Installing Watson Machine Learning on IBM Cloud

Watson Machine Learning provides a full range of tools and services so that you can build, train, and deploy Machine Learning models. Choose the tool with the level of automation or autonomy that matches your needs, from a fully automated process to writing your own code.

For more information about Watson Machine Learning, see Watson Machine Learning on Cloud Pak for Data .

Tip: This task maps to the following Ansible role, when you specify wml as the service name: cp4d_service. For more information, see IBM Maximo Application Suite installation with Ansible collection.

Procedure

To install by using the Red Hat® OpenShift® Container Platform web console:
1. Access the Red Hat OpenShift Container Platform Web Console.
2. In the banner, click Import YAML (). Enter the following YAML.
```
---
apiVersion: operators.coreos.com/v1alpha1
kind: Subscription
metadata:
  annotations:
  name: ibm-cpd-wml-operator-catalog-subscription
  namespace: ibm-common-services
spec:
  channel: v1.1
  installPlanApproval: Automatic
  name: ibm-cpd-wml-operator
  source: ibm-operator-catalog
  sourceNamespace: openshift-marketplace
```
3. Click the Create button to install the Watson Machine Learning operator subscription.
4. On the Workloads > Pods page, switch to the ibm-common-services project and wait for the Watson Studio pod resource ibm-cpd-wml-operator to indicate it is in Running state.

Installing the Watson Machine Learning custom resource:

Review the following table to ensure that you select the correct storage class:

Table 1.
Cloud Service Provider	Watson Machine Learning Storage Classes
On-premises	`ocs-storagecluster-cephfs`
AWS	`ocs-storagecluster-cephfs`
IBM Cloud	`ibmc-file-gold-gid`

In the banner, click Import YAML () Enter the following YAML.

If you are using Red Hat Openshift Container Storage (OCS), specify the "storageVendor" property as shown in the following example:


---
apiVersion: wml.cpd.ibm.com/v1beta1
kind: WmlBase
metadata:
  name: wml-cr
  namespace: cpd-services
spec:
  ignoreForMaintenance: false
  license:
    accept: true
    license: Standard
  storageVendor: ocs
  storageClass: ocs-storagecluster-cephfs          #if you use a different storage class, replace it with the appropriate storage class                            
  scaleConfig: small
  version: 4.0.8 # if you want to install the latest version, remove the 'version' property

If you are using IBM Cloud File Storage, use the following example.


---
apiVersion: wml.cpd.ibm.com/v1beta1
kind: WmlBase
metadata:
  name: wml-cr
  namespace: cpd-services
spec:
  ignoreForMaintenance: false
  license:
    accept: true
    license: Standard
  storageClass: ibmc-file-gold-gid         #if you use a different storage class, replace it with the appropriate storage class      
  scaleConfig: small
  version: 4.0.8 # if you want to install the latest version, remove the 'version' property

Click the Create button to install the Watson Machine Learning custom resource, which will initialize the service installation.

Verifying the Watson Machine Learning installation:
1. On the Home > Search, select the cpd-services project and search for resource type WmlBase.
2. Open the wml-cr instance of the WmlBase resource. From the YAML tab, wait until you see wmlStatus: Completed in the status section. This process can take up to 60 minutes depending on your cluster's network and capacity.
Suite Configuration Parameters:

MAS Configuration scope: Workspace-application

Now you are ready to configure Watson Machine Learning into Maximo Application Suite. You will need to configure Watson Machine Learning in Maximo Application Suite while activating Maximo Predict application. For more information on how to deploy and activate Maximo Predict, refer to Deploying IBM Maximo Predict.