Installing Watson AIOps AI Manager

Follow these instructions to prepare your cluster to install IBM Watson® AIOps AI Manager.

AI Manager (formerly known as IBM Watson AIOps) applies AI to structured and unstructured data from applications and infrastructure components of your IT landscape to analyze and inform your IT operations team about issues as they emerge. You can train models to read and analyze logs, events, and other incident data, to discover and correlate anomalies across components, and to localize faults. The models can provide these insights through a ChatOps interface (Slack) to help your IT operations teams to understand the nature and impact of issues, and to guide and inform short-term remedies and permanent resolutions.

Deciding how you want to install AI Manager

Deploy multiple AI Manager service instances on a single Red Hat® OpenShift® cluster, but in separate IBM Cloud Pak for Data installations, and in different Red Hat OpenShift projects (namespaces). If you choose this option, see Installing the Watson AIOps AI Manager service component.
Deploy multiple AI Manager service instances within the same IBM Cloud Pak for Data installation, and with a separate install for each service instance.

To deploy each service instance to a separate project (namespace), you can create a tethered project for the service instance during installation. The service instance in the tethered project can be managed by IBM Cloud Pak for Data, but is otherwise isolated from IBM Cloud Pak for Data and the other services that run in the IBM Cloud Pak for Data project. For more information, see Architecture for IBM Cloud Pak for Data: Tethered projects.

Note: If you choose this option, you must specify the --tether-to flag during installation.

Ensure that you have proper permissions on the cluster and that IBM Cloud Pak for Data is installed.