Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Clarify pollingInterval and Caching Metrics #1483

Open
wants to merge 2 commits into
base: main
Choose a base branch
from
Open

Clarify pollingInterval and Caching Metrics #1483

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
9f8d4a1
Clarify pollingInterval
rickbrouwer Oct 8, 2024
86e1f58
Clarify caching metrics
rickbrouwer Oct 9, 2024
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
2 changes: 1 addition & 1 deletion content/docs/2.16/concepts/scaling-deployments.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -39,7 +39,7 @@ The only constraint is that the target `Custom Resource` must define `/scale` [s

This feature enables caching of metric values during polling interval (as specified in `.spec.pollingInterval`). Kubernetes (HPA controller) asks for a metric every few seconds (as defined by `--horizontal-pod-autoscaler-sync-period`, usually 15s), then this request is routed to KEDA Metrics Server, that by default queries the scaler and reads the metric values. Enabling this feature changes this behavior such that KEDA Metrics Server tries to read metric from the cache first. This cache is updated periodically during the polling interval.

Enabling this feature can significantly reduce the load on the scaler service.
Enabling [`useCachedMetrics`](../reference/scaledobject-spec/#triggers) can significantly reduce the load on the scaler service.

This feature is not supported for `cpu`, `memory` or `cron` scaler.

Expand Down
8 changes: 6 additions & 2 deletions content/docs/2.16/reference/scaledobject-spec.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -70,11 +70,15 @@ To scale Kubernetes Deployments only `name` need be specified. To scale a differ
```yaml
pollingInterval: 30 # Optional. Default: 30 seconds
```

This is the interval to check each trigger on. By default, KEDA will check each trigger source on every ScaledObject every 30 seconds.

**Example:** in a queue scenario, KEDA will check the queueLength every `pollingInterval`, and scale the resource up or down accordingly.
When scaling from 0 to 1, the polling interval is controlled by KEDA. For example, if this parameter is set to `60`, KEDA will poll for a metric value every 60 seconds while the number of replicas is 0.

While scaling from 1 to N, on top of KEDA, the HPA will also poll regularly for metrics, based on the [`--horizontal-pod-autoscaler-sync-period`](https://kubernetes.io/docs/reference/command-line-tools-reference/kube-controller-manager/#options) parameter to the `kube-controller-manager`, which by default is 15 seconds. For example, if the `kube-controller-manager` was started with `--horizontal-pod-autoscaler-sync-period=30`, the HPA will poll for a metric value every 30 seconds while the number of replicas is between 1 and N.

If you want respect the polling interval, the feature [`caching metrics`](../concepts/scaling-deployments/#caching-metrics) enables caching of metric values during polling interval.

**Example:** in a queue scenario, KEDA will check the queueLength every `pollingInterval` while the number of replicas is 0, and scale the resource up an down accordingly.

## cooldownPeriod
```yaml
Expand Down
Loading