select {
		case <-ticker.C:
		case <-done:
			return
		}
	}
}

// DataUsageInfoHandler - GET /minio/admin/v3/datausage?capacity={true}
// ----------
// Get server/cluster data usage info
func (a adminAPIHandlers) DataUsageInfoHandler(w http.ResponseWriter, r *http.Request) {
	ctx := r.Context()

	objectAPI, _ := validateAdminReq(ctx, w, r, policy.DataUsageInfoAdminAction)

- All versioned buckets maintain the same order for "versions" for each object after being decommissioned to the other pools.
- A pool interrupted during the decommission process, such as for a cluster restart, resumes from where it left off.

## How to decommission a pool

```
λ mc admin decommission start alias/ http://minio{1...2}/data{1...4}
```

## Status decommissioning a pool

			Optional:    true,
			Type:        "path",
			Sensitive:   true,
		},
		config.HelpKV{
			Key:         KafkaVersion,
			Description: "specify the version of the Kafka cluster",
			Optional:    true,
			Type:        "string",
		},
		config.HelpKV{
			Key:         QueueSize,
			Description: "configure channel queue size for Kafka targets",
			Optional:    true,

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",
			 -->

  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(

	// Transport configured with proxy_url if set optionally.
	transport http.RoundTripper

	// The subnet base URL
	BaseURL string
}

var configLock sync.RWMutex

// Registered indicates if cluster is registered or not
func (c *Config) Registered() bool {
	configLock.RLock()
	defer configLock.RUnlock()

	return len(c.APIKey) > 0
}

            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();