Deploying Your Rasa Assistant¶
This page 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.
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.
The recommended deployment methods described below make it easy to share your assistant with test users via the share your assistant feature in Rasa X. Then, when you’re ready to make your assistant available via one or more Messaging and Voice Channels, you can easily add them to your existing deployment set up.
The recommended way to deploy an assistant is using either the One-Line Deployment or Kubernetes/Openshift options we support. Both deploy Rasa X and your assistant. They are the easiest ways to deploy your assistant, allow you to use Rasa X to view conversations and turn them into training data, and are production-ready.
The one-line deployment script is the easiest way to deploy Rasa X and your assistant. It installs a Kubernetes cluster on your machine with sensible defaults, getting you up and running in one command.
For assistants that will receive a lot of user traffic, setting up a Kubernetes or Openshift deployment via our helm charts is the best option. This provides a scalable architecture that is also straightforward to deploy. However, you can also customize the Helm charts if you have specific requirements.
You can also run Rasa X in a Docker Compose setup, without the cluster environment. We have a quick install script for doing so, as well as manual instructions for any custom setups.
It is also possible to deploy a Rasa assistant without Rasa X using Docker Compose. To do so, you can build your Rasa Assistant locally or in Docker. Then you can deploy your model in Docker Compose.