How do you deploy LangGraph applications?

LangGraph applications can be deployed in three main ways: LangGraph Cloud (managed service), self-hosted with Docker + FastAPI, and embedded in a larger application. The right choice depends on your team's infrastructure requirements and SLA needs.

LangGraph Cloud — LangChain's managed deployment platform. You push your graph code to a GitHub repo, connect it to LangGraph Cloud, and it handles scaling, checkpointing (PostgreSQL), streaming, and monitoring automatically. Provides REST and WebSocket APIs out of the box.

Self-hosted FastAPI — wrap the compiled graph with a FastAPI app and use PostgresSaver for multi-process state:

from fastapi import FastAPI
from langgraph.checkpoint.postgres.aio import AsyncPostgresSaver

app = FastAPI()

@app.on_event("startup")
async def startup():
    saver = await AsyncPostgresSaver.from_conn_string(DB_URL)
    global graph
    graph = graph_builder.compile(checkpointer=saver)

@app.post("/chat/{thread_id}")
async def chat(thread_id: str, message: str):
    config = {"configurable": {"thread_id": thread_id}}
    result = await graph.ainvoke({"messages": [HumanMessage(message)]}, config)
    return {"response": result["messages"][-1].content}

Containerise with Docker, expose via Kubernetes or a managed container service, and use LangSmith for production observability.

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