ortant}.object-fit-contain{-o-object-fit:contain!important;object-fit:contain!important}.object-fit-cover{-o-object-fit:cover!important;object-fit:cover!important}.object-fit-fill{-o-object-fit:fill!important;object-fit:fill!important}.object-fit-scale{-o-object-fit:scale-down!important;object-fit:scale-down!important}.object-fit-none{-o-object-fit:none!important;object-fit:none!important}.opacity-0{opacity:0!important}.opacity-25{opacity:.25!important}.opacity-50{opacity:.5!important}.opacity-7...

- If we set SelectPolicy MinPolicySelect on scaleUp behavior or scaleDown behavior,Horizontal Pod Autoscaler doesn't automatically scale the number of pods correctly ([#95647](https://github.com/kubernetes/kubernetes/pull/95647), [@JoshuaAndrew](https://github.com/JoshuaAndrew)) [SIG Apps and Autoscaling]

* Update etcd 2.2 references to use 3.0.x ([#29399](https://github.com/kubernetes/kubernetes/pull/29399), [@timothysc](https://github.com/timothysc))
* HPA: ignore scale targets whose replica count is 0 ([#29212](https://github.com/kubernetes/kubernetes/pull/29212), [@sjenning](https://github.com/sjenning))

`Policy` optionally took in a `tf.compat.v1.mixed_precision.LossScale` in the constructor, which defaulted to a dynamic loss scale for the `"mixed_float16"` policy and no loss scale for other policies. In `Model.compile`, if the model's policy had a loss scale, the optimizer would be wrapped with a `LossScaleOptimizer`. With the non-experimental `Policy`, there is no loss scale associated with the `Policy`, and `Model.compile` wraps the optimizer with a `LossScaleOptimizer` if and only if the policy...

* add goroutine to move unschedulable pods to activeq if they are not retried for more than 1 minute ([#72558](https://github.com/kubernetes/kubernetes/pull/72558), [@denkensk](https://github.com/denkensk))
* Scale max-inflight limits together with master VM sizes. ([#73268](https://github.com/kubernetes/kubernetes/pull/73268), [@wojtek-t](https://github.com/wojtek-t))

	// can easily eat into the internode bandwidth. This function would be mostly
	// TX saturating, however there are situations where a RX might also saturate.
	// To avoid these problems we must split the work at scale. With 1000 node
	// setup becoming a reality we must try to shard the work properly such as
	// pick 10 nodes that precisely can send those 100 requests the first node

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- When downscaling ReplicaSets, ready and creation timestamps are compared in a logarithmic scale. ([#99212](https://github.com/kubernetes/kubernetes/pull/99212), [@damemi](https://github.com/damemi)) [SIG Apps and Testing]
- When the kubelet is watching a ConfigMap or Secret purely in the context of setting environment variables

- From now on, the HPA controller will return an error for the container resource metrics when the feature gate "HPAContainerMetrics" is disabled. As a result, HPA with a container resource metric performs no scale-down and performs only scale-up based on other metrics. ([#116043](https://github.com/kubernetes/kubernetes/pull/116043), [@sanposhiho](https://github.com/sanposhiho)) [SIG API Machinery, Apps and Autoscaling]

- The validation of `replicas` field in the ReplicationController `/scale` subresource has been migrated to declarative validation.
  If the `DeclarativeValidation` feature gate is enabled, mismatches with existing validation are reported via metrics.