return
		}
	}
}

func (sr *SRStats) updateMovingAvg() {
	sr.lock.Lock()
	defer sr.lock.Unlock()
	for _, s := range sr.M {
		s.XferRateLrg.measure.updateExponentialMovingAverage(time.Now())
		s.XferRateSml.measure.updateExponentialMovingAverage(time.Now())
	}
}

// SRMetric captures replication metrics for a deployment
type SRMetric struct {

| `minio_cluster_health_erasure_set_healing_drives` | Count of healing drives in the erasure set     |
| `minio_cluster_health_erasure_set_online_drives`  | Count of online drives in the erasure set      |
| `minio_cluster_health_erasure_set_read_quorum`    | Get read quorum of the erasure set             |
| `minio_cluster_health_erasure_set_write_quorum`   | Get write quorum of the erasure set            |

	// so blockSizeV2 should be used for all future purposes.
	// this value is kept here to calculate the max API
	// requests based on RAM size for existing content.
	blockSizeV1 = 10 * humanize.MiByte

	// Block size used in erasure coding version 2.
	blockSizeV2 = 1 * humanize.MiByte

	// Buckets meta prefix.
	bucketMetaPrefix = "buckets"

	// Deleted Buckets prefix.
	deletedBucketsPrefix = ".deleted"

///

## Importez le `BaseModel` de Pydantic

Commencez par importer la classe `BaseModel` du module `pydantic` :

{* ../../docs_src/body/tutorial001.py hl[4] *}

## Créez votre modèle de données

Déclarez ensuite votre modèle de données en tant que classe qui hérite de `BaseModel`.

Utilisez les types Python standard pour tous les attributs :

{* ../../docs_src/body/tutorial001.py hl[7:11] *}

const (
	None Fault = iota
	MissingContentLength
	TooBigObject
	TooBigDecodedLength
	BadSignature
	BadMD5
	MissingUploadID
)

// Wrapper for calling HeadObject API handler tests for both Erasure multiple disks and FS single drive setup.
func TestAPIHeadObjectHandler(t *testing.T) {
	ExecObjectLayerAPITest(ExecObjectLayerAPITestArgs{t: t, objAPITest: testAPIHeadObjectHandler, endpoints: []string{"HeadObject"}})
}

MinIO is built ground up on the cloud-native premise. With features like erasure-coding, distributed and shared setup, it focuses only on storage and does it very well. While, it can be scaled by just replicating MinIO instances per tenant via an orchestration platform.

* [MinIO in a Container Installation Guide](https://docs.min.io/community/minio-object-store/operations/deployments/baremetal-deploy-minio-as-a-container.html)

	if err := newTestConfig(globalMinioDefaultRegion, obj); err != nil {
		t.Fatalf("Initializing config.json failed")
	}

	// Register the API end points with Erasure/FS object layer.
	apiRouter := initTestAPIEndPoints(obj, []string{"PostPolicy"})

	credentials := globalActiveCred
	bucketName := minioMetaBucket
	objectName := "config/x"

	"io"
)

// Implementation to calculate bitrot for the whole file.
type wholeBitrotWriter struct {
	disk      StorageAPI
	volume    string
	filePath  string
	shardSize int64 // This is the shard size of the erasure logic
	hash.Hash       // For bitrot hash
}

func (b *wholeBitrotWriter) Write(p []byte) (int, error) {
	err := b.disk.AppendFile(context.TODO(), b.volume, b.filePath, p)
	if err != nil {
		return 0, err
	}

NOTE:

- `timeToFirstByte` and `timeToResponse` will be expressed in Nanoseconds.
- Additionally in the case of the erasure coded setup `tags.objectLocation` provides per object details about
  - Pool number the object operation was performed on.
  - Set number the object operation was performed on.