Container Images

Kubeflow Notebooks natively supports three types of notebooks, JupyterLab, RStudio, and Visual Studio Code (code-server), but any web-based IDE should work. Notebook servers run as containers inside a Kubernetes Pod, which means the type of IDE (and which packages are installed) is determined by the Docker image you pick for your server.

Images

We provide a number of example container images to get you started.

Base Images

These images provide a common starting point for Kubeflow Notebook containers. See custom images to learn how to extend them with your own packages.

Full Images

These images extend the base images with common packages used by Data Scientists and ML Engineers.

Image Dependency Chart

This flow-chart shows how our notebook container images depend on each other.

Custom Images

Packages installed by users after spawning a Kubeflow Notebook will only last the lifetime of the pod (unless installed into a PVC-backed directory).

To ensure packages are preserved throughout Pod restarts users will need to either:

1. Build custom images that include them, or
2. Ensure they are installed in a PVC-backed directory

Image Requirements

For Kubeflow Notebooks to work with a container image, the image must:

• expose an HTTP interface on port 8888:
  • kubeflow sets an environment variable NB_PREFIX at runtime with the URL path we expect the container be listening under
  • kubeflow uses IFrames, so ensure your application sets Access-Control-Allow-Origin: * in HTTP response headers
• run as a user called jovyan:
  • the home directory of jovyan should be /home/jovyan
  • the UID of jovyan should be 1000
• start successfully with an empty PVC mounted at /home/jovyan:
  • kubeflow mounts a PVC at /home/jovyan to keep state across Pod restarts

Next steps

• Use your container image by specifying it when spawning your notebook server. (See the quickstart guide.)