grafana-replication-cluster.png...

the Cluster Autoscaler, which provides improved performance and error reporting.

[SIG Autoscaling]: https://github.com/kubernetes/community/tree/master/sig-autoscaling

### SIG Cluster Lifecycle

[SIG Cluster Lifecycle][] is responsible for the user experience of deploying,
upgrading, and deleting clusters.

For the 1.8 release, SIG Cluster Lifecycle continued to focus on expanding the

- E2e framework: the `node-role.kubernetes.io/master` taint has been removed from the default value of `--non-blocking-taints` flag. You may need to set `--non-blocking-taints` explicitly if the cluster to be tested has nodes with the deprecated `node-role.kubernetes.io/master` taint. ([#118510](https://github.com/kubernetes/kubernetes/pull/118510), [@SataQiu](https://github.com/SataQiu)) [SIG Testing]

- [KCCM - service controller]: enable connection draining for terminating pods upon node downscale by the cluster autoscaler. This is done by not reacting to the taint used by the cluster autoscaler to indicate that the node is going away soon, thus keeping the node referenced by the load balancer until the VM has been completely...

### Other (Cleanup or Flake)

  // be dropped.) The default value, "Cluster", uses the standard behavior of
  // routing to all endpoints evenly (possibly modified by topology and other
  // features). Note that traffic sent to an External IP or LoadBalancer IP from
  // within the cluster will always get "Cluster" semantics, but clients sending to
  // a NodePort from within the cluster may need to take traffic policy into account

Kubeadm: deploy a separate "super-admin.conf" file. The User in "admin.conf" is now bound to a new RBAC Group "kubeadm:cluster-admins" that have "cluster-admin" ClusterRole access. The User in "super-admin.conf" is bound to the "system:masters" built-in super-powers / break-glass Group that can bypass RBAC. Before this change the default "admin.conf" was bound to "system:masters" Group which was undesired. Executing "kubeadm init phase kubeconfig all" or just "kubeadm init" will now generate the...

</p>

<pre>
switch tag {
default: s3()
case 0, 1, 2, 3: s1()
case 4, 5, 6, 7: s2()
}

switch x := f(); {  // missing switch expression means "true"
case x &lt; 0: return -x
default: return x
}

switch {
case x &lt; y: f1()
case x &lt; z: f2()
case x == 4: f3()
}
</pre>

<p>

* Improved **correctness** in corner cases.
* **Safer** types.
* Better **performance** and **less energy** consumption.
* Better **extensibility**.
* etc.

...all this while keeping the **same Python API**. In most of the cases, for simple models, you can simply upgrade the Pydantic version and get all the benefits. 🚀