Viewing Operator metrics
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.
Accessing performance metrics
You can access the metrics and run queries by using the OKD web console.
Procedure
Select the Administrator perspective in the OKD web console.
Select Observe → Metrics.
To create a custom query, add your PromQL query to the Expression field.
To add multiple queries, select Add Query.
Provided Operator metrics
The Custom Metrics Autoscaler Operator exposes the following metrics, which you can view by using the OKD web console.
Metric name | Description |
---|---|
| Whether the particular scaler is active or inactive. A value of |
| The current value for each scaler’s metric, which is used by the Horizontal Pod Autoscaler (HPA) in computing the target average. |
| The latency of retrieving the current metric from each scaler. |
| The number of errors that have occurred for each scaler. |
| The total number of errors encountered for all scalers. |
| The number of errors that have occurred for each scaled obejct. |
| The total number of Custom Metrics Autoscaler custom resources in each namespace for each custom resource type. |
| 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 |
---|---|
| The number of scaled object validations. |
| The number of validation errors. |