> ## Documentation Index
> Fetch the complete documentation index at: https://langchain-5e9cc07a-preview-cbfron-1772840960-d2a2597.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# LangSmith Deployment

> Deploy and manage agents with durable execution, real-time streaming, and horizontal scaling.

LangSmith Deployment is a workflow orchestration runtime purpose-built for agent workloads. It handles the infrastructure that agents need to run reliably: long-running stateful execution, human-in-the-loop pauses, real-time streaming, horizontal scaling — all with a first-class [Studio](/langsmith/studio) development environment.

<Callout icon="rocket" color="#4F46E5" iconType="regular">
  **Start here if you're building or operating agent applications.** This section is about deploying **your application**. If you need to set up LangSmith infrastructure, the [Platform setup section](/langsmith/platform-setup) covers infrastructure options (cloud, hybrid, self-hosted) and setup guides.
</Callout>

A typical deployment workflow:

<Steps>
  <Step title={<a href="/langsmith/local-server">Test locally</a>}>
    Run your application on a local development server.
  </Step>

  <Step title={<a href="/langsmith/application-structure">Configure app for deployment</a>}>
    Set up dependencies, project structure, and environment configuration.
  </Step>

  <Step title={<a href="/langsmith/platform-setup">Choose hosting</a>}>
    (Required for deployment) Select Cloud, Hybrid, or Self-hosted.
  </Step>

  <Step title="Deploy your app">
    * [**Cloud**](/langsmith/deploy-to-cloud): Push code from a git repository
    * [**Hybrid or Self-hosted with control plane**](/langsmith/deploy-with-control-plane): Build and push Docker images, deploy via UI
    * [**Standalone servers**](/langsmith/deploy-standalone-server): Deploy directly without control plane
  </Step>

  <Step title={<a href="/langsmith/observability">Monitor & manage</a>}>
    Track traces, alerts, and dashboards.
  </Step>
</Steps>

***

## Durable execution

At its core, LangSmith Deployment is a durable execution engine. Your agents run on a managed task queue with automatic checkpointing, so any run can be retried, replayed, or resumed from the exact point of interruption — not from scratch.

Because execution is durable, agents can do things that would be fragile or impossible in a stateless runtime:

* **Wait for external input.** An agent calls [`interrupt()`](/langsmith/add-human-in-the-loop) and the runtime checkpoints its state, frees resources, and waits — for a human to approve a transaction, for a reviewer to edit a draft, for another system to return results. When [`Command(resume=...)`](/langsmith/add-human-in-the-loop) arrives hours or days later, execution picks up exactly where it stopped. This is the primitive underneath [human-in-the-loop](/langsmith/add-human-in-the-loop) workflows and [time-travel debugging](/langsmith/human-in-the-loop-time-travel).
* **Run in the background.** [Background runs](/langsmith/background-run) execute without blocking the caller. The runtime manages the full lifecycle — queuing, execution, checkpointing, completion — while the client moves on.
* **Run on a schedule.** [Cron jobs](/langsmith/cron-jobs) trigger agent execution on a recurring cadence. A daily summary agent, a weekly report, a periodic data sync — the runtime starts a new execution on schedule with the same durability guarantees.
* **Handle concurrent input.** When a user sends new input while an agent is mid-run ([double-texting](/langsmith/double-texting)), the runtime can queue it, cancel the in-progress run, or process both in parallel — without data races or corrupted state.
* **Retry on failure.** Configurable [retry policies](/oss/python/langgraph/use-graph-api#retry-policies) control backoff, max attempts, and which exceptions trigger retries on a per-node basis. Runs survive process restarts, infrastructure failures, and code revisions mid-execution.

For details on how containers, processes, and the task queue work together, see [Agent Server: Runtime architecture](/langsmith/agent-server#runtime-architecture). For scaling and throughput tuning, see [Configure Agent Server for scale](/langsmith/agent-server-scale).

## Streaming

Agents need to show their work in real time. The runtime provides [resumable streaming](/langsmith/streaming) — if a client disconnects mid-stream (network switch, tab sleep, mobile backgrounding), it reconnects and picks up where it left off. Multiple [streaming modes](/langsmith/streaming) give you control over granularity, from full state snapshots after each step to token-by-token LLM output as it arrives from the provider.

## Studio

[LangGraph Studio](/langsmith/studio) connects to any Agent Server — local or deployed — and gives you an interactive environment for developing and debugging agents. Visualize execution graphs, inspect state at any checkpoint, step through runs, modify state mid-execution, and branch to explore alternative paths.

## Agent composition

Agents don't run in isolation. [RemoteGraph](/langsmith/use-remote-graph) lets any agent call other deployed agents using the same interface you use locally — a research agent delegates to a search agent on a different deployment, a routing agent dispatches to specialized sub-agents. The agents don't need to know whether they're calling something local or remote.

Native support for [MCP](/langsmith/server-mcp) and [A2A](/langsmith/server-a2a) means your deployed agents can expose and consume tool interfaces and agent-to-agent protocols alongside the broader ecosystem.

***

## Deployment options

* **[Cloud](/langsmith/deploy-to-cloud)** — Fully managed. Push from a git repo.
* **[Hybrid](/langsmith/deploy-with-control-plane)** — Runs in your cloud, managed by the LangSmith [control plane](/langsmith/control-plane).
* **[Self-hosted](/langsmith/deploy-standalone-server)** — Fully self-managed in your own infrastructure.

Same runtime, same APIs. What changes is who manages the infrastructure. See [Platform setup](/langsmith/platform-setup) for a comparison.

***

## Go deeper

### Securing and customizing your server

* [Custom auth](/langsmith/auth) — Authentication and multi-tenant access control
* [Server customization](/langsmith/custom-routes) — Custom routes, [middleware](/langsmith/custom-middleware), [lifespan hooks](/langsmith/custom-lifespan), [encryption](/langsmith/encryption)

### Operations

* [CI/CD pipelines](/langsmith/cicd-pipeline-example)
* [TTL configuration](/langsmith/configure-ttl) for state and thread management
* [Semantic search](/langsmith/semantic-search)

### Reference

* [Agent Server](/langsmith/agent-server) — Runtime architecture reference

***

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    [Edit this page on GitHub](https://github.com/langchain-ai/docs/edit/main/src/langsmith/deployments.mdx) or [file an issue](https://github.com/langchain-ai/docs/issues/new/choose).
  </Callout>

  <Callout icon="terminal-2">
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