Table of contents

Installing Decision Optimization

A project administrator can install Decision Optimization on IBM® Cloud Pak for Data.

Permissions you need for this task
You must be an administrator of the OpenShift® project (Kubernetes namespace) where you will deploy Decision Optimization.
Information you need to complete this task
  • Decision Optimization needs only the restricted security context constraint (SCC).
  • Decision Optimization must be installed in the same project as Cloud Pak for Data.
  • Decision Optimization requires the Cloud Pak for Data common core services. If the common core services are not installed in the project where you plan to install Decision Optimization, the common core services will be automatically installed when you install Decision Optimization, which will increase the amount of time the installation takes to complete.
  • Decision Optimization uses the following storage classes. If you don't use these storage classes on your cluster, ensure that you have a storage class with an equivalent definition:
    Decision Optimization leverages the storage that is provisioned when you install Watson™ Studio.

Before you begin

Ensure that the cluster meets the minimum requirements for installing Decision Optimization. For details, see System requirements.

Additionally, ensure that a cluster administrator completed the required Pre-installation tasks for your environment. Specifically, verify that a cluster administrator completed the following tasks:

  1. Cloud Pak for Data is installed. For details, see Installing Cloud Pak for Data.
  2. For environments that use a private container registry, such as air-gapped environments, the Decision Optimization software images are mirrored to the private container registry. For details, see Mirroring images to your container registry.
  3. The cluster is configured to pull the Decision Optimization software images. For details, see Configuring your cluster to pull images.
  4. The Decision Optimization operator subscription exists. For details, see Creating operator subscriptions.

If these tasks are not complete, the Decision Optimization installation will fail.

Prerequisite services

Before you install Decision Optimization, ensure that the following services are installed and running:

  • Watson Studio
  • Watson Machine Learning

Procedure

Complete the following tasks to install Decision Optimization:

  1. Installing the service
  2. Verifying the installation
  3. What to do next

Installing the service

To install Decision Optimization:

  1. Log in to Red Hat® OpenShift Container Platform as a user with sufficient permissions to complete the task:
    oc login OpenShift_URL:port
  2. Create a DODS custom resource to install Decision Optimization. Follow the appropriate guidance for your environment.

    Create a custom resource with the following format.

    cat <<EOF |oc apply -f -
    apiVersion: dods.cpd.ibm.com/v1beta1
    kind: DODS
    metadata:
      name: dods-cr     # This is the recommended name, but you can change it
      namespace: project-name     # Replace with the project where you installed Cloud Pak for Data
    spec:
      license:
        accept: true
        license: Enterprise|Standard|WatsonStudioPremium     # Specify the license you purchased
      version: 4.0.0
    EOF

Verifying the installation

When you create the custom resource, the Decision Optimization operator processes the contents of the custom resource and starts up the microservices that comprise Decision Optimization, including DODS. (The DODS microservice is defined by the dods-cr custom resource.) Decision Optimization is installed when the DODS status is Completed.

To check the status of the installation:

  1. Change to the project where you installed Decision Optimization:
    oc project project-name
  2. Get the status of Decision Optimization (dods-cr):
    oc get DODS dods-cr -o jsonpath='{.status.dodsStatus} {"\n"}'

    Decision Optimization is ready when the command returns Completed

What to do next

The service is ready to use. For details, see Building Decision Optimization models.