cpuNice:           "CPU nice time",
		cpuLoad1:          "CPU load average 1min",
		cpuLoad5:          "CPU load average 5min",
		cpuLoad15:         "CPU load average 15min",
		cpuLoad1Perc:      "CPU load average 1min (percentage)",
		cpuLoad5Perc:      "CPU load average 5min (percentage)",
		cpuLoad15Perc:     "CPU load average 15min (percentage)",
	}
	resourceMetricsGroups = []*MetricsGroupV2{

}

// exponentialMovingAverage calculates the exponential moving average
func exponentialMovingAverage(beta, previousAvg, incrementAvg float64) float64 {
	return (1-beta)*incrementAvg + beta*previousAvg
}

// getExpMovingAvgBytesPerSecond returns the exponential moving average for the bucket/target in bytes
func (m *rateMeasurement) getExpMovingAvgBytesPerSecond() float64 {
	m.lock.Lock()

    /**
     * Calculate average send latency in microseconds
     *
     * @return average send latency
     */
    public double getAverageSendLatencyMicros() {
        long sends = rdmaSends.get();
        if (sends == 0) {
            return 0.0;
        }
        return totalSendTime.get() / (double) sends / 1000.0; // Convert to microseconds
    }

    /**
     * Calculate average receive latency in microseconds

| `minio_node_cpu_avg_load5`           | CPU load average 5min.                     |
| `minio_node_cpu_avg_load5_avg`       | CPU load average 5min (avg).               |
| `minio_node_cpu_avg_load5_max`       | CPU load average 5min (max).               |
| `minio_node_cpu_avg_load5_perc`      | CPU load average 5min (percentage).        |

{"attributes":{"description":"","kibanaSavedObjectMeta":{"searchSourceJSON":"{\"query\":{\"query\":\"\",\"language\":\"kuery\"},\"filter\":[],\"indexRefName\":\"kibanaSavedObjectMeta.searchSourceJSON.index\"}"},"title":"average-response-time","uiStateJSON":"{}","version":1,"visState":"{\"title\":\"average-response-time\",\"type\":\"area\",\"params\":{\"type\":\"area\",\"grid\":{\"categoryLines\":false},\"categoryAxes\":[{\"id\":\"CategoryAxis-1\",\"type\":\"category\",\"position\":\"bottom\",\"show\":true,\"...

 *       <ul>
 *         <li>2 levels: average of 64ns per lock()/unlock()
 *         <li>3 levels: average of 77ns per lock()/unlock()
 *         <li>4 levels: average of 99ns per lock()/unlock()
 *         <li>5 levels: average of 103ns per lock()/unlock()
 *         <li>10 levels: average of 184ns per lock()/unlock()
 *         <li>20 levels: average of 393ns per lock()/unlock()
 *       </ul>
 * </ul>
 *

            // Analyze timing consistency across threads
            if (!timings.isEmpty()) {
                double avgTime = timings.stream().mapToLong(Long::longValue).average().orElse(0.0);
                long maxTime = timings.stream().mapToLong(Long::longValue).max().orElse(0L);
                long minTime = timings.stream().mapToLong(Long::longValue).min().orElse(0L);

Et c'est le même niveau de performance que celui obtenu avec **FastAPI**.

 * you would expect.
 *
 * <p>If required to do a weighted average between an infinity and a finite value, or between an
 * infinite value and itself, the infinite value is returned. If required to do a weighted average
 * between {@link Double#NEGATIVE_INFINITY NEGATIVE_INFINITY} and {@link Double#POSITIVE_INFINITY

 *       <ul>
 *         <li>2 levels: average of 64ns per lock()/unlock()
 *         <li>3 levels: average of 77ns per lock()/unlock()
 *         <li>4 levels: average of 99ns per lock()/unlock()
 *         <li>5 levels: average of 103ns per lock()/unlock()
 *         <li>10 levels: average of 184ns per lock()/unlock()
 *         <li>20 levels: average of 393ns per lock()/unlock()
 *       </ul>
 * </ul>
 *