AWS Lambda cold start optimization — reducing initialization time

AWS Lambda functions take 1-10 seconds on first invocation (cold start). Users experience intermittent slow responses. Cold starts happen after periods of inactivity or during scaling.

(1) Keep deployment package small — fewer files to decompress. Use layers for dependencies. (2) Initialize SDK clients outside the handler — they persist across warm invocations. (3) Use provisioned concurrency for critical functions — keeps instances warm. (4) Language choice matters: Python/Node.js cold start ~200-500ms, Java/C# ~1-5s. (5) Use SnapStart (Java) to snapshot after initialization. (6) Minimize imports — only import what you need. (7) Use ARM64 (Graviton) — faster and cheaper. (8) Reduce memory to reduce cost but increase memory for faster CPU (Lambda CPU scales linearly with memory). (9) Use Lambda Extensions for monitoring instead of in-handler initialization.

Cold starts occur when Lambda must provision a new execution environment: download code, start the runtime, run initialization code. Once warm, the environment is reused for subsequent invocations.