🔧ZenML Self-Hosted

A guide on how to deploy ZenML in a self-hosted environment.

A ZenML deployment typically looks like this:

Some of the important components at play include:

• An HTTP server that exposes a RESTful API

  • the client's machine connects to this server to read and write the stack configurations to allow collaboration

  • the individual orchestrators and step operators communicate with the server to write and track the pipeline run data

  • the dashboard is served from the server to give a UI interface to all the metadata

• An SQL database that acts as the backend to track configurations and metadata

  • for production, currently, only MySQL is supported

• An optional secrets management service that is used as a backend for the ZenML secrets store

Choose the most appropriate deployment strategy for you out of the following options to get started with the deployment:

Deploy with ZenML CLI

Deploying ZenML on cloud using the ZenML CLI.

Deploy with Docker

Deploying ZenML in a Docker container.

Deploy with Helm

Deploying ZenML in a Kubernetes cluster with Helm.

Deploy using HuggingFace Spaces

Deploying ZenML to Huggingface Spaces.