Productionising LangGraph
Deploy a LangGraph agent: API worker vs queue consumer vs scheduled job on one Postgres, stream modes per consumer, bounding steps and tokens, and testing routers without a model.
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After this section you can
- Choose a deployment shape for a graph and stream the modes each consumer needs
- Bound steps, node time, run time and retries, and run the graph async behind a server
- Test routers and gates without a model, and ship graph changes without stranding paused threads
Productionising LangGraph
The compiled graph is a library object. What makes it production is everything around it: where it runs, what the user sees while it runs, what stops it, how you test it, and how you change it while runs are still in flight.
Nothing about a graph is a server. The same compiled object can sit behind an HTTP handler, a queue consumer and a cron job, and because the thread lives in the checkpointer, a run started by a request can be finished by a worker days later. Your work is the streams, the bounds, the tests and the migrations.