Deploying LangChain Apps on AWS Lambda: A Practical Guide

Why serverless for LLM apps

LLM backends are I/O-bound: most of the request lifetime is waiting on a model API. Lambda bills you only for that wait at a scale-to-zero price.

The traps

1. Cold starts — keep the deployment package lean; lazy-import heavy libraries
2. Timeouts — set 60s+, stream where possible
3. Statefulness — conversation memory belongs in DynamoDB or Redis, never in the function

Reference architecture

API Gateway → Lambda (FastAPI via Mangum) → Bedrock/OpenAI + vector store. Infrastructure as code with SAM or CDK.

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