Getting Started
How to get started with extending ZenML.
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
Orchestrating the runs of your pipeline
Storage for the artifacts created by your pipelines
Tracking the execution of your pipelines/steps
Store for your containers
Centralized location for the storage of your secrets
Execution of individual steps in specialized runtime environments
Services/platforms responsible for online model serving
Management of your data/features
Tracking your ML experiments
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.
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