So, in this case, you **would not** want to have a process manager like Gunicorn with Uvicorn workers, or Uvicorn using its own Uvicorn workers. You would want to have just a **single Uvicorn process** per container (but probably multiple containers).

	if v := globalHealConfig.GetWorkers(); v > 0 {
		numHealers = uint64(v)
	}

	healingLogEvent(ctx, fmt.Sprintf("Healing drive '%s' - use %d parallel workers.", tracker.disk.String(), numHealers))

	jt, _ := workers.New(int(numHealers))

	var retErr error
	// Heal all buckets with all objects
	for _, bucket := range healBuckets {
		if tracker.isHealed(bucket) {
			continue
		}

				return false
			}
		}
		return true
	}

	workerSize, err := strconv.Atoi(env.Get("_MINIO_BATCH_KEYROTATION_WORKERS", strconv.Itoa(runtime.GOMAXPROCS(0)/2)))
	if err != nil {
		return err
	}

	wk, err := workers.New(workerSize)
	if err != nil {
		// invalid worker size.
		return err
	}

	retryAttempts := ri.RetryAttempts
	ctx, cancel := context.WithCancel(ctx)

	const envDecomWorkers = "_MINIO_DECOMMISSION_WORKERS"
	workerSize, err := env.GetInt(envDecomWorkers, len(pool.sets))
	if err != nil {
		decomLogIf(ctx, fmt.Errorf("invalid workers value err: %v, defaulting to %d", err, len(pool.sets)))
		workerSize = len(pool.sets)
	}

	// Each decom worker needs one List() goroutine/worker
	// add that many extra workers.
	workerSize += len(pool.sets)

    "crossVersionTests": false
  },
  {
    "name": "worker-processes",
    "path": "platforms/core-execution/worker-processes",
    "unitTests": true,
    "functionalTests": false,
    "crossVersionTests": false
  },
  {
    "name": "worker-services",
    "path": "platforms/core-runtime/worker-services",
    "unitTests": false,
    "functionalTests": false,

    listOf(
        // We pass the 'maxParallelForks' setting as 'workers.max' to limit the maximum number of executers even
        // if multiple test tasks run in parallel. We also pass it to the Gradle build as a maximum (maxParallelForks)
        // for each test task, such that we are independent of whatever default value is defined in the build itself.
        "-Dorg.gradle.workers.max=$maxParallelForks",
        "-PmaxParallelForks=$maxParallelForks",

      "coverage" : {
        "per_week" : [ "linux" ]
      }
    } ]
  }, {
    "testId" : "org.gradle.performance.experiment.java.ParallelBuildPerformanceTest.clean assemble with 4 parallel workers",
    "groups" : [ {
      "testProject" : "largeJavaMultiProject",
      "coverage" : {
        "per_week" : [ "linux" ]
      }
    }, {
      "testProject" : "largeMonolithicJavaProject",
      "coverage" : {

| `minio_cluster_replication_current_active_workers`         | Total number of active replication workers                                                               |
| `minio_cluster_replication_average_active_workers`         | Average number of active replication workers                                                             |

可以通过多种方法来实现这一目标，我将在接下来的章节中向您详细介绍具体策略，例如在谈论 Docker 和容器时。

要考虑的主要限制是必须有一个**单个**组件来处理**公共IP**中的**端口**。 然后它必须有一种方法将通信**传输**到复制的**进程/worker**。

以下是一些可能的组合和策略：

* **Gunicorn** 管理 **Uvicorn workers**
     * Gunicorn 将是监听 **IP** 和 **端口** 的 **进程管理器**，复制将通过 **多个 Uvicorn 工作进程** 进行
* **Uvicorn** 管理 **Uvicorn workers**
     * 一个 Uvicorn **进程管理器** 将监听 **IP** 和 **端口**，并且它将启动 **多个 Uvicorn 工作进程**
* **Kubernetes** 和其他分布式 **容器系统**

## Imagem Oficial do Docker com Gunicorn - Uvicorn

Há uma imagem oficial do Docker que inclui o Gunicorn executando com trabalhadores Uvicorn, conforme detalhado em um capítulo anterior: [Server Workers - Gunicorn com Uvicorn](server-workers.md){.internal-link target=_blank}.