<img src="https://github.com/fastapi/fastapi/workflows/Test/badge.svg?event=push&branch=master" alt="Test">
</a>
<a href="https://coverage-badge.samuelcolvin.workers.dev/redirect/fastapi/fastapi" target="_blank">
    <img src="https://coverage-badge.samuelcolvin.workers.dev/fastapi/fastapi.svg" alt="Coverage">
</a>
<a href="https://pypi.org/project/fastapi" target="_blank">

    <img src="https://github.com/fastapi/fastapi/workflows/Test/badge.svg?event=push&branch=master" alt="Test">
</a>
<a href="https://coverage-badge.samuelcolvin.workers.dev/redirect/fastapi/fastapi" target="_blank">
    <img src="https://coverage-badge.samuelcolvin.workers.dev/fastapi/fastapi.svg" alt="Coverage">
</a>
<a href="https://pypi.org/project/fastapi" target="_blank">

    public static final String UNSAFE_URL = "unsafe-url";
  }

  /**
   * The HTTP <a href="https://www.w3.org/TR/service-workers/#update-algorithm">{@code
   * Service-Worker}</a> header field name.
   *
   * @since 20.0
   */
  public static final String SERVICE_WORKER = "Service-Worker";
  /** The HTTP {@code TE} header field name. */
  public static final String TE = "TE";

因此，在这种情况下，你**不会**希望拥有像 Gunicorn 和 Uvicorn worker一样的进程管理器，或者 Uvicorn 使用自己的 Uvicorn worker。 你可能希望每个容器（但可能有多个容器）只有一个**单独的 Uvicorn 进程**。

在容器内拥有另一个进程管理器（就像使用 Gunicorn 或 Uvicorn 管理 Uvicorn 工作线程一样）只会增加**不必要的复杂性**，而你很可能已经在集群系统中处理这些复杂性了。

### 具有多个进程的容器

当然，在某些**特殊情况**，你可能希望拥有 **一个容器**，其中包含 **Gunicorn 进程管理器**，并在其中启动多个 **Uvicorn worker进程**。

Но часто Вам может понадобиться несколько одновременно работающих одинаковых процессов.

### Множество процессов - Воркеры (Workers)

		Help:      "Total number of active replication workers",
		Type:      gaugeMetric,
	}
}

func getClusterReplAvgActiveWorkersCountMD() MetricDescription {
	return MetricDescription{
		Namespace: nodeMetricNamespace,
		Subsystem: replicationSubsystem,
		Name:      avgActiveWorkers,
		Help:      "Average number of active replication workers",
		Type:      gaugeMetric,
	}
}

## 🛂 ☁ 🖼 ⏮️ 🐁 - Uvicorn

📤 🛂 ☁ 🖼 👈 🔌 🐁 🏃‍♂ ⏮️ Uvicorn 👨‍🏭, ℹ ⏮️ 📃: [💽 👨‍🏭 - 🐁 ⏮️ Uvicorn](server-workers.md){.internal-link target=_blank}.

👉 🖼 🔜 ⚠ ✴️ ⚠ 🔬 🔛: [📦 ⏮️ 💗 🛠️ & 🎁 💼](#_18).

Aqui estão algumas combinações e estratégias possíveis:

* **Uvicorn** com `--workers`
    * Um **gerenciador de processos** Uvicorn escutaria no **IP** e na **porta** e iniciaria **vários processos de trabalho Uvicorn**.
* **Kubernetes** e outros **sistemas de contêineres** distribuídos

        decides which workers to read from. If `"ANY"`, TF workers read from any
        tf.data service workers. If `"LOCAL"`, TF workers will only read from
        local in-processs tf.data service workers. `"AUTO"` works well for most
        cases, while users can specify other targets. For example, `"LOCAL"`
        would help avoid RPCs and data copy if every TF worker colocates with a

	if source.noWait {
		select {
		case globalBackgroundHealRoutine.tasks <- task:
			if serverDebugLog {
				fmt.Printf("Task in the queue: %#v\n", task)
			}
		default:
			// task queue is full, no more workers, we shall move on and heal later.
			return nil
		}
		// Don't wait for result
		return nil
	}

	// respCh must be set to wait for result.
	// We make it size 1, so a result can always be written