Custom Image CLI for Runtimes in Cloud Pak for Data

CLI to create and use custom image runtimes

This project streamlines the process of creating a custom image for Cloud Pak for Data runtimes by wrapping the key steps into CLI commands, covering: 1. gather the needed information such as base image names 2. build one custom image per base image, in batch 3. push each custom image to a target container registry 4. register a custom image with the corresponding Cloud Pak for Data service

Currently it supports the following services:

  1. Watson Studio

  • Jupyter notebook and Jupyter Lab environments in Python

  • Rstudio environments

  1. Watson Machine Learning

  • Python online deployment environments

Important notes

1 - The current release is implemented and tested only for Cloud Pak for Data 4.0.x. If you are on 3.5.x, it does not apply because the way to fetch base images is changed in 4.0.x. If you are on 4.5.x, this CLI may work.

2 - Gathering information and registering custom images are specific to Cloud Pak for Data, while building and pushing the custom image can be easily extended to support arbitrary situation.

3 - You need to know the key to access the Cloud Pak for Data base image repository (cp.icr.io), or have access to the OpenShift backend of any 4.0.x Cloud Pak for Data cluster you are building a custom image for from where you will be able to extract the secrets according to the Getting Started Guide in this doc.

4 - R Jupyter environment is not tested or supported by this CLI as usually R users prefer Rstudio. Contact the author if there is a need.