}

	return sm, nil
}

func getLatency(promAPI promv1.API, workloadName, workloadNamespace string, duration time.Duration, quantile float64) (time.Duration, error) {
	latencyQuery := fmt.Sprintf(`histogram_quantile(%f, sum(rate(%s_bucket{%s=~"%s.*", %s=~"%s.*",reporter="destination"}[%s])) by (le))`,
		quantile, reqDur, destWorkloadLabel, workloadName, destWorkloadNamespaceLabel, workloadNamespace, duration)

    * Si on compare Uvicorn, il faut le comparer à d'autre applications de serveurs comme Daphne, Hypercorn, uWSGI, etc.
* **Starlette** :

                     "intervalFactor": 2,
                     "legendFormat": "{{cluster}} - {{namespace}} - {{name}} - mean\n"
                  }
               ],
               "title": "Workqueue Waiting Duration Quantile",
               "type": "timeseries"
            },
            {
               "datasource": {
                  "type": "datasource",
                  "uid": "-- Mixed --"
               },

    for (int i = fromIndex; i < toIndex; i++) {
      array[i] ^= Long.MAX_VALUE;
    }
  }

  /**
   * Returns dividend / divisor, where the dividend and divisor are treated as unsigned 64-bit
   * quantities.
   *
   * <p><b>Java 8+ users:</b> use {@link Long#divideUnsigned(long, long)} instead.
   *
   * @param dividend the dividend (numerator)
   * @param divisor the divisor (denominator)

// places. Numbers larger or more precise will be capped or rounded up.
// (E.g.: 0.1m will rounded up to 1m.)
// This may be extended in the future if we require larger or smaller quantities.
//
// When a Quantity is parsed from a string, it will remember the type of suffix
// it had, and will use the same type again when it is serialized.
//
// Before serializing, Quantity will be put in "canonical form".

    for (int i = fromIndex; i < toIndex; i++) {
      array[i] ^= Integer.MAX_VALUE;
    }
  }

  /**
   * Returns dividend / divisor, where the dividend and divisor are treated as unsigned 32-bit
   * quantities.
   *
   * <p><b>Java 8+ users:</b> use {@link Integer#divideUnsigned(int, int)} instead.
   *
   * @param dividend the dividend (numerator)
   * @param divisor the divisor (denominator)

    for (int i = fromIndex; i < toIndex; i++) {
      array[i] ^= Integer.MAX_VALUE;
    }
  }

  /**
   * Returns dividend / divisor, where the dividend and divisor are treated as unsigned 32-bit
   * quantities.
   *
   * <p><b>Java 8+ users:</b> use {@link Integer#divideUnsigned(int, int)} instead.
   *
   * @param dividend the dividend (numerator)
   * @param divisor the divisor (denominator)

### Testé

* 100% <abbr title="La quantité de code qui est testé automatiquement">de couverture de test</abbr>.

* GPU
    * Support for NVIDIA GPUs with compute capability 8.9 (e.g. L4 & L40) has been added to TF binary distributions (Python wheels).
* Replace `DebuggerOptions` of TensorFlow Quantizer, and migrate to `DebuggerConfig` of StableHLO Quantizer.
* Add TensorFlow to StableHLO converter to TensorFlow pip package.
* TensorRT support: this is the last release supporting TensorRT. It will be removed in the next release.

Cela prendrait autant de temps pour finir avec ou sans sections (concurrence) et vous auriez effectué la même quantité de travail.