/aws-billing-and-cost-management

EC2 Right-Sizing with Compute Optimizer

Prerequisites

Opt in first: aws compute-optimizer update-enrollment-status --status Active

Metrics Analyzed

Performance: CPU utilization, memory utilization (requires CloudWatch agent), GPU utilization/memory (requires CloudWatch agent + NVIDIA GPU)

Network: NetworkIn/Out bytes/sec, packets in/out per second

EBS: Read/Write bytes/sec, Read/Write ops/sec

Instance Store: Disk read/write bytes/sec, disk read/write ops/sec

Memory metrics are critical — without them, instances with low memory may appear optimized. Memory metrics enable up to 4x more savings opportunities. Recommend CloudWatch agent installation.

Finding Classifications

Finding Reason Codes

Each finding includes reason codes explaining which metrics triggered it: CPUOverprovisioned, CPUUnderprovisioned, MemoryOverprovisioned, MemoryUnderprovisioned, EBSThroughputOverprovisioned, NetworkBandwidthOverprovisioned, GPUOverprovisioned, etc. Found in findingReasonCodes array.

Lookback Periods

Uses P99.5 percentile by default (excludes top 0.5% outliers). Default 20% CPU/memory headroom buffer.

Migration Effort Levels

Performance Risk Scale

0-1: Very Low | >1-2: Low | >2-3: Medium | >3-4: High

Savings Estimation Modes

Check effectiveRecommendationPreferences.savingsEstimationMode.source:

• PublicPricing: On-Demand pricing (default)
• CostExplorerRightsizing: Incorporates SP/RI discounts
• CostOptimizationHub: Custom pricing

If only savingsOpportunity is present, calculation uses On-Demand. If savingsOpportunityAfterDiscounts is also present, compare both.

CLI Commands

# Over-provisioned EC2 instances
aws compute-optimizer get-ec2-instance-recommendations \
  --filters Name=Finding,Values=Overprovisioned

# Idle resources (near-zero utilization)
aws compute-optimizer get-idle-recommendations

# Export to S3 for bulk analysis
aws compute-optimizer export-ec2-instance-recommendations \
  --s3-destination-config bucket=my-bucket,keyPrefix=ec2-recs \
  --file-format Csv

Analyzing a Recommendation

When presenting a right-sizing recommendation to the user, include:

1. Current instance type and specs (vCPUs, memory)
2. Which metrics triggered the finding (with actual values)
3. Recommended instance type and specs
4. Monthly savings ($ and %) — calculate with a script, NEVER manually
5. Migration effort level and any platform differences (Xen→Nitro, x86→arm64)
6. Whether memory metrics were available (if not, recommend CloudWatch agent)