*       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 maxBandwidthChannel != null ? maxBandwidthChannel : channels.iterator().next();
        }

        if (isMetadataOperation(message)) {
            // For metadata operations, prefer low-latency channels
            return selectLeastLoaded(channels);
        }

        // Default to weighted random for general operations
        return selectWeightedRandom(channels);
    }

	}
	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": {

 *       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

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": {

 * OkHttp performs best when you create a single `OkHttpClient` instance and reuse it for all of
 * your HTTP calls. This is because each client holds its own connection pool and thread pools.
 * Reusing connections and threads reduces latency and saves memory. Conversely, creating a client
 * for each request wastes resources on idle pools.
 *
 * Use `new OkHttpClient()` to create a shared instance with the default settings:
 *
 * ```java

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...