Serverless Function Code Review: Performance, Cold Starts, and Cost

Serverless functions help teams ship quickly, but missteps during code review lead to painful cold starts and runaway bills. Use this checklist to review Lambda, Cloud Functions, or Azure Functions changes with an eye on performance and cost.

Understand the Execution Profile

Start by capturing baseline metrics: invocation frequency, payload size, memory usage, and latency targets. Ask authors to link dashboards so reviewers can reason about the workload. Without this context it is impossible to evaluate cold start impact or provisioned capacity needs.

Cold Start Mitigation Review

Cost Control Checklist

Reviewers should inspect:

• Configured memory and timeout values. Over-provisioning inflates cost linearly.
• Use of async batches that could trigger multiple downstream invocations unexpectedly.
• External API calls billed per request. Consider caching responses or batching.
• Logging verbosity. Large structured logs can double storage costs; apply sampling or log level guards.

Reliability and Retries

Serverless platforms retry automatically. During review verify backoff and idempotency:

• Idempotency keys for HTTP triggered functions writing to data stores.
• Dead letter queues or fallback topics for failed invocations (align with event driven review patterns).
• Timeouts on outbound requests to avoid hanging executions that burn minutes.

Security and Access

Serverless functions often have broad cloud permissions. Review IAM or role definitions to ensure least privilege. Confirm environment variables storing secrets are encrypted and rotated. If the function interacts with public APIs, check rate limiting and request validation logic.

Observability Expectations

Require structured logs with trace IDs, cold start flags, and execution duration. Ensure metrics include both billed duration and actual handler time so you can detect drift. Scatter plots of memory versus duration help right-size configuration. Export traces to correlate serverless latency with upstream requests.

Deployment Strategy

Ask for infrastructure changes alongside code. Confirm IaC templates update versioned aliases, environment variables, and concurrency settings atomically. Use staged rollouts or canaries to compare latency and cost before going all in. Document rollback steps and tie them to feature flags as described in our feature flag guide.

With disciplined reviews focused on cold starts, cost, and reliability, serverless platforms stay efficient and predictable. Combine these checks with the performance heuristics from our regression detection playbook to keep latency budgets intact as your serverless footprint grows.