A stand-alone MinIO server would go down if the server hosting the drives goes offline. In contrast, a distributed MinIO setup with _m_ servers and _n_ drives will have your data safe as long as _m/2_ servers or _m*n_/2 or more drives are online.

For example, an 16-server distributed setup with 200 drives per node would continue serving files, up to 4 servers can be offline in default configuration i.e around 800 drives down MinIO would continue to read and write objects.

| Minimum number of drives per server when server count is 1      | 02            |
| Minimum number of drives per server when server count is 2 or 3 | 01            |
| Minimum number of drives per server when server count is 4      | 01            |
| Maximum number of drives per server                             | no-limit      |
| Read quorum                                                     | N/2           |

Você também pode declarar um corpo como um `dict` com chaves de algum tipo e valores de outro tipo.

Sem ter que saber de antemão quais são os nomes de campos/atributos válidos (como seria o caso dos modelos Pydantic).

Isso seria útil se você deseja receber chaves que ainda não conhece.

---

Outro caso útil é quando você deseja ter chaves de outro tipo, por exemplo, `int`.

É isso que vamos ver aqui.

drives.  Therefore, the number of drives you present must be a multiple of one of these numbers.  Each object is written to a single erasure-coding set.

Minio uses the largest possible EC set size which divides into the number of drives given. For example, *18 drives* are configured as *2 sets of 9 drives*, and *24 drives* are configured as *2 sets of 12 drives*.  This is true for scenarios when running MinIO as a standalone erasure coded deployment. In [distributed setup however node (affinity)...

on 16 drive MinIO deployment. If you use eight data and eight parity drives, the file space usage will be approximately twice, i.e. 100 MiB
file will take 200 MiB space. But, if you use ten data and six parity drives, same 100 MiB file takes around 160 MiB. If you use 14 data and
two parity drives, 100 MiB file takes only approximately 114 MiB.

			buckets = append(buckets, BucketInfo{
				Name:    v.Name,
				Deleted: v.Created,
			})
		}
	}

	return buckets, nil
}

func cloneDrives(drives []StorageAPI) []StorageAPI {
	newDrives := make([]StorageAPI, len(drives))
	copy(newDrives, drives)
	return newDrives
}

func getBucketInfoLocal(ctx context.Context, bucket string, opts BucketOptions) (BucketInfo, error) {
	globalLocalDrivesMu.RLock()

- We limited the number of drives to 16 for erasure set because, erasure code shards more than 16 can become chatty and do not have any performance advantages. Additionally since 16 drive erasure set gives you tolerance of 8 drives per object by default which is plenty in any practical scenario.

import "context"

const (
	healthDrivesOfflineCount = "drives_offline_count"
	healthDrivesOnlineCount  = "drives_online_count"
	healthDrivesCount        = "drives_count"
)

var (
	healthDrivesOfflineCountMD = NewGaugeMD(healthDrivesOfflineCount,
		"Count of offline drives in the cluster")
	healthDrivesOnlineCountMD = NewGaugeMD(healthDrivesOnlineCount,
		"Count of online drives in the cluster")

If one or more drives are offline at the start of a PutObject or NewMultipartUpload operation the object will have additional data
protection bits added automatically to provide the regular safety for these objects up to 50% of the number of drives.
This will allow normal write operations to take place on systems that exceed the write tolerance.

 *  * [onHeaders] (unless canceled)
 *  * [onData] (optional sequence of data frames)
 *
 * As a stream ID is scoped to a single HTTP/2 connection, implementations which target multiple
 * connections should expect repetition of stream IDs.
 *
 * Return true to request cancellation of a pushed stream.  Note that this does not guarantee
 * future frames won't arrive on the stream ID.
 */
interface PushObserver {
  /**