Manage AI Costs with Amazon Bedrock Projects
This article explains how to use Amazon Bedrock Projects to attribute and analyze inference costs for AI workloads in AWS Cost Explorer and AWS Data Exports.
Why it matters
Effectively managing the costs of AI infrastructure and inference is crucial as enterprises scale their AI adoption.
Key Points
- 1Amazon Bedrock Projects allow you to attribute inference costs to specific AI workloads
- 2You can set up a tagging strategy to track costs for different AI projects or use cases
- 3The cost data can be analyzed in AWS Cost Explorer and AWS Data Exports
Details
Amazon Bedrock Projects is a feature that enables you to attribute the costs of AI inference workloads to specific projects or use cases. This allows you to better understand and manage the costs associated with running your AI models in production. By setting up a tagging strategy, you can track costs for different AI initiatives, such as separate projects, teams, or applications. The cost data can then be analyzed in AWS Cost Explorer and AWS Data Exports, providing visibility into the expenses related to your AI workloads. This can help optimize budgets, identify cost-saving opportunities, and make more informed decisions about your AI investments.
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