* we change the rate.
   */
  public void testWeNeverGetABurstMoreThanOneSec() {
    RateLimiter limiter = RateLimiter.create(1.0, stopwatch);
    int[] rates = {1000, 1, 10, 1000000, 10, 1};
    for (int rate : rates) {
      int oneSecWorthOfWork = rate;
      stopwatch.sleepMillis(rate * 1000);
      limiter.setRate(rate);

   * we change the rate.
   */
  public void testWeNeverGetABurstMoreThanOneSec() {
    RateLimiter limiter = RateLimiter.create(1.0, stopwatch);
    int[] rates = {1000, 1, 10, 1000000, 10, 1};
    for (int rate : rates) {
      int oneSecWorthOfWork = rate;
      stopwatch.sleepMillis(rate * 1000);
      limiter.setRate(rate);

                  "uid": "$datasource"
               },
               "expr": "sum (rate(istio_requests_total{reporter=~\"source|waypoint\",response_code!~\"5..\"}[$__rate_interval])) / sum (rate(istio_requests_total{reporter=~\"source|waypoint\"}[$__rate_interval]))"
            }
         ],
         "title": "Success Rate",
         "type": "stat"
      },
      {
         "datasource": {

          },
          "exemplar": true,
          "expr": "sum by (server) (rate(minio_s3_traffic_received_bytes{job=~\"$scrape_jobs\"}[$__rate_interval]))",
          "interval": "1m",
          "intervalFactor": 2,
          "legendFormat": "Data Received [{{server}}]",
          "refId": "A"
        }
      ],
      "title": "S3 API Ingress Rate ",
      "type": "timeseries"
    },
    {
      "datasource": {

    ]),
  ], 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.
        |||

            {
               "datasource": {
                  "type": "prometheus",
                  "uid": "$datasource"
               },
               "expr": "sum by (cluster, namespace, job) (\n    rate(\n        process_cpu_seconds_total{\n            cluster=~\"$cluster\",\n            namespace=~\"$namespace\",\n            job=~\"$job\"\n        }\n    [$__rate_interval])\n)\n",
               "intervalFactor": 2,

		"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,

  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);

	isReady.Store(false)
}

// installationThrottle is a small wrapper around a rate limitter. It aims to avoid excessive writes to CNI configuration,
// and detect if there is a loop of requests, typically caused by another component constantly reverting our work.
// Where possible, the remediate steps are logged.
type installationThrottle struct {
	limiter *rate.Limiter
	hits    int
	in      *Installer
}

	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},
			},