En particular, cuando corras en **Kubernetes** probablemente **no** querrás usar workers y en cambio correr **un solo proceso de Uvicorn por contenedor**, pero te contaré sobre eso más adelante en ese capítulo.

///

## Múltiples Workers { #multiple-workers }

Puedes iniciar múltiples workers con la opción de línea de comando `--workers`:

//// tab | `fastapi`

Si usas el comando `fastapi`:

<div class="termy">

///

## Mehrere Worker { #multiple-workers }

Sie können mehrere Worker mit der `--workers`-Befehlszeilenoption starten:

//// tab | `fastapi`

Wenn Sie den `fastapi`-Befehl verwenden:

<div class="termy">

```console
$ <font color="#4E9A06">fastapi</font> run --workers 4 <u style="text-decoration-style:solid">main.py</u>

In particular, when running on **Kubernetes** you will probably **not** want to use workers and instead run **a single Uvicorn process per container**, but I'll tell you about it later in that chapter.

///

## Multiple Workers { #multiple-workers }

You can start multiple workers with the `--workers` command line option:

//// tab | `fastapi`

If you use the `fastapi` command:

<div class="termy">

///

## Несколько воркеров { #multiple-workers }

Можно запустить несколько воркеров с помощью опции командной строки `--workers`:

//// tab | `fastapi`

Если вы используете команду `fastapi`:

<div class="termy">

```console
$ <font color="#4E9A06">fastapi</font> run --workers 4 <u style="text-decoration-style:solid">main.py</u>

///

## Vários trabalhadores { #multiple-workers }

Você pode iniciar vários trabalhadores com a opção de linha de comando `--workers`:

//// tab | `fastapi`

Se você usar o comando `fastapi`:

<div class="termy">

```console
$ <font color="#4E9A06">fastapi</font> run --workers 4 <u style="text-decoration-style:solid">main.py</u>

load, number of objects in the object store as well as storage speed. In addition, any bandwidth limits set via `mc admin bucket remote add` could also contribute to replication speed. The number of workers used for replication defaults to 100. Based on network bandwidth and system load, the number of workers used in replication can be configured using `mc admin config set alias api` to set the `replication_workers`. The prometheus metrics exposed by MinIO can be used to plan resource allocation and bandwidth...

	if (checkOld > 0 && len(p.workers) != checkOld) || n == len(p.workers) || n < 1 {
		// Either already satisfied or worker count changed while we waited for the lock.
		return
	}
	for len(p.workers) < n {
		input := make(chan ReplicationWorkerOperation, 10000)
		p.workers = append(p.workers, input)

		go p.AddWorker(input, &p.activeWorkers)
	}
	for len(p.workers) > n {
		worker := p.workers[len(p.workers)-1]

| `minio_node_replication_average_active_workers`         | Average number of active replication workers                                                             |
| `minio_node_replication_max_active_workers`             | Maximum number of active replication workers seen since server start                                     |

	es.mu.Lock()
	defer es.mu.Unlock()
	var workers []chan expiryOp
	if v := es.workers.Load(); v != nil {
		// Copy to new array.
		workers = append(workers, *v...)
	}

	if n == len(workers) || n < 1 {
		return
	}

	for len(workers) < n {
		input := make(chan expiryOp, 10000)
		workers = append(workers, input)
		go es.Worker(input)
		es.stats.workers.Add(1)
	}

	for len(workers) > n {

E se você precisar ter múltiplos workers, você pode simplesmente usar a opção de linha de comando `--workers`.

/// note | Detalhes Técnicos

A imagem Docker foi criada quando o Uvicorn não suportava gerenciar e reiniciar workers mortos, então era necessário usar o Gunicorn com o Uvicorn, o que adicionava bastante complexidade, apenas para que o Gunicorn gerenciasse e reiniciasse os processos workers do Uvicorn.