assertEquals(5120, stats.getBytesTransferred(), "Should have transferred 5KB total");
        assertEquals(1, stats.getOperationErrors(), "Should have 1 error");
        assertEquals(0.25, stats.getErrorRate(), 0.001, "Error rate should be 25% (1 error out of 4 successful operations)");

        // Verify latency calculations
        assertTrue(stats.getAverageReadLatencyMicros() > 0, "Read latency should be positive");

          "interval": "1m",
          "intervalFactor": 2,
          "legendFormat": "{{server}}",
          "refId": "A"
        }
      ],
      "title": "Avg. Transfer Rate (bytes/s)",
      "type": "timeseries"
    },
    {
      "datasource": {
        "type": "prometheus",
        "uid": "${DS_PROMETHEUS}"
      },
      "fieldConfig": {
        "defaults": {

| `minio_node_replication_average_transfer_rate`          | Average replication transfer rate in bytes/sec                                                           |
| `minio_node_replication_max_transfer_rate`              | Maximum replication transfer rate in bytes/sec seen since server start                                   |

                    handleChannelFailure(channel, e);
                }
            }
            
            // Check error rate
            if (channel.getErrorRate() > 0.1) {
                log.warn("High error rate on channel {}: {}", 
                    channel.getChannelId(), channel.getErrorRate());
                // Consider removing channel
            }
        }
    }

					throughputHighestPut = totalPut
					// let the client see lower value as well
					throughputHighestGet = totalGet
				}
				sendResult()
				break
			}

			// We break if we did not see 2.5% growth rate in total GET
			// requests, we have reached our peak at this point.
			doBreak := float64(totalGet-throughputHighestGet)/float64(totalGet) < 0.025

			throughputHighestGet = totalGet
			throughputHighestResults = results

                    handleChannelFailure(channel, e);
                }
            }

            // Check error rate
            if (channel.getErrorRate() > 0.1) {
                log.warn("High error rate on channel {}: {}", channel.getChannelId(), channel.getErrorRate());
            }
        }
    }

	// we allocate buffers rounded up to the closest size class.
	c := len(b) + n // ensure enough space for n elements
	if c < 2*cap(b) {
		// The growth rate has historically always been 2x. In the future,
		// we could rely purely on append to determine the growth rate.
		c = 2 * cap(b)
	}
	b2 := append([]byte(nil), make([]byte, c)...)
	i := copy(b2, b)
	return b2[:i]
}

| `minio_replication_current_active_workers`        | Total number of active replication workers. <br><br>Type: gauge                             | `server` |
| `minio_replication_current_data_transfer_rate`    | Current replication data transfer rate in bytes/sec. <br><br>Type: gauge                    | `server` |

   * only become known via CAS failures, convergence can be slow,
   * and because threads are typically not bound to CPUS forever,
   * may not occur at all. However, despite these limitations,
   * observed contention rates are typically low in these cases.
   *
   * It is possible for a Cell to become unused when threads that
   * once hashed to it terminate, as well as in the case where
   * doubling the table causes no thread to hash to it under

we don't consider this as a vulnerability, given that models can exhaust
resources in many different ways and solutions exist to prevent this from
happening (e.g., rate limits, ACLs, monitors to restart broken servers).

### Model sharing

If the multitenant design allows sharing models, make sure that tenants and