---
id: introduction
sidebar_label: Introduction
title: Deploying a Rasa Assistant
description: How to deploy your Rasa Assistant with Kubernetes/Openshift
abstract: This section explains when and how to deploy an assistant built with Rasa.
  It will allow you to make your assistant available to users and set you up with a production-ready environment.
---
<!-- this file is version specific, do not use `@site/...` syntax -->
import variables from './../variables.json';

:::note
Are you unfamiliar with Docker, Kubernetes and Helm? Check out "[Understanding Rasa Deployments](https://www.youtube.com/watch?v=aAs_RS0ueEw&list=PL75e0qA87dlHmfmu7oPPYA22fmc6GJ2aW)" on our [YouTube channel](https://www.youtube.com/channel/UCJ0V6493mLvqdiVwOKWBODQ).
:::

## When to Deploy Your Assistant

The best time to deploy your assistant and make it available to test users is once it can handle the most
important happy paths or is what we call a [minimum viable assistant](../glossary.mdx). Then you can use incoming
conversations to inform further development of your assistant.


## Recommended Deployment Method
The [Rasa Helm Chart](https://github.com/RasaHQ/helm-charts/tree/main/charts/rasa) is the production ready method to deploy
your assistant on a Kubernetes or Openshift cluster. For details, see the [deployment instructions](./deploy-rasa.mdx).

### Cluster Requirements

To install the Rasa Helm Chart, you need an existing
[Kubernetes cluster](https://kubernetes.io/) or [OpenShift cluster](https://www.openshift.com/).
If you don't have one yet, you can get a managed cluster from a cloud provider like:
* [Google Cloud](https://cloud.google.com/kubernetes-engine),
* [DigitalOcean](https://www.digitalocean.com/products/kubernetes/),
* [Microsoft Azure](https://azure.microsoft.com/en-us/services/kubernetes-service/), or
* [Amazon EKS](https://aws.amazon.com/eks/).

## Alternative Deployment Methods

The following deployment methods are not suited to a production deployment, but can be useful for development and testing:

* [Running an assistant locally on the command line](../command-line-interface.mdx#rasa-run)

* [Developing an assistant in a Docker container](../docker/building-in-docker.mdx)

* [Deploying an assistant with Docker Compose](../docker/deploying-in-docker-compose.mdx)
