}

// 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()

| `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).        |

	sysCPUUser      = "user"
)

var (
	sysCPUAvgIdleMD   = NewGaugeMD(sysCPUAvgIdle, "Average CPU idle time")
	sysCPUAvgIOWaitMD = NewGaugeMD(sysCPUAvgIOWait, "Average CPU IOWait time")
	sysCPULoadMD      = NewGaugeMD(sysCPULoad, "CPU load average 1min")
	sysCPULoadPercMD  = NewGaugeMD(sysCPULoadPerc, "CPU load average 1min (percentage)")
	sysCPUNiceMD      = NewGaugeMD(sysCPUNice, "CPU nice time")

var (
	replicationAverageActiveWorkersMD = NewGaugeMD(replicationAverageActiveWorkers,
		"Average number of active replication workers")
	replicationAverageQueuedBytesMD = NewGaugeMD(replicationAverageQueuedBytes,
		"Average number of bytes queued for replication since server start")
	replicationAverageQueuedCountMD = NewGaugeMD(replicationAverageQueuedCount,
		"Average number of objects queued for replication since server start")

| `minio_system_cpu_avg_idle`   | Average CPU idle time. <br><br>Type: gauge              | `server` |
| `minio_system_cpu_avg_iowait` | Average CPU IOWait time. <br><br>Type: gauge            | `server` |
| `minio_system_cpu_load`       | CPU load average 1min. <br><br>Type: gauge              | `server` |
| `minio_system_cpu_load_perc`  | CPU load average 1min (percentage). <br><br>Type: gauge | `server` |

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

   * provides more control over the underlying data structure.
   *
   * @param expectedKeys the expected number of distinct keys
   * @param expectedValuesPerKey the expected average number of values per key
   * @throws IllegalArgumentException if {@code expectedKeys} or {@code expectedValuesPerKey} is
   *     negative
   */

		Name:      avgLinkLatency,
		Help:      "Average replication link latency in milliseconds",
		Type:      gaugeMetric,
	}
}

func getClusterReplAvgQueuedOperationsMD() MetricDescription {
	return MetricDescription{
		Namespace: nodeMetricNamespace,
		Subsystem: replicationSubsystem,
		Name:      avgInQueueCount,
		Help:      "Average number of objects queued for replication since server uptime",

      assertEquivalent(stats.mean(), stream(array).average().getAsDouble());
      assertEquivalent(stats.sum(), stream(array).sum());
      assertEquivalent(stats.max(), stream(array).max().getAsDouble());
      assertEquivalent(stats.min(), stream(array).min().getAsDouble());
      // static method on Stats vs on instance method on DoubleStream
      assertEquivalent(Stats.meanOf(array), stream(array).average().getAsDouble());

---

FastAPI è un web framework moderno e veloce (a prestazioni elevate) che serve a creare API con Python 3.6+ basato sulle annotazioni di tipo di Python.

Le sue caratteristiche principali sono:

* **Velocità**: Prestazioni molto elevate, alla pari di **NodeJS** e **Go** (grazie a Starlette e Pydantic). [Uno dei framework Python più veloci in circolazione](#performance).