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rebase: bump k8s.io/kubernetes in the k8s-dependencies group

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Bumps the k8s-dependencies group with 1 update: [k8s.io/kubernetes](https://github.com/kubernetes/kubernetes).

Updates `k8s.io/kubernetes` from 1.32.3 to 1.33.0
- [Release notes](https://github.com/kubernetes/kubernetes/releases)
- [Commits](https://github.com/kubernetes/kubernetes/compare/v1.32.3...v1.33.0)

---
updated-dependencies:
- dependency-name: k8s.io/kubernetes
  dependency-version: 1.33.0
  dependency-type: direct:production
  update-type: version-update:semver-minor
  dependency-group: k8s-dependencies
...

Signed-off-by: dependabot[bot] <support@github.com>
Signed-off-by: Niels de Vos <ndevos@ibm.com>
This commit is contained in:
dependabot[bot]
2025-04-28 22:16:28 +00:00
committed by mergify[bot]
parent 4147d5d15a
commit 51895f8619
699 changed files with 51590 additions and 17096 deletions
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30
vendor/k8s.io/api/autoscaling/v2/generated.proto generated vendored
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@ -112,12 +112,18 @@ message HPAScalingPolicy {
optional int32 periodSeconds = 3;
}
// HPAScalingRules configures the scaling behavior for one direction.
// These Rules are applied after calculating DesiredReplicas from metrics for the HPA.
// HPAScalingRules configures the scaling behavior for one direction via
// scaling Policy Rules and a configurable metric tolerance.
//
// Scaling Policy Rules are applied after calculating DesiredReplicas from metrics for the HPA.
// They can limit the scaling velocity by specifying scaling policies.
// They can prevent flapping by specifying the stabilization window, so that the
// number of replicas is not set instantly, instead, the safest value from the stabilization
// window is chosen.
//
// The tolerance is applied to the metric values and prevents scaling too
// eagerly for small metric variations. (Note that setting a tolerance requires
// enabling the alpha HPAConfigurableTolerance feature gate.)
message HPAScalingRules {
// stabilizationWindowSeconds is the number of seconds for which past recommendations should be
// considered while scaling up or scaling down.
@ -134,10 +140,28 @@ message HPAScalingRules {
optional string selectPolicy = 1;
// policies is a list of potential scaling polices which can be used during scaling.
// At least one policy must be specified, otherwise the HPAScalingRules will be discarded as invalid
// If not set, use the default values:
// - For scale up: allow doubling the number of pods, or an absolute change of 4 pods in a 15s window.
// - For scale down: allow all pods to be removed in a 15s window.
// +listType=atomic
// +optional
repeated HPAScalingPolicy policies = 2;
// tolerance is the tolerance on the ratio between the current and desired
// metric value under which no updates are made to the desired number of
// replicas (e.g. 0.01 for 1%). Must be greater than or equal to zero. If not
// set, the default cluster-wide tolerance is applied (by default 10%).
//
// For example, if autoscaling is configured with a memory consumption target of 100Mi,
// and scale-down and scale-up tolerances of 5% and 1% respectively, scaling will be
// triggered when the actual consumption falls below 95Mi or exceeds 101Mi.
//
// This is an alpha field and requires enabling the HPAConfigurableTolerance
// feature gate.
//
// +featureGate=HPAConfigurableTolerance
// +optional
optional .k8s.io.apimachinery.pkg.api.resource.Quantity tolerance = 4;
}
// HorizontalPodAutoscaler is the configuration for a horizontal pod