aws-serverless

AWS Serverless

Specialized skill for building production-ready serverless applications on AWS. Covers Lambda functions, API Gateway, DynamoDB, SQS/SNS event-driven patterns, SAM/CDK deployment, and cold start optimization.

Principles

• Right-size memory and timeout (measure before optimizing)
• Minimize cold starts for latency-sensitive workloads
• Use SnapStart for Java 11+, Python 3.12+, .NET 8+ functions
• Prefer HTTP API over REST API for simple use cases
• Design for failure with DLQs and retries
• Keep deployment packages small
• Use environment variables for configuration
• Implement structured logging with correlation IDs

When to use / pattern index

Match the task to a pattern, then open its reference file for full code.

Task	Pattern	Reference
Any Lambda function, API handler, event processor, scheduled task	Lambda Handler (Node + Python, error handling)	references/lambda-handler.md
REST/HTTP API backed by Lambda; choosing HTTP vs REST API	API Gateway Integration (SAM template + handler, API comparison)	references/api-gateway.md
Decoupled async processing, batch consumers, DynamoDB change reactions	Event-Driven (SQS with partial-batch failure + DLQ, DynamoDB Streams)	references/event-driven.md
Latency-sensitive / user-facing / high-traffic functions	Cold Start Optimization (package size, SnapStart, memory, provisioned concurrency, lazy init)	references/cold-start.md
Local dev/testing; IaC with SAM or CDK	Deployment (SAM local + CDK stack)	references/deployment.md
Debugging production issues (INIT billing, timeouts, OOM, VPC cold start, event-loop hangs, payload limits, recursive invocation)	Sharp Edges	references/sharp-edges.md
Reviewing serverless code for anti-patterns	Validation Checks (credentials, IAM, error handling, memory/timeout, DLQ, SDK imports)	references/validation-checks.md

Collaboration

Delegation Triggers

• user needs GCP serverless -> gcp-cloud-run (Cloud Run for containers, Cloud Functions for events)
• user needs Azure serverless -> azure-functions (Azure Functions, Logic Apps)
• user needs database design -> postgres-wizard (RDS design, or use DynamoDB patterns)
• user needs authentication -> auth-specialist (Cognito, API Gateway authorizers)
• user needs complex workflows -> workflow-automation (Step Functions, EventBridge)
• user needs AI integration -> llm-architect (Lambda calling Bedrock or external LLMs)

Limitations

• Use this skill only when the task clearly matches the scope described above.
• Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
• Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.