echo "${KUBERNETES_CNI} is not recognized. Supported options are \"calico\" or do not set the variable to use default."
      return 1
      ;;
  esac

  # If metrics server configuration directory is specified then deploy in
  # the cluster just created
  if [[ -n ${METRICS_SERVER_CONFIG_DIR:-} ]]; then
    retry kubectl apply -f "${METRICS_SERVER_CONFIG_DIR}"
  fi

* The implicit registration of Prometheus metrics for request count and latency have been removed, and a plug-able interface was added. If you were using our client libraries in your own binaries and want these metrics, add the following to your imports in the main package: "k8s.io/pkg/client/metrics/prometheus".  ([#30638](https://github.com/kubernetes/kubernetes/pull/30638), [@krousey](https://github.com/krousey))

		func(ctx context.Context) (info DiskInfo, err error) {
			ctx, cancel := context.WithTimeout(ctx, 5*time.Second)
			defer cancel()

			nopts := DiskInfoOptions{DiskID: *client.diskID.Load(), Metrics: true}
			infop, err := storageDiskInfoRPC.Call(ctx, client.gridConn, &nopts)
			if err != nil {
				return info, toStorageErr(err)
			}
			info = *infop
			if info.Error != "" {

pkg runtime/metrics, const KindBad = 0
pkg runtime/metrics, const KindBad ValueKind
pkg runtime/metrics, const KindFloat64 = 2
pkg runtime/metrics, const KindFloat64 ValueKind
pkg runtime/metrics, const KindFloat64Histogram = 3
pkg runtime/metrics, const KindFloat64Histogram ValueKind
pkg runtime/metrics, const KindUint64 = 1
pkg runtime/metrics, const KindUint64 ValueKind

 * limitations under the License.
 */
package okhttp3

import java.io.IOException
import java.net.InetAddress
import java.net.InetSocketAddress
import java.net.Proxy

/**
 * Listener for metrics events. Extend this class to monitor the quantity, size, and duration of
 * your application's HTTP calls.
 *
 * All start/connect/acquire events will eventually receive a matching end/release event, either

- The nftables kube-proxy mode now has its own metrics rather than reporting
  metrics with "iptables" in their names. ([#124557](https://github.com/kubernetes/kubernetes/pull/124557), [@danwinship](https://github.com/danwinship)) [SIG Network and Windows]

func (z *erasureServerPools) LocalStorageInfo(ctx context.Context, metrics bool) StorageInfo {
	var storageInfo StorageInfo

	storageInfos := make([]StorageInfo, len(z.serverPools))
	g := errgroup.WithNErrs(len(z.serverPools))
	for index := range z.serverPools {
		index := index
		g.Go(func() error {
			storageInfos[index] = z.serverPools[index].LocalStorageInfo(ctx, metrics)
			return nil
		}, index)
	}

			req.URL.Path == healthCheckPathPrefix+healthCheckClusterPath ||
			req.URL.Path == healthCheckPathPrefix+healthCheckClusterReadPath)
}

// guessIsMetricsReq - returns true if incoming request looks
// like metrics request
func guessIsMetricsReq(req *http.Request) bool {
	if req == nil {
		return false
	}
	aType := getRequestAuthType(req)
	return (aType == authTypeAnonymous || aType == authTypeJWT) &&

### Autoscaling
* **[alpha]** The Horizontal Pod Autoscaler now supports drawing metrics through the API server aggregator.
* **[alpha]** The Horizontal Pod Autoscaler now supports scaling on multiple, custom metrics.
* Cluster Autoscaler publishes its status to kube-system/cluster-autoscaler-status ConfigMap.

* **Bilgisayar görüsü**: bir görüntü milyonlarca pikselden oluşur, her pikselin 3 değeri / rengi vardır, bu pikseller üzerinde aynı anda bir şeyler hesaplamayı gerektiren işleme.
* **Makine Öğrenimi**: Çok sayıda "matris" ve "vektör" çarpımı gerektirir. Sayıları olan ve hepsini aynı anda çarpan büyük bir elektronik tablo düşünün.