- Added SchedulingConstraints to express TAS constraints for pod group scheduling behind TopologyAwareWorkloadScheduling feature gate.
  

- Pod spread constraints have been added in alpha. You can use these constraints to control how Pods are spread across the cluster among failure-domains. ([#77327](https://github.com/kubernetes/kubernetes/pull/77327), [#77760](https://github.com/kubernetes/kubernetes/pull/77760), [#77828](https:/...

- Added `optionalOldSelf` to `x-kubernetes-validations` to support ratcheting CRD schema constraints. ([#121034](https://github.com/kubernetes/kubernetes/pull/121034), [@alexzielenski](https://github.com/alexzielenski))

- New parameter `defaultingType` for `PodTopologySpread` plugin allows to use k8s defined or user provided default constraints ([#95048](https://github.com/kubernetes/kubernetes/pull/95048), [@alculquicondor](https://github.com/alculquicondor)) [SIG Scheduling]

- Revised the logic for DaemonSet rolling update to exclude nodes if scheduling constraints are not met.

- Graduated support for `minDomains` in pod topology spread constraints, to general availability.
  The `MinDomainsInPodTopologySpread` feature gate no longer has any effect, and the field is

  In addition, when this feature is enabled, the 'details' field of 'Status' from the LIST response
  includes information that identifies the corrupt object(s).
  NOTE: unsafe deletion ignores finalizer constraints, and skips precondition checks.
  WARNING: this may break the workload associated with the resource being unsafe-deleted, if it relies on

  Previously, when unschedulable Pods are updated, the scheduler always put Pods back to activeQ/backoffQ. But, actually not all updates to Pods make Pods schedulable, especially considering many scheduling constraints nowadays are immutable.

  matching the spreading selector on those excluded nodes (not matching the node affinity/selector),
  especially when the `topologyKey` is not node-level. Revisit the node affinity and/or pod selector in the
  topology spread constraints to avoid this scenario. ([#107009](https://github.com/kubernetes/kubernetes/pull/107009), [@kerthcet](https://github.com/kerthcet))

multiple clusters ensures that cluster-level autoscalers are
consistently deployed across those clusters, and dynamically managed
to ensure that autoscaling can occur optimially in all clusters,
within a set of global constraints on the total number of replicas
permitted across all clusters.  If replicas are not
required in some clusters due to low system load or insufficient quota
or capacity in those clusters, additional replicas are made available