// and they will only connect once and persist.
	// However, if they do get in a state where they call us in a loop, we will quickly OOM
	limit := rate.NewLimiter(rate.Limit(5), 1)
	for {
		log.Debug("accepting conn")
		if err := limit.Wait(ctx); err != nil {
			log.Errorf("failed to wait for ztunnel connection: %v", err)
			return
		}
		conn, err := z.accept()

          "datasource": {
            "type": "prometheus",
            "uid": "${datasource}"
          },
          "editorMode": "code",
          "expr": "sum(irate(istio_requests_total{reporter=~\"$qrep\",destination_service=~\"$service\",response_code!~\"5.*\"}[5m])) / (sum(irate(istio_requests_total{reporter=~\"$qrep\",destination_service=~\"$service\"}[5m])) or on () vector(1))",
          "format": "time_series",
          "intervalFactor": 1,

					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

	rc, err := kube.DefaultRestConfig(kubeconfig, configContext, func(config *rest.Config) {
		// We are running a one-off command locally, so we don't need to worry too much about rate limiting
		// Bumping this up greatly decreases install time
		config.QPS = 50
		config.Burst = 100
		config.Impersonate = impersonateConfig
	})
	if err != nil {
		return nil, err
	}

        + override.byName.withProperty('decimals', 2)
        + override.byName.withProperty('unit', 'ms'),
        override.byName.new('Value #success')
        + override.byName.withProperty('displayName', 'Success Rate')
        + override.byName.withProperty('decimals', 2)
        + override.byName.withProperty('unit', 'percentunit')
        + override.byName.withProperty('custom.cellOptions', { type: 'color-background' })

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

          "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                                   |

| `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` |

 * late. Also, all life cycle methods are executed with a lock held, so subclasses can safely modify
 * shared state without additional synchronization necessary for visibility to later executions of
 * the life cycle methods.
 *
 * <h3>Usage Example</h3>
 *
 * <p>Here is a sketch of a service which crawls a website and uses the scheduling capabilities to
 * rate limit itself.
 *
 * <pre>{@code