Creating custom workbench images

{productname-long} includes a selection of default workbench images that a data scientist can select when they create or edit a workbench.

In addition, you can import a custom workbench image, for example, if you want to add libraries that data scientists often use, or if your data scientists require a specific version of a library that is different from the version provided in a default image. Custom workbench images are also useful if your data scientists require operating system packages or applications because they cannot install them directly in their running environment (data scientist users do not have root access, which is needed for those operations).

A custom workbench image is simply a container image. You build one as you would build any standard container image, by using a Containerfile (or Dockerfile). You start from an existing image (the FROM instruction), and then add your required elements.

You have the following options for creating a custom workbench image:

Start from one of the default images, as described in Creating a custom image from a default {productname-short} image.
Create your own image by following the guidelines for making it compatible with {productname-short}, as described in Creating a custom image from your own image.