StabilityLevel: metrics.ALPHA,
		},
		[]string{"protocol", "transport", "stage"},
	)

	legacyregistry.MustRegister(starts)
	legacyregistry.MustRegister(latencies)
	legacyregistry.MustRegister(failures)
	return &DialMetrics{starts: starts, latencies: latencies, failures: failures, clock: clock.RealClock{}}
}

// Clock returns the clock.
func (m *DialMetrics) Clock() clock.Clock {
	return m.clock
}

			Namespace: namespace,
			Subsystem: subsystem,
			Name:      "transformation_duration_seconds",
			Help:      "Latencies in seconds of value transformation operations.",
			// In-process transformations (ex. AES CBC) complete on the order of 20 microseconds. However, when
			// external KMS is involved latencies may climb into hundreds of milliseconds.
			Buckets:        metrics.ExponentialBuckets(5e-6, 2, 25),
			StabilityLevel: metrics.ALPHA,

			b.ReportMetric(float64(latencies[len(latencies)*90/100]), "p90-ns")
			b.ReportMetric(float64(latencies[len(latencies)*99/100]), "p99-ns")
		}
		return func(b *testing.B) {
			b.Run("idle", runOne)

			b.Run("loaded", func(b *testing.B) {
				stop := applyGCLoad(b)
				runOne(b)
				// Make sure to stop the timer before we wait! The load created above

}

var _ crConverterInterface = &converterMetric{}

type converterMetric struct {
	delegate  crConverterInterface
	latencies *metrics.HistogramVec
	crdName   string
}

func (c *converterMetricFactory) addMetrics(crdName string, converter crConverterInterface) (crConverterInterface, error) {
	c.factoryLock.Lock()
	defer c.factoryLock.Unlock()

}

type metricSet struct {
	latencies        *metrics.HistogramVec
	latenciesSummary *metrics.SummaryVec
}

// MustRegister registers all the prometheus metrics in the metricSet.
func (m *metricSet) mustRegister() {
	legacyregistry.MustRegister(m.latencies)
	if m.latenciesSummary != nil {
		legacyregistry.MustRegister(m.latenciesSummary)
	}
}

	b.ReportMetric(0, "ns/op")
	b.ReportMetric(0, "B/op")
	b.ReportMetric(0, "allocs/op")

	// Sort latencies then report percentiles.
	slices.Sort(latencies)
	b.ReportMetric(float64(latencies[len(latencies)*50/100]), "p50-ns")
	b.ReportMetric(float64(latencies[len(latencies)*90/100]), "p90-ns")
	b.ReportMetric(float64(latencies[len(latencies)*99/100]), "p99-ns")
}

func TestUserForcedGC(t *testing.T) {

// implementation which is buggy on NUMA systems, we have to use a simpler
// io.Writer implementation alone avoids also unnecessary buffer copies,
// and as such incurred latencies.
var Discard io.Writer = discard{}

// discard is /dev/null for Golang.
type discard struct{}

func (discard) Write(p []byte) (int, error) {
	return len(p), nil
}

// DiscardReader discarded reader

			Dest: otherRegion,
		}: 100 * time.Millisecond,
	}

	networkLatencyCases := []struct {
		enable    bool
		latencies map[mesh.RouteKey]time.Duration
	}{
		{
			enable:    false,
			latencies: make(map[mesh.RouteKey]time.Duration),
		},
		{
			enable:    true,
			latencies: networkLatencies,
		},
	}

	weightCases := []struct {
		enableWeighting       bool

	b.ReportMetric(0, "allocs/op")

	// Sort latencies then report percentiles.
	sort.Slice(latencies, func(i, j int) bool {
		return latencies[i] < latencies[j]
	})
	b.ReportMetric(float64(latencies[len(latencies)*50/100]), "p50-ns")
	b.ReportMetric(float64(latencies[len(latencies)*90/100]), "p90-ns")
	b.ReportMetric(float64(latencies[len(latencies)*99/100]), "p99-ns")
}

var readMetricsSink [1024]interface{}

query results are printed to the console, organized by workload name.

All metrics returned are from server-side reports. This means that latencies
and error rates are from the perspective of the service itself and not of an
individual client (or aggregate set of clients). Rates and latencies are
calculated over a time interval of 1 minute.
`,
		Example: `  # Retrieve workload metrics for productpage-v1 workload