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AWS outlines a five-stage operating model for managing Amazon Bedrock generative AI costs: attribute spend to IAM principals, log requests with metadata, enforce budgets, optimize platform defaults, and run a review cadence. The playbook covers per-user attribution behind shared gateways, invocation logging with CloudWatch and S3/Athena, and three enforcement tiers ranging from alerts to synchronous gateway blocking. It also details model routing and prompt caching as central cost levers, with diagnostic queries for token usage by caller and workload.
Why it matters: It gives FinOps and platform teams a concrete, implementation-oriented framework for attributing, observing, and controlling Bedrock spend as agentic workloads increase token consumption.
Amazon BedrockFinOpsAI cost governance