentry mechanism designed to enforce real-time token usage limits. We explored the core architecture, token tracking strategies, and initial budget enforcement techniques that help organizations control their generative AI expenses.

Building upon that foundation, this post explores advanced cost monitoring strategies for generative AI deployments. We introduce granular custom tagging approaches for precise cost allocation, and develop comprehensive reporting mechanisms.

Solution overview

The cost sentry solution introduced in Part 1 was developed as a centralized mechanism to proactively limit generative AI usage to adhere to prescribed budgets. The following diagram illustrates the core components of the solution, adding in cost monitoring through AWS Billing and Cost Management.

Invocation-level tagging for enhanced traceability

Invocation-level tagging extends our solution’s capabilities by attaching rich metadata to every API request, creating a comprehensive ...