alea
ălea
altceva
altcineva
am
ar
are
aş
aşadar
asemenea
asta
ăsta
astăzi
astea
ăstea
ăştia
asupra
aţi
au
avea
avem
aveţi
azi
bine
bucur
bună
ca
că
căci
când
care
cărei
căror
cărui
cât
câte
câţi
către
câtva
ce
cel
ceva
chiar
cînd
cine
cineva
cît
cîte
cîţi
cîtva
contra
cu
cum
cumva

    ]),
  ], panelHeight=10, startY=1)
  + g.util.grid.makeGrid([
    row.new('Push Information')
    + row.withPanels([
      panels.timeSeries.xdsPushes(
        'XDS Pushes', queries.xdsPushes, |||
          Rate of XDS push operations, by type. This is incremented on a per-proxy basis.
        |||
      ),
      panels.timeSeries.base(
        'Events', queries.pilotEvents, |||
          Size of each xDS push.
        |||

		"Average replication data transfer rate in bytes/sec")
	replicationCurrentActiveWorkersMD = NewGaugeMD(replicationCurrentActiveWorkers,
		"Total number of active replication workers")
	replicationCurrentDataTransferRateMD = NewGaugeMD(replicationCurrentDataTransferRate,
		"Current replication data transfer rate in bytes/sec")
	replicationLastMinuteQueuedBytesMD = NewGaugeMD(replicationLastMinuteQueuedBytes,

{
  sum(query, by=[]):
    if std.length(by) == 0 then
      'sum (%s)' % [query]
    else
      'sum by (%s) (%s)' % [std.join(',', by), query],
  irate(query):
    'irate(%s[$__rate_interval])' % query,
  rate(query):
    'rate(%s[$__rate_interval])' % query,
  round(query, by=0.01):
    'round(%s, %s)' % [query, by],
  quantile(quantile, query):
    'histogram_quantile(%s, %s)' %[quantile, query],
  labels(metric_name, labels):

  int maximumSize;

  @Param("5000")
  int distinctKeys;

  @Param("4")
  int segments;

  // 1 means uniform likelihood of keys; higher means some keys are more popular
  // tweak this to control hit rate
  @Param("2.5")
  double concentration;

  Random random = new Random();

  LoadingCache<Integer, Integer> cache;

  int max;

  static AtomicLong requests = new AtomicLong(0);

	mockProm := mockPromAPI{
		cannedResponse: map[string]prometheus_model.Value{
			"sum(rate(istio_requests_total{destination_workload=~\"details.*\", destination_workload_namespace=~\".*\",reporter=\"destination\"}[1m0s]))": prometheus_model.Vector{ // nolint: lll
				&prometheus_model.Sample{Value: 0.04},
			},

    row.new('Global Traffic')
    + row.withPanels([
      panels.timeSeries.statRps('Traffic Volume', queries.globalRequest, 'Total requests in the cluster'),
      panels.timeSeries.statPercent('Success Rate', queries.globalRequestSuccessRate, 'Total success rate of requests in the cluster'),
      panels.timeSeries.statRps('4xxs', queries.globalRequest4xx, 'Total 4xx requests in in the cluster'),

package bandwidth

//go:generate msgp -file=$GOFILE -unexported

import (
	"context"
	"sync"
	"time"

	"golang.org/x/time/rate"
)

//msgp:ignore bucketThrottle Monitor

type bucketThrottle struct {
	*rate.Limiter
	NodeBandwidthPerSec int64
}

// Monitor holds the state of the global bucket monitor
type Monitor struct {
	tlock sync.RWMutex // mutex for bucket throttling

	wname := parts[0]
	wns := ""
	if len(parts) > 1 {
		wns = parts[1]
	}

	rpsQuery := fmt.Sprintf(`sum(rate(%s{%s=~"%s.*", %s=~"%s.*",reporter="destination"}[%s]))`,
		reqTot, destWorkloadLabel, wname, destWorkloadNamespaceLabel, wns, duration)
	errRPSQuery := fmt.Sprintf(`sum(rate(%s{%s=~"%s.*", %s=~"%s.*",reporter="destination",response_code=~"[45][0-9]{2}"}[%s]))`,

                "name": "default.httpbin-rate-limiting",
                "typedConfig": {
                    "@type": "type.googleapis.com/envoy.extensions.filters.http.wasm.v3.Wasm",
                    "config": {
                        "name": "default.httpbin-rate-limiting",
                        "vmConfig": {
                            "runtime": "envoy.wasm.runtime.v8",