Chapter 1. Creating custom workbench images

Procedure

1. Obtain the location of the default image that you want to use as the base for your custom image.

   1. In the OpenShift console, select Builds ImageStreams.
   2. Select the redhat-ods-applications project.
   3. From the list of installed imagestreams, click the name of the image that you want to use as the base for your custom image. For example, click pytorch.
   4. On the ImageStream details page, click YAML.

   5. In the spec:tags section, find the tag for the version of the image that you want to use.

      The location of the original image is shown in the tag’s from:name section, for example:

      name: 'quay.io/modh/odh-pytorch-notebook@sha256:b68e0192abf7d…'

   6. Copy this location for use in your custom image.
2. Create a standard Containerfile or Dockerfile.

3. For the FROM instruction, specify the base image location that you copied in Step 1, for example:

   FROM quay.io/modh/odh-pytorch-notebook@sha256:b68e0…

4. Optional: Install OS images:

   1. Switch to USER 0 (USER 0 is required to install OS packages).
   2. Install the packages.

   3. Switch back to USER 1001.

      The following example creates a custom workbench image that adds Java to the default PyTorch image:

       FROM quay.io/modh/odh-pytorch-notebook@sha256:b68e0…
      
       USER 0
      
       RUN INSTALL_PKGS="java-11-openjdk java-11-openjdk-devel" && \
          dnf install -y --setopt=tsflags=nodocs $INSTALL_PKGS && \
          dnf -y clean all --enablerepo=*
      
       USER 1001

5. Optional: Add Python packages:

   1. Specify USER 1001.
   2. Copy the requirements.txt file.

   3. Install the packages.

      The following example installs packages from the requirements.txt file in the default PyTorch image:

       FROM quay.io/modh/odh-pytorch-notebook@sha256:b68e0…
      
       USER 1001
      
       COPY requirements.txt ./requirements.txt
      
       RUN pip install -r requirements.txt

6. Build the image file. For example, you can use podman build locally where the image file is located and then push the image to a registry that is accessible to OpenShift AI:

   $ podman build -t my-registry/my-custom-image:0.0.1 .
   $ podman push my-registry/my-custom-image:0.0.1

   Alternatively, you can leverage OpenShift’s image build capabilities by using BuildConfig.

Procedure

1. From the OpenShift AI dashboard, click Settings Notebook images.

   The Notebook images page appears. Previously imported images are displayed. To enable or disable a previously imported image, on the row containing the relevant image, click the toggle in the Enable column.

2. Optional: If you want to associate an accelerator and you have not already created an accelerator profile, click Create profile on the row containing the image and complete the relevant fields. If the image does not contain an accelerator identifier, you must manually configure one before creating an associated accelerator profile.

3. Click Import new image. Alternatively, if no previously imported images were found, click Import image.

   The Import Notebook images dialog appears.

4. In the Image location field, enter the URL of the repository containing the image. For example: quay.io/my-repo/my-image:tag, quay.io/my-repo/my-image@sha256:xxxxxxxxxxxxx, or docker.io/my-repo/my-image:tag.
5. In the Name field, enter an appropriate name for the image.
6. Optional: In the Description field, enter a description for the image.
7. Optional: From the Accelerator identifier list, select an identifier to set its accelerator as recommended with the image. If the image contains only one accelerator identifier, the identifier name displays by default.

8. Optional: Add software to the image. After the import has completed, the software is added to the image’s meta-data and displayed on the Jupyter server creation page.

   1. Click the Software tab.
   2. Click the Add software button.
   3. Click Edit ( ).
   4. Enter the Software name.
   5. Enter the software Version.
   6. Click Confirm ( ) to confirm your entry.
   7. To add additional software, click Add software, complete the relevant fields, and confirm your entry.

9. Optional: Add packages to the notebook images. After the import has completed, the packages are added to the image’s meta-data and displayed on the Jupyter server creation page.

   1. Click the Packages tab.
   2. Click the Add package button.
   3. Click Edit ( ).
   4. Enter the Package name. For example, if you want to include data science pipeline V2 automatically, as a runtime configuration, type odh-elyra.
   5. Enter the package Version. For example, type 3.16.7.
   6. Click Confirm ( ) to confirm your entry.
   7. To add an additional package, click Add package, complete the relevant fields, and confirm your entry.
10. Click Import.