},
          "exemplar": true,
          "expr": "sum by (server) (minio_cluster_replication_average_transfer_rate{job=\"$scrape_jobs\"})",
          "interval": "1m",
          "intervalFactor": 2,
          "legendFormat": "{{server}}",
          "refId": "A"
        }
      ],
      "title": "Avg. Transfer Rate (bytes/s)",
      "type": "timeseries"
    },
    {
      "datasource": {
        "type": "prometheus",

	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
	})
	if err != nil {
		return nil, err
	}

 *       token attempt, one measure of the quality of a hash function is <i>how well</i> it succeeds
 *       at this goal. Important note: it may be easy to achieve the theoretical minimum collision
 *       rate when using completely <i>random</i> sample input. The true test of a hash function is
 *       how it performs on representative real-world data, which tends to contain many hidden

          "expr": "sum by (server) (minio_cluster_replication_average_transfer_rate{job=\"$scrape_jobs\"})",
          "interval": "1m",
          "intervalFactor": 2,
          "legendFormat": "{{server}}",
          "refId": "A"
        }
      ],
      "thresholds": [],
      "timeRegions": [],
      "title": "Avg. Transfer Rate (bytes/s)",
      "tooltip": {
        "shared": true,
        "sort": 0,

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

1, "legendFormat": "Rejected LDS Configs", "refId": "B" }, { "expr": "sum(rate(pilot_xds_write_timeout{app=\"istiod\"}[1m]))", "format": "time_series", "intervalFactor": 1, "legendFormat": "Write Timeouts", "refId": "F" }, { "expr": "sum(rate(pilot_total_xds_internal_errors{app=\"istiod\"}[1m]))", "format": "time_series", "hide": false, "intervalFactor": 1, "legendFormat": "Internal Errors", "refId": "H" }, { "expr": "sum(rate(pilot_total_xds_rejects{app=\"istiod\"}[1m]))", "format": "time_series",...

		Code:           "SlowDownRead",
		Description:    "Resource requested is unreadable, please reduce your request rate",
		HTTPStatusCode: http.StatusServiceUnavailable,
	},
	ErrSlowDownWrite: {
		Code:           "SlowDownWrite",
		Description:    "Resource requested is unwritable, please reduce your request rate",
		HTTPStatusCode: http.StatusServiceUnavailable,
	},
	ErrMaxVersionsExceeded: {

	receivedCount      MetricName = "received_count"
	sentCount          MetricName = "sent_count"
	currTransferRate   MetricName = "current_transfer_rate"
	avgTransferRate    MetricName = "average_transfer_rate"
	maxTransferRate    MetricName = "max_transfer_rate"
	credentialErrors   MetricName = "credential_errors"

	currLinkLatency MetricName = "current_link_latency_ms"
	avgLinkLatency  MetricName = "average_link_latency_ms"

  - "routeTableCacheTTLInSeconds"
  ([#86266](https://github.com/kubernetes/kubernetes/pull/86266), [@zqingqing1](https://github.com/zqingqing1)) [SIG Cloud Provider]

          Assert.assertEquals(0.50d, prob, epsilon);
        }
      }
    }
  }

  /**
   * Checks that a Hasher returns the same HashCode when given the same input, and also that the
   * collision rate looks sane.
   */
  static void assertInvariants(HashFunction hashFunction) {
    int objects = 100;
    Set<HashCode> hashcodes = Sets.newHashSetWithExpectedSize(objects);
    Random random = new Random(314159);