BD Brain Drip
Module 09 7 concepts

Deployment

LangGraph Cloud, Docker, and production deployment.

01

Cloud Provider Deployment

Deploying LangGraph agents to AWS, GCP, or Azure involves packaging the agent as a Docker container and running it on a managed container service – with each provider offering trade-offs in complexity, cost, and scaling behavior.

02

Containerization

Docker packages your LangGraph agent, its dependencies, and runtime into a portable container that runs identically everywhere – from your laptop to production servers.

03

FastAPI Deployment

Wrapping a LangGraph agent in FastAPI gives you a production-ready API with sync and streaming endpoints, full control over auth, rate limiting, and zero vendor lock-in.

04

LangGraph Dev Server

The langgraph dev command launches a built-in development server with an API, visual Studio UI, and auto-generated docs – the fastest way to test and debug agents locally.

05

LangGraph Platform

LangGraph Platform (deployed via LangSmith) is a managed hosting service purpose-built for stateful, long-running agents – handling infrastructure, scaling, persistence, and operational concerns so you can deploy directly from a GitHub repository.

06

LangGraph SDK

The langgraph-sdk package provides Python and JavaScript clients for interacting with any LangGraph server – managing threads, streaming runs, inspecting state, and controlling agent execution through a unified API.

07

Production Checklist

Twelve essential steps that transform a working LangGraph prototype into a reliable, observable, and maintainable production system.