* [okhttp-stats](https://github.com/flipkart-incubator/okhttp-stats): Get stats like average network speed.
 * [okhttp-system-keystore](https://github.com/charleskorn/okhttp-system-keystore): Use trusted certificates from the operating system keystore (Keychain on macOS, Certificate Store on Windows).

 * you would expect.
 *
 * <p>If required to do a weighted average between an infinity and a finite value, or between an
 * infinite value and itself, the infinite value is returned. If required to do a weighted average
 * between {@link Double#NEGATIVE_INFINITY NEGATIVE_INFINITY} and {@link Double#POSITIVE_INFINITY

	bucketsThrottle    map[BucketOptions]*bucketThrottle
	bucketsMeasurement map[BucketOptions]*bucketMeasurement // Buckets with objects in flight

	bucketMovingAvgTicker *time.Ticker    // Ticker for calculating moving averages
	ctx                   context.Context // Context for generate
	NodeCount             uint64
}

// NewMonitor returns a monitor with defaults.
func NewMonitor(ctx context.Context, numNodes uint64) *Monitor {

		Name:      avgLinkLatency,
		Help:      "Average replication link latency in milliseconds",
		Type:      gaugeMetric,
	}
}

func getClusterReplAvgQueuedOperationsMD() MetricDescription {
	return MetricDescription{
		Namespace: nodeMetricNamespace,
		Subsystem: replicationSubsystem,
		Name:      avgInQueueCount,
		Help:      "Average number of objects queued for replication since server uptime",

	// Total Replica received
	ReplicaCount int64                `json:"replicaCount"`
	M            map[string]*SRStatus `json:"srStatusMap"`

	movingAvgTicker *time.Ticker // Ticker for calculating moving averages
	lock            sync.RWMutex // mutex for srStats
}

// SRStatus has replication stats at deployment level
type SRStatus struct {
	ReplicatedSize int64 `json:"completedReplicationSize"`

  // We could make this a Map<E, EndpointPair<N>>. It would make incidentNodes(edge) slightly
  // faster, but also make Networks consume 5 to 20+% (increasing with average degree) more memory.
  final MapIteratorCache<E, N> edgeToReferenceNode; // referenceNode == source if directed

  /** Constructs a graph with the properties specified in {@code builder}. */

  // We could make this a Map<E, EndpointPair<N>>. It would make incidentNodes(edge) slightly
  // faster, but also make Networks consume 5 to 20+% (increasing with average degree) more memory.
  final MapIteratorCache<E, N> edgeToReferenceNode; // referenceNode == source if directed

  /** Constructs a graph with the properties specified in {@code builder}. */

      assertEquivalent(stats.mean(), stream(array).average().getAsDouble());
      assertEquivalent(stats.sum(), stream(array).sum());
      assertEquivalent(stats.max(), stream(array).max().getAsDouble());
      assertEquivalent(stats.min(), stream(array).min().getAsDouble());
      // static method on Stats vs on instance method on DoubleStream
      assertEquivalent(Stats.meanOf(array), stream(array).average().getAsDouble());

	sync.RWMutex                 // mutex for Cache
	mostRecentStatsMu sync.Mutex // mutex for mostRecentStats

	wlock sync.RWMutex // mutex for active workers

	movingAvgTicker *time.Ticker // Ticker for calculating moving averages
	wTimer          *time.Ticker // ticker for calculating active workers
	qTimer          *time.Ticker // ticker for calculating queue stats
}

func (r *ReplicationStats) trackEWMA() {
	for {
		select {

 * add(x)} operations <i>do not</i> create objects for the garbage collector to deal with, and for
 * every element added, the garbage collector will have to traverse {@code 1.5} references on
 * average, in the marking phase, not {@code 5.0} as in {@code java.util.HashSet}.
 *
 * <p>If there are no removals, then {@link #iterator iteration} order is the same as insertion
 * order. Any removal invalidates any ordering guarantees.