# except HTTPException inside a dependency with yield.
                # This needs to happen after user middlewares because those create a
                # new contextvars context copy by using a new AnyIO task group.
                # This AsyncExitStack preserves the context for contextvars, not
                # strictly necessary for closing files but it was one of the original
                # intentions.

taifun-dns.de

// Tailscale Inc. : https://www.tailscale.com
// Submitted by David Anderson <******@****.***>
ts.net
*.c.ts.net

// TASK geographical domains (https://www.task.gda.pl/uslugi/dns)
gda.pl
gdansk.pl
gdynia.pl
med.pl
sopot.pl

// Tave Creative Corp : https://tave.com/
// Submitted by Adrian Ziemkowski <******@****.***>

dockershim socket unless you are still using kubelet version < 1.24 with kubeadm >= 1.24. Remove the DockerValidor and ServiceCheck for the `docker` service from kubeadm preflight. Docker is no longer special cased during host validation and ideally this task should be done in the now external cri-dockerd project where the importance of the compatibility matters. Use `crictl` for all communication with CRI sockets for actions like pulling images and obtaining a list of running containers instead of using...

* Add validation for CustomResources via JSON Schema. ([#47263](https://github.com/kubernetes/kubernetes/pull/47263), [@nikhita](https://github.com/nikhita))
* enqueue a sync task to wake up jobcontroller to check job ActiveDeadlineSeconds in time ([#48454](https://github.com/kubernetes/kubernetes/pull/48454), [@weiwei04](https://github.com/weiwei04))

* Add validation for CustomResources via JSON Schema. ([#47263](https://github.com/kubernetes/kubernetes/pull/47263), [@nikhita](https://github.com/nikhita))
* enqueue a sync task to wake up jobcontroller to check job ActiveDeadlineSeconds in time ([#48454](https://github.com/kubernetes/kubernetes/pull/48454), [@weiwei04](https://github.com/weiwei04))

        `tf.distribute.InputOptions` for specific options when used with
        distribution.
    *   `tf.keras.experimental.SidecarEvaluator` is now available for a program
        intended to be run on an evaluator task, which is commonly used to
        supplement a training cluster running with
        `tf.distribute.experimental.ParameterServerStrategy` (see
        `https://www.tensorflow.org/tutorials/distribute/parameter_server_training).