Getting Started

How to get started with extending ZenML.

This is an older version of the ZenML documentation. To check the latest version please visit https://docs.zenml.io

While you are working on an ML task, it is very likely that you will require a custom tailored solution. This might not only mean that you have to write custom code, but also custom components for your infrastructure.

That's exactly why we built ZenML in a way which is completely open to extension. You can simply use our base abstractions, create your own flavors and generate custom stack components.

If you would like to learn more about how to achieve this with a specific stack component, please check the links below:

Type of Stack Component	Description
Orchestrator	Orchestrating the runs of your pipeline
Artifact Store	Storage for the artifacts created by your pipelines
Metadata Store	Tracking the execution of your pipelines/steps
Container Registry	Store for your containers
Secrets Manager	Centralized location for the storage of your secrets
Step Operator	Execution of individual steps in specialized runtime environments
Model Deployer	Services/platforms responsible for online model serving
Feature Store	Management of your data/features
Experiment Tracker	Tracking your ML experiments
Alerter	Sending alerts through specified channels

Keep in mind that ZenML is an open-source project. We appreciate and thrive on the contribution from our community. If you would like to contribute your custom implementations back our repository, you can find the guide on GitHub.