activeConnections uint64
	sync.RWMutex
}

func (n *netPerfRX) Connect() {
	n.Lock()
	defer n.Unlock()
	n.activeConnections++
	atomic.StoreUint64(&n.RX, 0)
	n.lastToConnect = time.Now()
}

func (n *netPerfRX) Disconnect() {
	n.Lock()
	defer n.Unlock()
	n.activeConnections--
	if n.firstToDisconnect.IsZero() {
		n.RXSample = atomic.LoadUint64(&n.RX)

	sys.Lock()
	for _, bucket := range buckets {
		sys.group.Forget(bucket)
		delete(sys.metadataMap, bucket)
		globalBucketMonitor.DeleteBucket(bucket)
	}
	sys.Unlock()
}

// RemoveStaleBuckets removes all stale buckets in memory that are not on disk.
func (sys *BucketMetadataSys) RemoveStaleBuckets(diskBuckets set.StringSet) {
	sys.Lock()
	defer sys.Unlock()

		return err
	}

	// if no update is needed return right away.
	if !update {
		z.poolMetaMutex.Lock()
		z.poolMeta = meta
		z.poolMetaMutex.Unlock()
	} else {
		newMeta := newPoolMeta(z, meta)
		if err = newMeta.save(ctx, z.serverPools); err != nil {
			return err
		}
		z.poolMetaMutex.Lock()
		z.poolMeta = newMeta
		z.poolMetaMutex.Unlock()
	}

	pools := meta.returnResumablePools()

import (
	"io"
	"os"

	"github.com/minio/minio/internal/lock"
)

// AppendFile - appends the file "src" to the file "dst"
func AppendFile(dst string, src string, osync bool) error {
	appendFile, err := lock.Open(dst, os.O_WRONLY|os.O_APPEND|os.O_CREATE, 0o666)
	if err != nil {
		return err
	}
	defer appendFile.Close()

	srcFile, err := lock.Open(src, os.O_RDONLY, 0o666)
	if err != nil {
		return err
	}

func (ahs *allHealState) setDiskHealingStatus(ep Endpoint, healing bool) {
	ahs.Lock()
	defer ahs.Unlock()

	ahs.healLocalDisks[ep] = healing
}

func (ahs *allHealState) pushHealLocalDisks(healLocalDisks ...Endpoint) {
	ahs.Lock()
	defer ahs.Unlock()

	for _, ep := range healLocalDisks {
		ahs.healLocalDisks[ep] = false
	}
}

   * of reads may not be immediately reflected on the algorithm's data structures. These structures
   * are guarded by a lock and operations are applied in batches to avoid lock contention. The
   * penalty of applying the batches is spread across threads so that the amortized cost is slightly
   * higher than performing just the operation without enforcing the capacity constraint.

   * of reads may not be immediately reflected on the algorithm's data structures. These structures
   * are guarded by a lock and operations are applied in batches to avoid lock contention. The
   * penalty of applying the batches is spread across threads so that the amortized cost is slightly
   * higher than performing just the operation without enforcing the capacity constraint.

		return
	}

	go func() {
		r := rand.New(rand.NewSource(time.Now().UnixNano()))
		// Leader node (that successfully acquires the lock inside runCallhome)
		// will keep performing the callhome. If the leader goes down for some reason,
		// the lock will be released and another node will acquire it and take over
		// because of this loop.
		for {
			if !globalCallhomeConfig.Enabled() {
				return
			}

	}
	// Unlock, since we are calling deleteMux, which will call close - which will lock recvMu.
	if locked {
		m.recvMu.Unlock()
		defer m.recvMu.Lock()
	}
	m.parent.deleteMux(true, m.ID)
}

func (m *muxServer) send(msg message) {
	m.sendMu.Lock()
	defer m.sendMu.Unlock()
	msg.MuxID = m.ID
	msg.Seq = m.SendSeq
	m.SendSeq++
	if debugPrint {

	sync.Mutex
}

func (l *logOnceType) logOnceConsoleIf(ctx context.Context, subsystem string, err error, id string, errKind ...interface{}) {
	if err == nil {
		return
	}

	nerr := unwrapErrs(err)
	l.Lock()
	shouldLog := true
	prev, ok := l.IDMap[id]
	if !ok {
		l.IDMap[id] = onceErr{
			Err:   nerr,
			Count: 1,
		}
	} else if prev.Err.Error() == nerr.Error() {
		// if errors are equal do not log.