* Addon manager supports HA masters. ([#55782](https://github.com/kubernetes/kubernetes/pull/55782), [@x13n](https://github.com/x13n))

- Restore the ability to `kubectl apply --prune` without --namespace flag.  Since 1.17, `kubectl apply --prune` only prunes resources in the default namespace (or from kubeconfig) or explicitly specified in command line flag.  But this is s breaking change from kubectl 1.16, which can prune resources in all namespace in config file.  This patch restores the kubectl 1.16 behaviour. ([#89551](https://github.com/kubernetes/kubernetes/pull/89551),...

- Existing InTree AzureFile PVs which don't have a secret namespace defined will now work properly after enabling CSI migration - the namespace will be obtained from ClaimRef. ([#108000](https://github.com/kubernetes/kubernetes/pull/108000), [@RomanBednar](https://github.com/RomanBednar)) [SIG Cloud Provider and Storage]

		Namespace: namespace,
		Subsystem: replicationSubsystem,
		Name:      lastHourFailedBytes,
		Help:      "Total number of bytes failed at least once to replicate in the last hour",
		Type:      gaugeMetric,
	}
}

func getRepFailedOperationsLastHourMD(namespace MetricNamespace) MetricDescription {
	return MetricDescription{
		Namespace: namespace,
		Subsystem: replicationSubsystem,
		Name:      lastHourFailedCount,

{{ template "minio.fullname" . }}.{{ .Release.Namespace }}.{{ .Values.clusterDomain }}

To access MinIO from localhost, run the below commands:

  1. export POD_NAME=$(kubectl get pods --namespace {{ .Release.Namespace }} -l "release={{ .Release.Name }}" -o jsonpath="{.items[0].metadata.name}")

  2. kubectl port-forward $POD_NAME 9000 --namespace {{ .Release.Namespace }}

#include <utility>

#include "tensorflow/c/eager/abstract_function.h"
#include "tensorflow/core/framework/function.h"
#include "tensorflow/core/platform/status.h"

namespace tensorflow {
namespace tracing {
namespace graph {
GraphFunction::GraphFunction(FunctionDef fdef)
    : AbstractFunction(kGraph),
      func_record_(new FunctionRecord(std::move(fdef), {}, true)) {}
GraphFunction::~GraphFunction() {}

#include "tensorflow/c/tf_status_helper.h"
#include "tensorflow/c/tf_tensor.h"
#include "tensorflow/core/platform/tensor_float_32_utils.h"
#include "tensorflow/core/platform/test.h"

namespace tensorflow {
namespace gradients {
namespace internal {
namespace {

using tensorflow::TF_StatusPtr;

void CompareNumericalAndManualGradients(
    Model model, AbstractContext* ctx,

ServiceAccount metadata: name: {{ .Values.serviceAccount.name | quote }} namespace: {{ .Release.Namespace | quote }} {{- end -}} minio/templates/servicemonitor.yaml {{- if .Values.metrics.serviceMonitor.enabled }} apiVersion: monitoring.coreos.com/v1 kind: ServiceMonitor metadata: name: {{ template "minio.fullname" . }} {{- if .Values.metrics.serviceMonitor.namespace }} namespace: {{ .Values.metrics.serviceMonitor.namespace }} {{ else }} namespace: {{ .Release.Namespace | quote }} {{- end }} labels: app: {{...

on the following DNS name from within your cluster: {{ template "minio.fullname" . }}.{{ .Release.Namespace }}.svc.cluster.local To access MinIO from localhost, run the below commands: 1. export POD_NAME=$(kubectl get pods --namespace {{ .Release.Namespace }} -l "release={{ .Release.Name }}" -o jsonpath="{.items[0].metadata.name}") 2. kubectl port-forward $POD_NAME 9000 --namespace {{ .Release.Namespace }} Read more about port forwarding here: http://kubernetes.io/docs/user-guide/kubectl/kubectl_port-forward/...

#define TENSORFLOW_C_EAGER_GRAPH_FUNCTION_H_

#include "tensorflow/c/eager/abstract_function.h"
#include "tensorflow/core/framework/function.h"
#include "tensorflow/core/platform/refcount.h"
namespace tensorflow {
namespace tracing {
namespace graph {
using tensorflow::AbstractFunction;
// Thin wrapper around a FunctionDef.
class GraphFunction : public AbstractFunction {
 public:
  explicit GraphFunction(FunctionDef fdef);