rx.measure = newRateMeasurement(time.Now())
	}
	rx.measure.incrementBytes(uint64(sz))
	rx.Curr = rx.measure.getExpMovingAvgBytesPerSecond()
	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

		Error:         retError,
	}, nil
}

// To collect RX stats during "mc support perf net"
// RXSample holds the RX bytes for the duration between
// the last peer to connect and the first peer to disconnect.
// This is to improve the RX throughput accuracy.
type netPerfRX struct {
	RX                uint64    // RX bytes
	lastToConnect     time.Time // time at which last peer to connect to us

  "event": "",
  "trigger": "incoming",
  "api": {
    "name": "PutObject",
    "bucket": "testbucket",
    "object": "hosts",
    "status": "OK",
    "statusCode": 200,
    "rx": 401,
    "tx": 0,
    "timeToResponse": "13309747ns",
    "timeToResponseInNS": "13309747"
  },
  "remotehost": "127.0.0.1",
  "requestID": "17CDC1F4D7E69123",

			nil, nil),
		prometheus.CounterValue,
		float64(connStats.internodeOutputBytes),
	)

	ch <- prometheus.MustNewConstMetric(
		prometheus.NewDesc(
			prometheus.BuildFQName(interNodeNamespace, "rx", "bytes_total"),
			"Total number of internode bytes received by current MinIO server instance",
			nil, nil),
		prometheus.CounterValue,
		float64(connStats.internodeInputBytes),
	)

	globalSiteNetPerfRX.Connect()
	defer globalSiteNetPerfRX.Disconnect()

	connectTime := time.Now()
	for {
		n, err := io.CopyN(xioutil.Discard, r.Body, 128*humanize.KiByte)
		atomic.AddUint64(&globalSiteNetPerfRX.RX, uint64(n))
		if err != nil && err != io.EOF && err != io.ErrUnexpectedEOF {
			// If there is a disconnection before globalNetPerfMinDuration (we give a margin of error of 1 sec)

	// FIXME: network calls made in this manner such as one goroutine per node,
	// can easily eat into the internode bandwidth. This function would be mostly
	// TX saturating, however there are situations where a RX might also saturate.
	// To avoid these problems we must split the work at scale. With 1000 node
	// setup becoming a reality we must try to shard the work properly such as