From 7ff6cbb63b8bbd7a975e9479dc77ce20f9d64adb Mon Sep 17 00:00:00 2001 From: geoffrey1330 Date: Mon, 16 Oct 2023 10:57:25 +0100 Subject: [PATCH] Improved keda_scaled_object_pause details in the docs Signed-off-by: geoffrey1330 --- content/docs/2.11/operate/prometheus.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/content/docs/2.11/operate/prometheus.md b/content/docs/2.11/operate/prometheus.md index e35ea4b45..612e3a9b8 100644 --- a/content/docs/2.11/operate/prometheus.md +++ b/content/docs/2.11/operate/prometheus.md @@ -12,12 +12,12 @@ The KEDA Operator exposes Prometheus metrics which can be scraped on port `8080` - `keda_build_info` - Info metric, with static information about KEDA build like: version, git commit and Golang runtime info. - `keda_scaler_active` - This metric marks whether the particular scaler is active (value == 1) or in-active (value == 0). +- `keda_scaled_object_paused` - The paused ScaledObjects in Prometheus metrics (using the annotation detailed [here](https://keda.sh/docs/latest/concepts/scaling-deployments/#pause-autoscaling)) - `keda_scaler_metrics_value` - The current value for each scaler's metric that would be used by the HPA in computing the target average. - `keda_scaler_metrics_latency` - The latency of retrieving 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 ScaledObejct. -- `keda_scaled_object_paused` - The number of paused scaledObject (using the annotation detailed [here](https://keda.sh/docs/latest/concepts/scaling-deployments/#pause-autoscaling)) - `keda_resource_totals` - Total number of KEDA custom resources per namespace for each custom resource type (CRD). - `keda_trigger_totals` - Total number of triggers per trigger type. - `keda_internal_scale_loop_latency` - Total deviation (in miliseconds) between the expected execution time and the actual execution time for the scaling loop. This latency could be produced due to accumulated scalers latencies or high load. This is an internal metric.