* L'apprentissage automatique (ou **Machine Learning**) : cela nécessite de nombreuses multiplications de matrices et vecteurs. Imaginez une énorme feuille de calcul remplie de nombres que vous multiplierez entre eux tous au même moment.

* **Machine Learning**: normalmente requiere muchas multiplicaciones de "matrices" y "vectores". Piensa en una enorme hoja de cálculo con números y multiplicando todos juntos al mismo tiempo.

type minioCollector struct {
	desc *prometheus.Desc
}

// Describe sends the super-set of all possible descriptors of metrics
func (c *minioCollector) Describe(ch chan<- *prometheus.Desc) {
	ch <- c.desc
}

// Collect is called by the Prometheus registry when collecting metrics.
func (c *minioCollector) Collect(ch chan<- prometheus.Metric) {
	// Expose MinIO's version information

	name := rm.Name
	metrics := make([]MetricV2, 0, 3)
	metrics = append(metrics, MetricV2{
		Description:    getResourceMetricDescription(subSys, name, help),
		Value:          rm.Current,
		VariableLabels: cloneMSS(rm.Labels),
	})

	if requireAvgMax {
		avgName := MetricName(fmt.Sprintf("%s_avg", name))
		avgHelp := fmt.Sprintf("%s (avg)", help)
		metrics = append(metrics, MetricV2{

)

// Collector paths.
//
// These are paths under the top-level /minio/metrics/v3 metrics endpoint. Each
// of these paths returns a set of V3 metrics.
//
// Per-bucket metrics endpoints always start with /bucket and the bucket name is
// appended to the path. e.g. if the collector path is /bucket/api, the endpoint
// for the bucket "mybucket" would be /minio/metrics/v3/bucket/api/mybucket
const (

		}
		return nil
	}
}

// MetricsGroup - represents a group of metrics. It includes a `MetricsLoaderFn`
// function that provides a way to load the metrics from the system. The metrics
// are cached and refreshed after a given timeout.
//
// For metrics with a `bucket` dimension, a list of buckets argument is required
// to collect the metrics.
//
// It implements the prometheus.Collector interface for metric groups without a

type InQueueStats struct {
	nowBytes   int64 `json:"-"`
	nowCount   int64 `json:"-"`
	histCounts metrics.Histogram
	histBytes  metrics.Histogram
}

func newInQueueStats(r metrics.Registry, lbl string) InQueueStats {
	histCounts := metrics.NewHistogram(metrics.NewUniformSample(100))
	histBytes := metrics.NewHistogram(metrics.NewUniformSample(100))

	r.Register("replication.queue.counts."+lbl, histCounts)

Harshavardhana <******@****.***> 1745441778 -0700

	deletes := make([]uint64, len(infos))
	writes := make([]uint64, len(infos))
	for index, di := range infos {
		deletes[index] = di.Metrics.TotalDeletes
		writes[index] = di.Metrics.TotalWrites
	}

	filter := func(list []uint64) (commonCount uint64) {
		maxCnt := 0
		signatureMap := map[uint64]int{}
		for _, v := range list {
			signatureMap[v]++
		}

# Metrics Version 3

In metrics version 3, all metrics are available under the following base endpoint:

```
/minio/metrics/v3
```

To query metrics of a specific type, append the appropriate path to the base endpoint.
Querying the base endpoint returns "404 Not Found."

Metrics are organized into groups at paths **relative** to the top-level endpoint above.