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AWS Compute Optimizer

AWS Compute Optimizer is a free AWS service that analyzes resource utilization metrics and recommends right-sized configurations for EC2 instances, Auto Scaling groups, EBS volumes, Lambda functions, and ECS services on Fargate.

How It Works

AWS Compute Optimizer uses machine learning to analyze CloudWatch metrics for your running resources. It looks at CPU, memory, storage, and network utilization over a lookback period and compares that usage against the performance profiles of available resource configurations. Based on that analysis, it generates recommendations in one of three categories: over-provisioned (you could downsize), under-provisioned (you risk performance issues), or optimized (current sizing is appropriate). You access recommendations through the AWS console, the AWS CLI, or the Compute Optimizer API, or you can export them to S3.

Why It Matters for Cloud Cost

Over-provisioned resources are a common source of wasted cloud spend. A team that provisions a large EC2 instance for a workload that only uses 10% of its CPU is paying for capacity it does not need. Compute Optimizer surfaces those mismatches so engineers and finance teams can act on them. Without a tool like this, right-sizing decisions rely on manual observation or periodic audits, which are slow and easy to skip. Following Compute Optimizer recommendations can reduce the cost of individual resources, though total savings depend on the specific workload and how consistently recommendations are applied.

Usage AI: Usage AI’s CoPilot surfaces commitment-layer recommendations alongside right-sizing context, so teams can act on both resource efficiency and pricing efficiency in the same workflow. See how Usage AI saves 30 to 50% on AWS, GCP, and Azure.

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