}
		}
	}

	processed := map[string]metricsConfig{}
	for provider, modeMap := range providers {
		tmm := processed[provider]
		tmm.ReportingInterval = reportingIntervals[provider]

		for mode, metricMap := range modeMap {
			key := metricProviderModeKey(provider, mode)
			if disabledAllMetricsProviders.Contains(key) {
				switch mode {
				case tpb.WorkloadMode_CLIENT:
					tmm.ClientMetrics.Disabled = true

		return
	}
	ps.proxyStatusMutex.Lock()
	defer ps.proxyStatusMutex.Unlock()

	metricMap, f := ps.ProxyStatus[metric.Name()]
	if !f {
		metricMap = map[string]ProxyPushStatus{}
		ps.ProxyStatus[metric.Name()] = metricMap
	}
	ev := ProxyPushStatus{Message: msg, Proxy: proxyID}
	metricMap[key] = ev
}

var (

	if isResource {
		fakeMetricsClient.AddReactor("list", "pods", func(action core.Action) (handled bool, ret runtime.Object, err error) {
			metrics := &metricsapi.PodMetricsList{}
			for i, containers := range tc.reportedPodMetrics {
				metric := metricsapi.PodMetrics{
					ObjectMeta: metav1.ObjectMeta{
						Name:      fmt.Sprintf("%s-%d", podNamePrefix, i),
						Namespace: namespace,
						Labels:    podLabels,
					},

	v1 "k8s.io/api/core/v1"
	metav1 "k8s.io/apimachinery/pkg/apis/meta/v1"
	"k8s.io/apimachinery/pkg/labels"
	"k8s.io/apimachinery/pkg/runtime/schema"
	customapi "k8s.io/metrics/pkg/apis/custom_metrics/v1beta2"
	metricsapi "k8s.io/metrics/pkg/apis/metrics/v1beta1"
	resourceclient "k8s.io/metrics/pkg/client/clientset/versioned/typed/metrics/v1beta1"
	customclient "k8s.io/metrics/pkg/client/custom_metrics"

			Type:   cadvisorapiv1.MetricCumulative,
			Format: cadvisorapiv1.FloatType,
			Units:  "count",
		},
	}
	timestamp1 := time.Now()
	timestamp2 := time.Now().Add(time.Minute)
	metrics := map[string][]cadvisorapiv1.MetricVal{
		"qos": {
			{
				Timestamp: timestamp1,
				IntValue:  10,
			},
			{
				Timestamp: timestamp2,
				IntValue:  100,
			},
		},
		"cpuLoad": {
			{
				Timestamp:  timestamp1,

	f.Fuzz(&ret)
	return ret
}

func generateCustomMetrics(spec []cadvisorapiv1.MetricSpec) map[string][]cadvisorapiv1.MetricVal {
	ret := map[string][]cadvisorapiv1.MetricVal{}
	for _, metricSpec := range spec {
		f := fuzz.New().NilChance(0).Funcs(
			func(e *cadvisorapiv1.MetricVal, c fuzz.Continue) {
				switch metricSpec.Format {
				case cadvisorapiv1.IntType:
					c.Fuzz(&e.IntValue)

	var lastKey []byte
	var withRev int64
	var getResp *clientv3.GetResponse

	metricsOp := "get"
	if wc.recursive {
		metricsOp = "list"
	}

	preparedKey := wc.key

	for {
		startTime := time.Now()
		getResp, err = wc.watcher.client.KV.Get(wc.ctx, preparedKey, opts...)
		metrics.RecordEtcdRequest(metricsOp, wc.watcher.groupResource.String(), err, startTime)
		if err != nil {

Nesse caso, se você tivesse **múltiplos contêineres**, por padrão, quando o Prometheus fosse **ler as métricas**, ele receberia as métricas de **um único contêiner cada vez** (para o contêiner que tratou essa solicitação específica), em vez de receber as **métricas acumuladas** de todos os contêineres replicados.

				podMetric := metricsapi.PodMetrics{
					ObjectMeta: metav1.ObjectMeta{
						Name:      podName,
						Namespace: testNamespace,
						Labels:    map[string]string{"name": podNamePrefix},
					},
					Timestamp:  metav1.Time{Time: tc.timestamp},
					Window:     metav1.Duration{Duration: time.Minute},
					Containers: make([]metricsapi.ContainerMetrics, numContainersPerPod),
				}

		metrics.RecordStorageListMetrics(s.groupResourceString, numFetched, numEvald, numReturn)
	}()

	metricsOp := "get"
	if opts.Recursive {
		metricsOp = "list"
	}

	for {
		startTime := time.Now()
		getResp, err = s.client.KV.Get(ctx, preparedKey, options...)
		metrics.RecordEtcdRequest(metricsOp, s.groupResourceString, err, startTime)
		if err != nil {