Upgrading Watson Machine Learning from Version 4.8.x to a later 4.8 refresh

An instance administrator can upgrade Watson Machine Learning from Cloud Pak for Data Version 4.8.x to a later 4.8 refresh.

Who needs to complete this task?

Instance administrator To upgrade Watson Machine Learning, you must be an instance administrator. An instance administrator has permission to manage software in the following projects:

The operators project for the instance

The operators for this instance of Cloud Pak for Data are installed in the operators project. In the upgrade commands, the ${PROJECT_CPD_INST_OPERATORS} environment variable refers to the operators project.

The operands project for the instance

The Cloud Pak for Data control plane and the services for this instance of Cloud Pak for Data are installed in the operands project. In the upgrade commands, the ${PROJECT_CPD_INST_OPERANDS} environment variable refers to the operands project.

When do you need to complete this task?

Review the following options to determine whether you need to complete this task:

  • If you want to upgrade the Cloud Pak for Data control plane and one or more services at the same time, follow the process in Upgrading an instance of Cloud Pak for Data instead.
  • If you didn't upgrade Watson Machine Learning when you upgraded the Cloud Pak for Data control plane, complete this task to upgrade Watson Machine Learning.

    Repeat as needed If you are responsible for multiple instances of Cloud Pak for Data, you can repeat this task to upgrade more instances of Watson Machine Learning on the cluster.

Information you need to complete this task

Review the following information before you upgrade Watson Machine Learning:

Version requirements

All the components that are associated with an instance of Cloud Pak for Data must be installed at the same release. For example, if the Cloud Pak for Data control plane is at Version 4.8.7, you must upgrade Watson Machine Learning to Version 4.8.7.

Environment variables
The commands in this task use environment variables so that you can run the commands exactly as written.
  • If you don't have the script that defines the environment variables, see Setting up installation environment variables.
  • To use the environment variables from the script, you must source the environment variables before you run the commands in this task. For example, run:
    source ./cpd_vars.sh
Common core services
Watson Machine Learning requires the Cloud Pak for Data common core services.

If the common core services are not at the correct version in the operands project for the instance, the common core services are automatically upgraded when you upgrade Watson Machine Learning. The common core services upgrade increases the amount of time the upgrade takes to complete.

Storage requirements
Specify the storage that you use in your existing installation. You cannot change the storage that is associated with Watson Machine Learning during an upgrade. Ensure that the environment variables point to the correct storage classes for your environment.

Before you begin

This task assumes that the following prerequisites are met:

Prerequisite Where to find more information
The cluster meets the minimum requirements for Watson Machine Learning. If this task is not complete, see System requirements.
The workstation from which you will run the upgrade is set up as a client workstation and the following command-line interfaces:
  • Cloud Pak for Data CLI: cpd-cli
  • OpenShift® CLI: oc
If this task is not complete, see Updating client workstations.
The Cloud Pak for Data control plane is upgraded. If this task is not complete, see Upgrading an instance of Cloud Pak for Data.
For environments that use a private container registry, such as air-gapped environments, the Watson Machine Learning software images are mirrored to the private container registry. If this task is not complete, see Mirroring images to a private container registry.
For environments that use a private container registry, such as air-gapped environments, the cpd-cli is configured to pull the olm-utils-v2 image from the private container registry. If this task is not complete, see Pulling the olm-utils-v2 image from the private container registry.

Procedure

Complete the following tasks to upgrade Watson Machine Learning:

  1. Upgrading the service
  2. Validating the upgrade
  3. What to do next

If you want to enable the patch commands after upgrade, see Enabling installation options after installation or upgrade for.

Upgrading the service

Important: The Operator Lifecycle Manager (OLM) objects for Watson Machine Learning were updated when you upgraded the Cloud Pak for Data platform. The cpd-cli manage apply-olm updates all of the OLM objects in the operators project at the same time.

To upgrade Watson Machine Learning:

  1. Log the cpd-cli in to the Red Hat® OpenShift Container Platform cluster:
    ${CPDM_OC_LOGIN}
    Remember: CPDM_OC_LOGIN is an alias for the cpd-cli manage login-to-ocp command.
  2. Update the custom resource for Watson Machine Learning.

    The command that you run depends on the storage on your cluster:


    Red Hat OpenShift Data Foundation storage

    Run the following command to create the custom resource.

    cpd-cli manage apply-cr \
    --components=wml \
    --release=${VERSION} \
    --cpd_instance_ns=${PROJECT_CPD_INST_OPERANDS} \
    --block_storage_class=${STG_CLASS_BLOCK} \
    --file_storage_class=${STG_CLASS_FILE} \
    --license_acceptance=true \
    --upgrade=true

    IBM Storage Fusion Data Foundation storage

    Run the following command to create the custom resource.

    cpd-cli manage apply-cr \
    --components=wml \
    --release=${VERSION} \
    --cpd_instance_ns=${PROJECT_CPD_INST_OPERANDS} \
    --block_storage_class=${STG_CLASS_BLOCK} \
    --file_storage_class=${STG_CLASS_FILE} \
    --license_acceptance=true \
    --upgrade=true

    IBM Storage Fusion Global Data Platform storage
    Remember: When you use IBM Storage Fusion storage, both ${STG_CLASS_BLOCK} and ${STG_CLASS_FILE} point to the same storage class, typically ibm-spectrum-scale-sc or ibm-storage-fusion-cp-sc.

    Run the following command to create the custom resource.

    cpd-cli manage apply-cr \
    --components=wml \
    --release=${VERSION} \
    --cpd_instance_ns=${PROJECT_CPD_INST_OPERANDS} \
    --block_storage_class=${STG_CLASS_BLOCK} \
    --file_storage_class=${STG_CLASS_FILE} \
    --license_acceptance=true \
    --upgrade=true

    IBM Storage Scale Container Native storage
    Remember: When you use IBM Storage Scale Container Native storage, both ${STG_CLASS_BLOCK} and ${STG_CLASS_FILE} point to the same storage class, typically ibm-spectrum-scale-sc.

    Run the following command to create the custom resource.

    cpd-cli manage apply-cr \
    --components=wml \
    --release=${VERSION} \
    --cpd_instance_ns=${PROJECT_CPD_INST_OPERANDS} \
    --block_storage_class=${STG_CLASS_BLOCK} \
    --file_storage_class=${STG_CLASS_FILE} \
    --license_acceptance=true \
    --upgrade=true

    Portworx storage

    Run the following command to create the custom resource.

    cpd-cli manage apply-cr \
    --components=wml \
    --release=${VERSION} \
    --cpd_instance_ns=${PROJECT_CPD_INST_OPERANDS} \
    --storage_vendor=portworx \
    --license_acceptance=true \
    --upgrade=true

    NFS storage
    Remember: When you use NFS storage, both ${STG_CLASS_BLOCK} and ${STG_CLASS_FILE} point to the same storage class, typically managed-nfs-storage.

    Run the following command to create the custom resource.

    cpd-cli manage apply-cr \
    --components=wml \
    --release=${VERSION} \
    --cpd_instance_ns=${PROJECT_CPD_INST_OPERANDS} \
    --block_storage_class=${STG_CLASS_BLOCK} \
    --file_storage_class=${STG_CLASS_FILE} \
    --license_acceptance=true \
    --upgrade=true

    AWS with EFS storage only
    Remember: When you use EFS storage, both ${STG_CLASS_BLOCK} and ${STG_CLASS_FILE} point to the same storage class, typically efs-nfs-client.

    Run the following command to create the custom resource.

    cpd-cli manage apply-cr \
    --components=wml \
    --release=${VERSION} \
    --cpd_instance_ns=${PROJECT_CPD_INST_OPERANDS} \
    --block_storage_class=${STG_CLASS_BLOCK} \
    --file_storage_class=${STG_CLASS_FILE} \
    --license_acceptance=true \
    --upgrade=true

    AWS with EFS and EBS storage

    Run the following command to create the custom resource.

    cpd-cli manage apply-cr \
    --components=wml \
    --release=${VERSION} \
    --cpd_instance_ns=${PROJECT_CPD_INST_OPERANDS} \
    --block_storage_class=${STG_CLASS_BLOCK} \
    --file_storage_class=${STG_CLASS_FILE} \
    --license_acceptance=true \
    --upgrade=true

    NetApp Trident
    Remember: When you use NetApp Trident storage, both ${STG_CLASS_BLOCK} and ${STG_CLASS_FILE} point to the same storage class.

    Run the following command to create the custom resource.

    cpd-cli manage apply-cr \
    --components=wml \
    --release=${VERSION} \
    --cpd_instance_ns=${PROJECT_CPD_INST_OPERANDS} \
    --block_storage_class=${STG_CLASS_BLOCK} \
    --file_storage_class=${STG_CLASS_FILE} \
    --license_acceptance=true \
    --upgrade=true

Validating the upgrade

Watson Machine Learning is upgraded when the apply-cr command returns:
[SUCCESS]... The apply-cr command ran successfully

If you want to confirm that the custom resource status is Completed, you can run the cpd-cli manage get-cr-status command:

cpd-cli manage get-cr-status \
--cpd_instance_ns=${PROJECT_CPD_INST_OPERANDS} \
--components=wml

What to do next

No post-upgrade steps. The service is ready to use.