},
          "exemplar": true,
          "expr": "sum by (bucket) (rate(minio_bucket_traffic_sent_bytes{job=\"$scrape_jobs\"}[$__rate_interval]))",
          "interval": "1m",
          "intervalFactor": 2,
          "legendFormat": "Data Sent [{{bucket}}]",
          "refId": "A"
        }
      ],
      "title": "Total Data Sent Rate",
      "type": "timeseries"
    },
    {
      "datasource": {

	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"

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",...

Rabbit with pink eyes ran close by her.

  There was nothing so VERY remarkable in that; nor did Alice
think it so VERY much out of the way to hear the Rabbit say to
itself, `Oh dear!  Oh dear!  I shall be late!'  (when she thought
it over afterwards, it occurred to her that she ought to have
wondered at this, but at the time it all seemed quite natural);
but when the Rabbit actually TOOK A WATCH OUT OF ITS WAISTCOAT-

Rabbit with pink eyes ran close by her.

  There was nothing so VERY remarkable in that; nor did Alice
think it so VERY much out of the way to hear the Rabbit say to
itself, `Oh dear!  Oh dear!  I shall be late!'  (when she thought
it over afterwards, it occurred to her that she ought to have
wondered at this, but at the time it all seemed quite natural);
but when the Rabbit actually TOOK A WATCH OUT OF ITS WAISTCOAT-

          "format": "time_series",
          "intervalFactor": 1,
          "range": true,
          "refId": "A"
        }
      ],
      "title": "Client Success Rate (non-5xx responses)",
      "type": "stat"
    },
    {
      "datasource": {
        "type": "prometheus",
        "uid": "${datasource}"
      },
      "fieldConfig": {
        "defaults": {

          "format": "time_series",
          "intervalFactor": 1,
          "refId": "A"
        }
      ],
      "title": "Incoming Success Rate (non-5xx responses)",
      "type": "stat"
    },
    {
      "datasource": {
        "type": "prometheus",
        "uid": "${datasource}"
      },
      "fieldConfig": {
        "defaults": {

      * if the new state is "partialDisruption" or "fullDisruption" we call a user defined function that returns a new QPS to use (default 1/10 of the default rate, and the default rate respectively),
      * if the new state is "normal" we resume normal operation (go back to default limiter settings),
      * if all zones in the cluster are in "fullDisruption" state we stop all evictions.

   *
   * The Least Recently Used page replacement algorithm was chosen due to its simplicity, high hit
   * rate, and ability to be implemented with O(1) time complexity. The initial LRU implementation
   * operates per-segment rather than globally for increased implementation simplicity. We expect
   * the cache hit rate to be similar to that of a global LRU algorithm.
   */

  // Constants

  /**

   *
   * The Least Recently Used page replacement algorithm was chosen due to its simplicity, high hit
   * rate, and ability to be implemented with O(1) time complexity. The initial LRU implementation
   * operates per-segment rather than globally for increased implementation simplicity. We expect
   * the cache hit rate to be similar to that of a global LRU algorithm.
   */

  // Constants

  /**