system that operates at large scale and in heterogeneous environments. TensorFlow uses dataflow graphs to represent computation, shared state, and the operations that mutate that state. It maps the nodes of a dataflow graph across many machines in a cluster, and within a machine across multiple computational devices, including multicore CPUs, general purpose GPUs, and custom-designed ASICs known as Tensor Processing Units (TPUs). This architecture gives flexibility to the application developer, whereas...

            settingsBuilder.put("discovery.type", "single-node");
            // settingsBuilder.putList("discovery.seed_hosts", "127.0.0.1:9301");
            // settingsBuilder.putList("cluster.initial_master_nodes", "127.0.0.1:9301");
        }).build(newConfigs().clusterName("ArraySettingsTest").numOfNode(1)
                .pluginTypes("org.codelibs.opensearch.extension.ExtensionPlugin"));
        runner.ensureYellow();

            settingsBuilder.put("discovery.type", "single-node");
            // settingsBuilder.putList("discovery.seed_hosts", "127.0.0.1:9301");
            // settingsBuilder.putList("cluster.initial_master_nodes", "127.0.0.1:9301");
        }).build(newConfigs().clusterName("ESSourceReaderTest").numOfNode(1)
                .pluginTypes("org.codelibs.opensearch.extension.ExtensionPlugin"));
        runner.ensureYellow();

		<property name="settings">
			{"http.cors.enabled":"true",
			 "http.cors.allow-origin":"*",
			 "discovery.type":"single-node",
			 "cluster.allocator.existing_shards_allocator.batch_enabled":"true",
			 <!--
			 "node.name":"search_engine",
			 "discovery.seed_hosts":"search_engine",
			 "cluster.initial_cluster_manager_nodes":"search_engine",
			 "node.roles":"cluster_manager,data,ingest,ml",
			 -->

}
```

## 4. Enable ILM transition feature

  TFE_Context* ctx = TFE_NewContext(opts, status);
  EXPECT_EQ(TF_GetCode(status), TF_OK) << TF_Message(status);

  server_def.set_task_index(0);
  auto cluster = server_def.mutable_cluster();
  auto client_job = cluster->add_job();
  client_job->set_name("localhost");
  int client_port = tensorflow::testing::PickUnusedPortOrDie();
  client_job->mutable_tasks()->insert(

- On single-stack configured (IPv4 or IPv6, but not both) clusters, Services which are both headless (no clusterIP) and selectorless (empty or undefined selector) will report `ipFamilyPolicy RequireDualStack` and will have entries in `ipFamilies[]` for both IPv4 and IPv6.  This is a change from...

		return
	}

	if globalSiteReplicationSys.isEnabled() && !v.Enabled() {
		writeErrorResponse(ctx, w, APIError{
			Code:           "InvalidBucketState",
			Description:    "Cluster replication is enabled on this site, versioning cannot be suspended on bucket.",
			HTTPStatusCode: http.StatusBadRequest,
		}, r.URL)
		return
	}

	// activity initiated from this cluster
	ReplicationStatus = "replication-status"
	// ReplicationTimestamp - the last time replication was initiated on this cluster for this object version
	ReplicationTimestamp = "replication-timestamp"
	// ReplicaStatus - this header is present if a replica was received by this cluster for this object version
	ReplicaStatus = "replica-status"

declaratively. It handles versioning, multiple simultaneous rollouts,
aggregating status across all pods, maintaining application availability, and
rollback.
  * <strong>Automated cluster management: </strong>
     * Kubernetes clusters can now span zones within a cloud provider. Pods from a
service will be automatically spread across zones, enabling applications to
tolerate zone failure.