Configure background worker scaling

Configure resource limits and autoscaling for the background worker pods that execute built-in workflows.

Before you begin

You have cluster administrator access to the OpenShift cluster running the automation orchestrator.
You have installed the automation orchestrator operator and have a running AutomationOrchestrator instance.

Open the AutomationOrchestrator custom resource (CR) for editing:
```
$ oc edit automationorchestrator instance-name -n namespace
```
Add or modify the spec.backgroundWorker section:
```
spec:
  backgroundWorker:
    resources:
      requests:
        cpu: 250m
        memory: 256Mi
      limits:
        memory: 1Gi
    hpa:
      minReplicas: 2
      maxReplicas: 5
      targetCPUUtilization: 80
```
- resources sets the CPU and memory requests and limits for each pod.
- hpa.minReplicas sets the minimum number of background worker pods. The Horizontal Pod Autoscaler (HPA) manages replica count exclusively.
- hpa.maxReplicas sets the maximum number of background worker pods the HPA scales to.
- hpa.targetCPUUtilization sets the target CPU utilization percentage that triggers scaling. Defaults to 80 if omitted.
Note:

Do not set spec.backgroundWorker.replicas directly. The operator ignores this field because the HPA manages replica count. Setting it emits a ReplicasIgnored warning event.
Save the CR.

The operator detects the change and performs a rolling update of the background worker deployment.

Verify that the HPA reflects the values you configured:

$ oc get hpa instance-name-background-worker -n namespace

Confirm that MINPODS and MAXPODS match the hpa.minReplicas and hpa.maxReplicas values you configured.

Verify that the background worker pods are running:

$ oc get pods -n namespace -l app.kubernetes.io/component=background-worker