Deploy ZenML

A guide on how to deploy ZenML.

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.

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Set up your MLOps platform

Deploy with ZenML CLI

Last modified 2d ago