🛡️ AWS Lambda Function memory is overprovisioned🟢

• Contextual name: 🛡️ Function memory is overprovisioned🟢
• ID: /ce/ca/aws/lambda/function-memory-overprovisioned
• Tags:
  • 🟢 Policy with categories
  • 🟢 Policy with type
  • 🟢 Production policy
• Policy Type: BEST_PRACTICE
• Policy Categories: COST

Stats

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Logic

• 🧠 prod.logic.yaml🟢
  • 📗 AWS Lambda Function
  • 🔌 AWS Lambda Function - object.extracts.yaml
  • 🔌 AWS Compute Optimizer Lambda Func. Rec. - object.extracts.yaml
  • 🧪 test-data.json

Description

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Description

This policy identifies AWS Lambda functions whose current $LATEST configuration has an AWS Compute Optimizer memory overprovisioning recommendation and a valid smaller memory option. Review these functions for potential cost savings and benchmark the proposed configuration before reducing memory.

Rationale

Excess memory can increase Lambda compute costs. Compute Optimizer provides workload-based recommendations that distinguish memory overprovisioning from underprovisioning. Using the specific MemoryOverprovisioned reason avoids treating every NotOptimized finding as a downsizing opportunity.

The policy identifies candidates for review, rather than guaranteed savings. Prioritize functions with positive estimated savings and enough usage to justify the testing and deployment effort. A zero or unavailable savings estimate should not be treated as a confirmed financial benefit.

The 14-day analysis period, minimum invocation count, and supported memory range are eligibility checks, not a formula for calculating the recommended memory size. AWS bases Lambda sizing recommendations on workload history, including CPU time, duration, and memory usage. The Lambda recommendation API does not expose fixed utilization thresholds, memory headroom settings, or a maximum permitted duration increase. This policy therefore validates the recommendation and its smaller memory option without inventing a memory-utilization cutoff. Observed memory usage, projected duration, and savings provide evidence for reviewing the recommendation; they do not reproduce AWS's sizing model.

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Remediation

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Remediation

1. Open AWS Compute Optimizer → Lambda functions in the affected account and Region, and select the function. Confirm that the recommendation targets $LATEST, reports MemoryOverprovisioned, matches the current memory size, and still reflects the deployed code and configuration. If the function has changed since analysis, wait for a new recommendation.
2. Review the smaller recommended memory option, projected duration, available performance risk, and estimated monthly savings, including applicable discounts. Performance risk can be empty for overprovisioned functions; do not interpret an empty risk value as a guarantee of safe downsizing. Prioritize changes with a worthwhile financial benefit; zero or unavailable estimated savings alone do not justify a production change.
3. Benchmark the proposed memory size in a test environment with representative inputs, peak traffic, cold starts, and infrequent workloads. Compare execution duration, memory use, errors, timeouts, and total compute cost with the current configuration. Lower memory also reduces CPU allocation, so retain the current size if the proposed change does not meet performance requirements or reduce cost.

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policy.yaml

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Linked Framework Sections

Section	Sub Sections	Internal Rules	Policies	Flags	Compliance
💼 Cloudaware Framework → 💼 Resource Right-Sizing			22		no data