Managing Amazon Bedrock costs end to end: A playbook for FinOps and platform teams
According to AWS. AWS published an end-to-end cost management playbook detailing a five-stage operating model for Amazon Bedrock deployments.
- • Cost management for generative AI is a shared responsibility between application builders and cloud finance teams.
- • The five-stage operating model spans attribute, observe, enforce, optimize, and operate review cadences.
- • Amazon Bedrock automatically attributes inference costs to the IAM principal that made the call across all models.
- • Platform teams can utilize application inference profiles and projects for alternative attribution mechanisms.
Operating model overview
Cost management for generative AI functions as an architectural and operational discipline shared between application developers and cloud spend accountability teams. AWS presents a five-stage operating model run as a continuous loop: attribute every dollar to an owner, make every request observable, enforce budgets and restrictions, optimize platform defaults to eliminate waste, and operate a review cadence that converts data into decisions.
Granular cost attribution
Managing costs effectively relies on granular attribution, starting with Amazon Bedrock automatically attributing inference costs to the AWS Identity and Access Management principal that made the call across all models. Setup involves turning on IAM principal data in CUR 2.0 data exports, tagging IAM principals with business dimensions, configuring session names for federated access, and activating those tags in AWS Billing to track spend seamlessly.
- 1. aws.amazon.comOpen source