- Seccomp support has graduated to GA. A new `seccompProfile` field is added...

### Bug or Regression

- (PodSecurity admission) errors validating workload resources (deployment, replicaset, etc.) no longer block admission. ([#106017](https://github.com/kubernetes/kubernetes/pull/106017), [@tallclair](https://github.com/tallclair)) [SIG Auth]

With cluster-wide seccomp defaults, the kubelet uses the `RuntimeDefault` seccomp profile by default, rather than than `Unconfined`. This allows enhancing the default cluster wide workload security of the Kubernetes deployment. Security administrators will now sleep better knowing there is some security by default for the workloads.

  select the same set of Pods, scaling now will be disabled for those HPAs with
  the reason `AmbiguousSelector`. This change also covers a case when multiple HPAs
  point to the same deployment.'
   ([#112011](https://github.com/kubernetes/kubernetes/pull/112011), [@pbeschetnov](https://github.com/pbeschetnov))
- 'Pod Security admission: the pod-security `warn` level will now default to
  the `enforce` level.'

- The deprecated kube-controller-manager flag '--deployment-controller-sync-period' has been removed, it is not used by the deployment controller. ([#107178](https://github.com/kubernetes/kubernetes/pull/107178), [@SataQiu](https://github.com/SataQiu))

## Major Features and Improvements

TensorFlow 2.0 focuses on **simplicity** and **ease of use**, featuring updates
like:

*   Easy model building with Keras and eager execution.
*   Robust model deployment in production on any platform.
*   Powerful experimentation for research.
*   API simplification by reducing duplication and removing deprecated
    endpoints.

For details on best practices with 2.0, see