Chapter 2. Support removals
This section describes major changes in support for user-facing features in Red Hat OpenShift Data Science.
2.1. NVIDIA GPU Operator replaces NVIDIA GPU add-on
Previously, to enable graphics processing units (GPUs) to help with compute-heavy workloads, you installed the NVIDIA GPU add-on. OpenShift Data Science no longer supports this add-on.
Now, to enable GPU support, you must install the NVIDIA GPU Operator. To learn how to install the GPU Operator, see NVIDIA GPU Operator on OpenShift (external).
2.2. Kubeflow Notebook Controller replaces JupyterHub
In OpenShift Data Science 1.15 and earlier, JupyterHub was used to create and launch notebook server environments. In OpenShift Data Science 1.16 and later, JupyterHub is no longer included, and its functionality is replaced by Kubeflow Notebook Controller.
This change provides the following benefits:
- Users can now immediately cancel a request, make changes, and retry the request, instead of waiting 5+ minutes for the initial request to time out. This means that users do not wait as long when requests fail, for example, when a notebook server does not start correctly.
- The architecture no longer prevents a single user from having more than one notebook server session, expanding future feature possibilities.
- The removal of the PostgreSQL database requirement allows for future expanded environment support in OpenShift Data Science.
However, this update also creates the following behavior changes:
- For IT Operations administrators, the notebook server administration interface does not currently allow login access to data scientist users' notebook servers. This is planned to be added in future releases.
- For data scientists, the JupyterHub interface URL is no longer valid. Update your bookmarks to point to the OpenShift Data Science Dashboard.
The JupyterLab interface is unchanged and data scientists can continue to use JupyterLab to work with their notebook files as usual.