Creating a custom image

Create custom images for Python-based models and functions or create a custom SPSS image.

The samples provided here use Podman, but you can use any other Docker-compatible image builder.

Before you begin

You must prepare by gathering the registry URL and downloading the image configuration file and the image. For more information, see Getting registry URL and downloading image configuration.

Creating a custom Python image

After you download the image for the runtime that you want to customize, you can create a custom image by adding your customizations to the downloaded image. Start with the base image and install the libraries and packages that you need. Then, add your customizations to the Dockerfile.

Required role: You must have root privileges on your machine to execute the commands that build a custom image.

  1. Prepare the Dockerfile.

    • Do not change the contents in the USER directives. They impact how the container runs in the cluster.
    • You must have root privileges to install OS packages and to modify kernel specifications.
    • Use the microdnf tool to install the OS libraries.

  2. Create a custom Watson Machine Learning image.

For more information, see sample Dockerfile for the Watson Machine Learning Python runtime.

Adding customizations for SPSS models

To add customizations for SPSS, run the Dockerfile for installing the Exasol driver in SPSS.

For <SPSS_RUNTIME_IMAGE>, use the image name from Downloading a custom image configuration file for SPSS.

For more information, see sample Dockerfile for the Watson Machine Learning SPSS runtime.

Next steps

Pushing the custom image to the image registry.

Parent topic: Customizing deployment runtime images