AWS Compute Optimizer
AWS Compute Optimizer
AWS Compute Optimizer API analyzes historical EC2/EBS/Lambda/ECS usage and recommends better instance types/configs for cost savings or performance gains.
Based on at least 14 days of CloudWatch data — recommendations are data-grounded
Recommendations consider only historical load, not business seasonality
Enable Compute Optimizer in AWS Console (one-time opt-in). Wait 14 days for recommendations. GetEC2InstanceRecommendations for details.
Uptime · 30-day window
GitHub activity
About this API
AWS resource waste is widespread in enterprises — running m5.4xlarge with 5% average CPU, Lambda configured at 1GB but P99 uses 100MB, EBS volume IOPS overprovisioned but actual usage 10%. Compute Optimizer uses machine learning on CloudWatch history to tell you "this EC2 can drop to m5.large saving 75%", "this Lambda memory can go from 1GB to 256MB", "this EBS can move from gp3 to gp2". Each recommendation includes expected savings and performance impact. Saves 20-40% of AWS spend for large enterprises. Free to use; only cost is enabling CloudWatch detailed monitoring (some metrics required).
What you can build
- 1EC2 rightsizing (wasted spend from wrong instance type)
- 2Lambda memory configuration optimization
- 3EBS volume type/IOPS optimization
- 4Identify idle resources for downsizing
Strengths & limitations
Strengths
- Based on at least 14 days of CloudWatch data — recommendations are data-grounded
- Free (recommendations are free; only implementation costs)
- Distinguishes "cost savings" vs "performance" optimization
Limitations
- Recommendations consider only historical load, not business seasonality
- EC2 type recommendations may not account for existing Reserved Instance commitments
Example request
curl https://github.com/mermade/aws2openapi/<endpoint>Getting started
Enable Compute Optimizer in AWS Console (one-time opt-in). Wait 14 days for recommendations. GetEC2InstanceRecommendations for details.
FAQ
How accurate are the recommendations?+
Based on 14 days of data — accurate for steady-state load. Spiky load (e.g. end-of-quarter peaks) may produce overly aggressive recommendations — human review needed.
Cost Explorer vs. Compute Optimizer?+
Cost Explorer: how much you spent. Compute Optimizer: how to spend less (specific resource-level recommendations).
Technical details
- Auth type
- unknown
- Pricing
- unknown
- Protocols
- REST
- SDKs
- python, javascript, go, java, csharp
- Response time
- 20 ms
- Last health check
- 5/12/2026, 7:36:33 AM
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