}
		nextFiles = next
	}

	for _, c := range contexts {
		c.Compiler = build.Default.Compiler
	}

	walkers := make([]*Walker, len(contexts))
	var wg sync.WaitGroup
	for i, context := range contexts {
		i, context := i, context
		wg.Add(1)
		go func() {
			defer wg.Done()
			walkers[i] = NewWalker(context, filepath.Join(testenv.GOROOT(t), "src"))
		}()
	}
	wg.Wait()

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">

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

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

//// tab | `fastapi`

Si usas el comando `fastapi`:

<div class="termy">

```console

## 구니콘을 유비콘 워커와 함께 실행하기

설치 후 구니콘 실행하기:

<div class="termy">

```console
$ gunicorn main:app --workers 4 --worker-class uvicorn.workers.UvicornWorker --bind 0.0.0.0:80

[19499] [INFO] Starting gunicorn 20.1.0
[19499] [INFO] Listening at: http://0.0.0.0:80 (19499)
[19499] [INFO] Using worker: uvicorn.workers.UvicornWorker
[19511] [INFO] Booting worker with pid: 19511
[19513] [INFO] Booting worker with pid: 19513

///

## Vários trabalhadores

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...

| `minio_cluster_usage_buckets_versions_count`                    | Total object versions count in bucket, including delete markers. <br><br>Type: gauge | `bucket`          |
| `minio_cluster_usage_buckets_delete_markers_count`              | Total delete markers count in bucket. <br><br>Type: gauge                            | `bucket`          |

	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]

	oi, ok := oiCache[fmt.Sprintf("%s-%s", toDel.ObjectName, toDel.VersionID)]
	return oi, ok
}

func batchObjsForDelete(ctx context.Context, r *BatchJobExpire, ri *batchJobInfo, job BatchJobRequest, api ObjectLayer, wk *workers.Workers, expireCh <-chan []expireObjInfo) {
	vc, _ := globalBucketVersioningSys.Get(r.Bucket)
	retryAttempts := job.Expire.Retry.Attempts
	if retryAttempts <= 0 {
		retryAttempts = batchExpireJobDefaultRetries
	}

| `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                                     |