This is a cache of https://docs.openshift.com/rosa/nodes/cma/nodes-cma-autoscaling-custom-metrics.html. It is a snapshot of the page at 2024-11-30T03:18:52.503+0000.
Viewing Operator metrics - Automatically scaling pods with the Custom Metrics Autoscaler Operator | Nodes | Red Hat OpenShift Service on AWS
    OpenShift docs are moving and will soon only be available at docs.redhat.com, the home of all Red Hat product documentation. Explore the new docs experience today.
  1. Documentation
    2. history bug_report picture_as_pdf
×

Viewing Operator metrics

edit

The Custom Metrics Autoscaler Operator exposes ready-to-use metrics that it pulls from the on-cluster monitoring component. You can query the metrics by using the Prometheus Query Language (PromQL) to analyze and diagnose issues. All metrics are reset when the controller pod restarts.

edit

Accessing performance metrics

You can access the metrics and run queries by using the Red Hat OpenShift Service on AWS web console.

Procedure

  1. Select the Administrator perspective in the Red Hat OpenShift Service on AWS web console.

  2. Select Observe → Metrics.

  3. To create a custom query, add your PromQL query to the Expression field.

  4. To add multiple queries, select Add Query.

edit

Provided Operator metrics

The Custom Metrics Autoscaler Operator exposes the following metrics, which you can view by using the Red Hat OpenShift Service on AWS web console.

Table 1. Custom Metric Autoscaler Operator metrics
Metric name Description

keda_scaler_activity

Whether the particular scaler is active or inactive. A value of 1 indicates the scaler is active; a value of 0 indicates the scaler is inactive.

keda_scaler_metrics_value

The current value for each scaler’s metric, which is used by the Horizontal Pod Autoscaler (HPA) in computing the target average.

keda_scaler_metrics_latency

The latency of retrieving the current metric from each scaler.

keda_scaler_errors

The number of errors that have occurred for each scaler.

keda_scaler_errors_total

The total number of errors encountered for all scalers.

keda_scaled_object_errors

The number of errors that have occurred for each scaled obejct.

keda_resource_totals

The total number of Custom Metrics Autoscaler custom resources in each namespace for each custom resource type.

keda_trigger_totals

The total number of triggers by trigger type.
Custom Metrics Autoscaler Admission webhook metrics

The Custom Metrics Autoscaler Admission webhook also exposes the following Prometheus metrics.

Metric name Description

keda_scaled_object_validation_total

The number of scaled object validations.

keda_scaled_object_validation_errors

The number of validation errors.