Manually create PriorityClass

The operator no longer installs the required `PriorityClass` that is used by dynamically created training and precheck jobs.

In environments where the `PriorityClass` is not present, these jobs might fail to start, thereby affecting the following features.

The following algorithms dynamically create training or precheck jobs and require the `PriorityClass`:

Similar Incident
Change Risk
Deprecated Log Anomaly Detection

If the required `PriorityClass` does not exist in the cluster, the training or precheck jobs created by these algorithms will fail, as in earlier versions, the operator created the required `PriorityClass` during installation. However, starting with version 4.13.0 the operator no longer creates cluster-scoped resources by default in order to comply with environments that restrict cluster-level permissions for operators.

The `PriorityClass` must now be created manually by a cluster administrator if these algorithms are used.

Important:

Manual creation of the `PriorityClass` is required in the following scenarios:

New installations of version 4.13.0 (or later)
Clusters where the `PriorityClass` does not already exist

Existing clusters that already have this `PriorityClass` from previous versions do not require any action.

Create the PriorityClass YAML

Save the following definition in a file named `aimanager-training-priorityclass.yaml`.

apiVersion: scheduling.k8s.io/v1
kind: PriorityClass
metadata:
  name: aimanager-aio-training-priority
description: This priority class should be used for training pods only.
value: 1
preemptionPolicy: Never

Apply the YAML to the Cluster

For Kubernetes:

bash kubectl apply -f aimanager-training-priorityclass.yaml

For OpenShift:

bash oc apply -f aimanager-training-priorityclass.yaml

Verify the PriorityClass
Verify that the `PriorityClass` was created successfully:
```
bash kubectl get priorityclass
```
The output should include:
```
aimanager-aio-training-priority
```