> ## Documentation Index
> Fetch the complete documentation index at: https://growthx-chore-remove-output-wrapper.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Deployment overview

> Deploy your Output workflows to production

This section covers deploying Output workflows to a production environment. Whether you're running a single worker or scaling across multiple instances, the deployment architecture stays the same.

## What you're deploying

An Output deployment consists of two core services, with an optional third for remote tracing:

| Service    | Required | Purpose                                                                                                                                                      |
| ---------- | -------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------ |
| **API**    | Yes      | HTTP endpoint for triggering workflows, listing available workflows, and retrieving results. Deployed from a pre-built Docker image — no custom code needed. |
| **Worker** | Yes      | Runs your workflows. Contains your workflow code, connects to the Temporal backend, and executes workflow steps.                                             |
| **Redis**  | No       | Enables remote trace file generation and S3 upload for debugging production runs. See [Tracing](/operations/tracing) for details.                            |

The API is a lightweight HTTP server that accepts workflow execution requests, routes them to the Temporal backend, and returns results. It ships as a pre-built Docker image so there's no custom code to maintain.

The Worker is the core of your deployment — it contains your workflow code and connects to the Temporal backend for orchestration. Workers scale horizontally; you can add more instances to handle increased load without changing your workflow code.

<Note>
  These guides assume you're using **Temporal Cloud** for workflow orchestration. If you need help setting up Temporal Cloud, see the [Temporal Cloud documentation](https://docs.temporal.io/cloud).
</Note>

## Prerequisites

Before deploying to any platform, ensure you have:

* A Temporal backend with a dedicated namespace (e.g. [Temporal Cloud](https://temporal.io/cloud))
* Your workflow repository on GitHub
* API keys for any services your workflows use (Anthropic, OpenAI, etc.)

## Platform guides

Choose your deployment platform:

<CardGroup cols={3}>
  <Card title="Railway" icon="train" href="/operations/deployment/railway">
    **Railway.** Simple Docker-based deployments with automatic scaling.
  </Card>

  <Card title="Render" icon="cloud" href="/operations/deployment/render">
    **Render.** Infrastructure-as-code deployments with a single render.yaml Blueprint.
  </Card>

  <Card title="Advanced" icon="gear" href="/operations/deployment/advanced">
    **Advanced.** Remote tracing with Redis and S3 for production debugging.
  </Card>
</CardGroup>

## Next steps

<CardGroup cols={2}>
  <Card title="Tracing" icon="magnifying-glass" href="/operations/tracing">
    **Tracing.** Configure production tracing and S3 storage.
  </Card>

  <Card title="Error Handling" icon="triangle-exclamation" href="/operations/error-handling">
    **Error Handling.** Handle failures gracefully in production.
  </Card>
</CardGroup>