Architectural patterns for serverless execution and orchestration.

🚀 Core Commands

Function Lifecycle

# List all functions with runtime and memory info
aws lambda list-functions --query "Functions[].{Name:FunctionName,Runtime:Runtime,Memory:MemorySize}" --output table
# Invoke a function synchronously with payload
aws lambda invoke --function-name  --payload '{"key": "value"}' --cli-binary-format raw-in-base64-out response.json

Deployment & Configuration

# Update function code via ZIP
aws lambda update-function-code --function-name  --zip-file fileb://function.zip
# Update environment variables
aws lambda update-function-configuration --function-name  --environment "Variables={KEY=VALUE,ENV=PROD}"

Performance & Scaling

# Check concurrency limits and usage
aws lambda get-account-settings --query "AccountLimit"
# Put provisioned concurrency (warm start optimization)
aws lambda put-provisioned-concurrency-config --function-name  --qualifier  --provisioned-concurrent-executions 5

🧠 Best Practices

• Layer Management: Offload heavy dependencies (like FFmpeg or Chromium) into Lambda Layers to keep deployment packages small.
• Timeout Strategy: Set aggressive timeouts to prevent runaway costs from stuck executions.
• IAM Execution Role: Ensure the role has exactly the permissions needed for S3/DynamoDB access—no more.
• Monitoring: Use CloudWatch Insights to trace latencies and cold starts.