sconfig.Metadata.Retry.Backoff = (10 * time.Second)
	sconfig.Metadata.RefreshFrequency = (15 * time.Minute)

	h.config = sconfig

	var brokers []string
	for _, broker := range h.kconfig.Brokers {
		brokers = append(brokers, broker.String())
	}

	client, err := sarama.NewClient(brokers, sconfig)
	if err != nil {
		return err
	}

	producer, err := sarama.NewSyncProducerFromClient(client)
	if err != nil {

				break
			}
			brokers = append(brokers, *host)
		}
		if err != nil {
			return cfg, err
		}

		clientAuthCfgVal := getCfgVal(EnvKafkaTLSClientAuth, k, kv.Get(KafkaTLSClientAuth))
		clientAuth, err := strconv.Atoi(clientAuthCfgVal)
		if err != nil {
			return cfg, err
		}

		kafkaArgs := kafka.Config{
			Enabled: enabled,
			Brokers: brokers,

namespace {

TEST(CAPI_EXPERIMENTAL, GetServerDefTest) {
  const string expected_text_proto(R"(cluster {
  job {
    name: "worker"
    tasks {
      key: 0
      value: "tpuserver:0"
    }
    tasks {
      key: 1
      value: "localhost:1"
    }
  }
}
job_name: "worker"
task_index: 1
protocol: "grpc"
)");

  TF_Status* status = TF_NewStatus();

Hier sind einige mögliche Kombinationen und Strategien:

* **Gunicorn**, welches **Uvicorn-Worker** managt
    * Gunicorn wäre der **Prozessmanager**, der die **IP** und den **Port** überwacht, die Replikation würde durch **mehrere Uvicorn-Workerprozesse** erfolgen
* **Uvicorn**, welches **Uvicorn-Worker** managt

```console
$ pip install "hypercorn[trio]"
---> 100%
```

</div>

### Exécuter avec Trio

Ensuite, vous pouvez passer l'option de ligne de commande `--worker-class` avec la valeur `trio` :

<div class="termy">

```console
$ hypercorn main:app --worker-class trio
```

</div>

Et cela démarrera Hypercorn avec votre application en utilisant Trio comme backend.

```console
$ pip install "hypercorn[trio]"
---> 100%
```

</div>

### Mit Trio ausführen

Dann können Sie die Befehlszeilenoption `--worker-class` mit dem Wert `trio` übergeben:

<div class="termy">

```console
$ hypercorn main:app --worker-class trio
```

</div>

Und das startet Hypercorn mit Ihrer Anwendung und verwendet Trio als Backend.

### AWS

* Add AWS cloud provider option to use an assumed IAM role. For example, this allows running Controller Manager in a account separate from the worker nodes, but still allows all resources created to interact with the workers. ELBs created would be in the same account as the worker nodes for instance.([#59668](https://github.com/kubernetes/kubernetes/pull/59668), [@brycecarman](https://github.com/brycecarman))

			Key:   config.Enable,
			Value: config.EnableOn,
		},
		config.KV{
			Key: target.KafkaBrokers,
			Value: func() string {
				var brokers []string
				for _, broker := range cfg.Brokers {
					brokers = append(brokers, broker.String())
				}
				return strings.Join(brokers, config.ValueSeparator)
			}(),
		},
		config.KV{
			Key:   target.KafkaTopic,
			Value: cfg.Topic,
		},
		config.KV{

      TF_NewStatus(), TF_DeleteStatus);
  std::unique_ptr<TFE_Context, decltype(&TFE_DeleteContext)> context(
      TFE_NewContext(opts.get(), status.get()), TFE_DeleteContext);
  tensorflow::ServerDef server_def = GetServerDef("worker", 3);

  // This server def has the task index set to 0.
  std::string serialized = server_def.SerializeAsString();

  server_def.set_task_index(1);
  std::unique_ptr<tensorflow::GrpcServer> worker_server1;

    - Windows kube-proxy will wait for HNS network creation on start ([#78612](https://github.com/kubernetes/kubernetes/pull/78612), [@ksubrmnn](https://github.com/ksubrmnn))