Help:      "Average replication transfer rate in bytes/sec",
		Type:      gaugeMetric,
	}
}

func getClusterReplMaxTransferRateMD() MetricDescription {
	return MetricDescription{
		Namespace: nodeMetricNamespace,
		Subsystem: replicationSubsystem,
		Name:      maxTransferRate,
		Help:      "Maximum replication transfer rate in bytes/sec seen since server uptime",
		Type:      gaugeMetric,

    Closer closer = Closer.create();
    try {
      InputStream in = closer.register(openStream());
      return countBySkipping(in);
    } catch (IOException e) {
      // skip may not be supported... at any rate, try reading
    } finally {
      closer.close();
    }

    closer = Closer.create();
    try {
      InputStream in = closer.register(openStream());
      return ByteStreams.exhaust(in);

   *
   * <p>See http://en.wikipedia.org/wiki/Bloom_filter#Probability_of_false_positives for the
   * formula.
   *
   * @param n expected insertions (must be positive)
   * @param p false positive rate (must be 0 < p < 1)
   */
  @VisibleForTesting
  static long optimalNumOfBits(long n, double p) {
    if (p == 0) {
      p = Double.MIN_VALUE;
    }
    return (long) (-n * Math.log(p) / SQUARED_LOG_TWO);

      * if the new state is "partialDisruption" or "fullDisruption" we call a user defined function that returns a new QPS to use (default 1/10 of the default rate, and the default rate respectively),
      * if the new state is "normal" we resume normal operation (go back to default limiter settings),
      * if all zones in the cluster are in "fullDisruption" state we stop all evictions.

				return nil, err
			}
			defer RemoveAll(dirPath)
			return ioutilx.ReadFile(fn)
		}
	case madmin.ProfilerCPUIO:
		// at 10k or more goroutines fgprof is likely to become
		// unable to maintain its sampling rate and to significantly
		// degrade the performance of your application
		// https://github.com/felixge/fgprof#fgprof
		if n := runtime.NumGoroutine(); n > 10000 && !globalIsCICD {

* vSphere Volume Plugin Implementation ([#24947](https://github.com/kubernetes/kubernetes/pull/24947), [@abithap](https://github.com/abithap))
* ResourceQuota controller uses rate limiter to prevent hot-loops in error situations ([#25748](https://github.com/kubernetes/kubernetes/pull/25748), [@derekwaynecarr](https://github.com/derekwaynecarr))

   *
   * The Least Recently Used page replacement algorithm was chosen due to its simplicity, high hit
   * rate, and ability to be implemented with O(1) time complexity. The initial LRU implementation
   * operates per-segment rather than globally for increased implementation simplicity. We expect
   * the cache hit rate to be similar to that of a global LRU algorithm.
   */

  // Constants

  /**

```

MinIO server also supports [NATS Streaming mode](http://nats.io/documentation/streaming/nats-streaming-intro/) that offers additional functionality like `At-least-once-delivery`, and `Publisher rate limiting`. To configure MinIO server to send notifications to NATS Streaming server, update the MinIO server configuration file as follows:

&d.a, out, buf) } else { // We have "buffered" output still to copy. if d.n < d.rate { x := copy(out, d.a[d.n:d.rate]) d.n += x out = out[x:] } if len(out) == 0 { return } klmd(d.function()|nopad, &d.a, out, nil) } if len(out)%d.rate == 0 { // The final permutation was not performed, // so there is no "buffered" output. d.n = d.rate } else { d.n = len(out) % d.rate } return } func (d *Digest) function() code { switch d.rate { case rateK256: return shake_128 case rateK448: return sha3_224 case rateK512:...

      maintains a hash table to track the most up-to-date vocabulary based on
      the inputs received by the layer and the eviction policy. When this layer
      is used with an `UpdateEmbeddingCallback`, which is a time-based callback,
      the vocabulary lookup tensor is updated at the time interval set in the
      `UpdateEmbeddingCallback` based on the most up-to-date vocabulary hash