Failed:          fstats.toMetric(),
				FailStats:       fstats,
				ReplicatedSize:  stat.ReplicatedSize + oldst.ReplicatedSize,
				ReplicatedCount: stat.ReplicatedCount + oldst.ReplicatedCount,
				Latency:         stat.Latency.merge(oldst.Latency),
				XferRateLrg:     &lrg,
				XferRateSml:     &sml,
			}
			totReplicatedSize += stat.ReplicatedSize
			totReplicatedCount += stat.ReplicatedCount

server: the port number, HTTPS settings, and preferred network protocols (like HTTP/2).

URLs that share the same address may also share the same underlying TCP socket connection. Sharing a connection has substantial performance benefits: lower latency, higher throughput (due to [TCP slow start](https://www.igvita.com/2011/10/20/faster-web-vs-tcp-slow-start/)) and conserved battery. OkHttp uses a [ConnectionPool](https://square.github.io/okhttp/5.x/okhttp/okhttp3/-connection-pool/) that automatically...

	// This will make `test/a` and `test/b` share listings if they are concurrent.
	// Enabling this will make cache sharing more likely and cause less IO,
	// but may cause additional latency to some calls.
	metacacheSharePrefix = false
)

//go:generate msgp -file $GOFILE -unexported

// metacache contains a tracked cache entry.
type metacache struct {

 *       anything about how the property is tested. To find out, read the code.
 *   <li>These tests are "conformance tests", and do not attempt to test throughput, latency,
 *       scalability or other performance factors (see the separate "jtreg" tests for a set intended
 *       to check these for the most central aspects of functionality.) So, most tests use the

	}
	return &KMS{
		Type:       Builtin,
		DefaultKey: keyID,
		conn: secretKey{
			keyID: keyID,
			key:   key,
		},
		latencyBuckets: defaultLatencyBuckets,
		latency:        make([]atomic.Uint64, len(defaultLatencyBuckets)),
	}, nil
}

// secretKey is a KMS implementation that derives new DEKs
// from a single key.
type secretKey struct {
	keyID string
	key   []byte
}

          "interval": "1m",
          "intervalFactor": 2,
          "legendFormat": "{{server,endpoint}}",
          "refId": "A"
        }
      ],
      "title": "Avg. Link Latency (millis)",
      "type": "timeseries"
    },
    {
      "datasource": {
        "type": "prometheus",
        "uid": "${DS_PROMETHEUS}"
      },
      "fieldConfig": {
        "defaults": {

efficiently makes your stuff load faster and saves bandwidth.

OkHttp is an HTTP client that’s efficient by default:

 * HTTP/2 support allows all requests to the same host to share a socket.
 * Connection pooling reduces request latency (if HTTP/2 isn’t available).
 * Transparent GZIP shrinks download sizes.
 * Response caching avoids the network completely for repeat requests.

It includes built in muxing of concurrent requests as well as congestion handling for streams.

Requests can be "Single Payload" or "Streamed".

Use the MinIO Grid for:

* Small, frequent requests with low latency requirements.
* Long-running requests with small/medium payloads.

Do *not* use the MinIO Grid for:

* Large payloads.

Only a single connection is ever made between two servers.

          "interval": "",
          "legendFormat": "[{{drive}}:{{api}}]",
          "refId": "B"
        }
      ],
      "title": "Drive Latency (micro sec)",
      "type": "timeseries"
    },
    {
      "datasource": {
        "type": "prometheus",
        "uid": "${DS_PROMETHEUS}"
      },
      "description": "",
      "fieldConfig": {

Depending on the number of previously existing objects, the existing objects that are now eligible to be replicated will eventually be synced to the target cluster as the scanner schedules them. This may be slower depending on the load on the cluster, latency and size of the namespace.

In the rare event that target DR site is entirely lost and previously replicated objects to the DR cluster need to be re-replicated, `mc replicate resync start alias/bucket --remote-bucket <arn>` can be used to...