}

  @Throws(IOException::class)
  override fun createServerSocket(
    port: Int,
    backlog: Int,
  ): ServerSocket {
    val serverSocket = delegate.createServerSocket(port, backlog)
    return configureServerSocket(serverSocket)
  }

  @Throws(IOException::class)
  override fun createServerSocket(
    port: Int,
    backlog: Int,
    ifAddress: InetAddress,
  ): ServerSocket {

    return createServerSocket();
  }

  @Override public ServerSocket createServerSocket(int port, int backlog) throws IOException {
    return createServerSocket();
  }

  @Override public ServerSocket createServerSocket(
      int port, int backlog, InetAddress inetAddress) throws IOException {
    return createServerSocket();
  }

  final class UnixDomainServerSocket extends ServerSocket {

  var isParallel = false

  /** Number of calls to [TaskRunner.Backend.execute]. Guarded by `this`. */
  var executeCallCount = 0

  /** Guarded by [taskRunner]. */
  var nanoTime = 0L
    private set

  /** Backlog of tasks to run. Only one task runs at a time. Guarded by `this`. */
  private val serialTaskQueue = ArrayDeque<SerialTask>()

  /** The task that's currently executing. Guarded by `this`. */

		"Maximum replication data transfer rate in bytes/sec seen since server start")
	replicationRecentBacklogCountMD = NewGaugeMD(replicationRecentBacklogCount,
		"Total number of objects seen in replication backlog in the last 5 minutes")
)

// loadClusterReplicationMetrics - `MetricsLoaderFn` for cluster replication metrics
// such as transfer rate and objects queued.

	rx.sma.addSample(rx.Curr)
	rx.Avg = rx.sma.simpleMovingAvg()
	if rx.Curr > rx.Peak {
		rx.Peak = rx.Curr
	}
	rx.N++
}

// ReplicationMRFStats holds stats of MRF backlog saved to disk in the last 5 minutes
// and number of entries that failed replication after 3 retries
type ReplicationMRFStats struct {
	LastFailedCount uint64 `json:"failedCount_last5min"`

On the target bucket, `s3:PutObject` event shows `X-Amz-Replication-Status` status of `REPLICA` in the metadata. Additional metrics to monitor backlog state for the purpose of bandwidth management and resource allocation are exposed via Prometheus - see <https://github.com/minio/minio/blob/master/docs/metrics/prometheus/list.md> for more details.

### Sync/Async Replication

	// for site replication - maintain stats at global level
	srStats *SRStats
	// active worker stats
	workers *ActiveWorkerStat
	// queue stats cache
	qCache queueCache

	pCache proxyStatsCache
	// mrf backlog stats
	mrfStats ReplicationMRFStats
	// for bucket replication, continue to use existing cache
	Cache             map[string]*BucketReplicationStats
	mostRecentStats   BucketStatsMap
	registry          metrics.Registry

				return
			}
			xhttp.Flush(w)
		case <-ctx.Done():
			return
		}
	}
}

// ReplicationMRFHandler - POST returns info on entries in the MRF backlog for a node or all nodes
func (a adminAPIHandlers) ReplicationMRFHandler(w http.ResponseWriter, r *http.Request) {
	ctx := r.Context()

	vars := mux.Vars(r)
	bucket := vars["bucket"]

| `minio_replication_recent_backlog_count`          | Total number of objects seen in replication backlog in the last 5 minutes <br><br>Type: gauge | `server` |
#### `/bucket/replication`

Doch dann verlagerte sich der Schwerpunkt des Projekts.