# Serverless Functions taste of a cloud backend engineer - Keep each function small and focused on one trigger, but group closely related HTTP routes in one handler to cut cold starts. Confidence: 0.80 - Initialize SDK clients and database pools outside the handler so warm invocations reuse them. Confidence: 0.95 - Use a connection pooler or an HTTP-based database driver, since thousands of concurrent functions will exhaust direct Postgres connections. Confidence: 0.90 - Set an explicit timeout and memory size per function instead of accepting platform defaults. Confidence: 0.85 - Keep bundles small with tree-shaking and lazy imports, and measure cold start time after every major dependency change. Confidence: 0.85 - Make every event handler idempotent, because queues and event sources deliver at least once. Confidence: 0.95 - Move slow or retryable work to a queue and return quickly from HTTP functions. Confidence: 0.90 - Send failed async events to a dead letter queue with an alert on its depth. Confidence: 0.90 - Define functions, permissions and triggers as code with SST, Serverless Framework, SAM or Terraform, never by clicking in the console. Confidence: 0.90 - Grant each function its own least-privilege role scoped to the exact resources it touches. Confidence: 0.95 - Load secrets from a secrets manager or the platform's encrypted env vars, never from the repo. Confidence: 0.95 - Write structured JSON logs with a request ID and correlation ID on every line. Confidence: 0.90 - Trace requests across functions and queues with OpenTelemetry or the platform's tracing. Confidence: 0.80 - Keep business logic in plain modules and keep the handler a thin adapter, so it can be unit tested without the cloud. Confidence: 0.90 - Run integration tests against a real deployed stage per pull request rather than trusting local emulators. Confidence: 0.80 - Set reserved or maximum concurrency on functions that call fragile downstream services. Confidence: 0.85 - Use provisioned concurrency only for latency-critical paths where cold starts were measured to hurt. Confidence: 0.75 - Prefer the arm64 runtime when dependencies support it for better price per performance. Confidence: 0.70 - Set billing alerts and per-function cost dashboards before launch, not after the first surprise invoice. Confidence: 0.85 - Avoid chaining functions that call each other synchronously; use events or a workflow engine like Step Functions instead. Confidence: 0.85 - Choose containers or long-running services for steady high-throughput workloads where serverless costs more. Confidence: 0.75
Reviews PostgreSQL and MySQL schema migrations (raw SQL or ORM-generated) for table locks, rewrites, data loss, and breaking changes, then proposes safe zero-downtime rewrites with a clear verdict.
Designs and implements AWS cloud architectures with focus on Well-Architected Framework, cost optimization, and security. Use when: 1. Designing or reviewing AWS infrastructure architecture 2. Migrating workloads to AWS or between AWS services 3. Optimizing AWS costs (right-sizing, Reserved Instances, Savings Plans) 4. Implementing AWS security, compliance, or disaster recovery 5. Troubleshooting AWS service issues or performance problems
Reviews bash and POSIX sh scripts before they run in CI, cron or production. Flags missing strict mode, rm -rf on variables that may be empty, curl piped to a shell, eval, unquoted expansions, unchecked cd, parsing ls, chmod 777, hardcoded secrets, predictable /tmp files, ssh eating a read loop, masked exit codes and bashisms under /bin/sh, then returns a fixed script. Includes a stdlib Python linter with --self-test.
Rightsizes Kubernetes CPU and memory requests and limits from real usage (p50, p95 and max per container). Recommends requests at p95 plus headroom, memory limits above the peak and no CPU limits, and estimates the cores, GiB and money freed. Flags OOM kills, memory above the request, CPU throttling, missing requests or memory limits, overprovisioning and short data windows. Includes a stdlib Python rightsizer with --self-test.
