Red Hat SummitChapter 1. Overview
In Red Hat OpenShift AI, a workbench is an isolated area where a data scientist can examine and work with ML models. When you create a workbench, you specify a workbench image. OpenShift AI provides a selection of default workbench images that you can choose from. Each image is optimized with the tools and libraries that a data scientist needs for model development. To view a list of the OpenShift AI default workbench images and their preinstalled packages, see Supported Configurations for 3.x.
As a cluster administrator, you can create a custom image, for example, if a data scientist on your team requires a specific version of a library that is different from the version provided in a default image. For information about OpenShift AI custom images, see Creating custom workbench images.
You have the following options for creating workbenches and custom images:
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As an OpenShift cluster administrator, you can create a custom image and a workbench by using OpenShift AI Custom Resource Definitions (CRDs) and the OpenShift CLI (
oc) as described in this guide. - As an OpenShift cluster administrator, you can use OpenShift APIs to create resources, such as a custom image. You can programmatically call the APIs through HTTP GET methods in your code, a Bash script, or a Python script. For more information about using the OpenShift APIs to create an ImageStream resource, see the ImageStream entry in the OpenShift API Reference.
- As any OpenShift AI user, you can use the OpenShift AI dashboard to create workbenches and select images, as described in Using project workbenches.
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