int port = tensorflow::testing::PickUnusedPortOrDie();
  // 3. Replace worker1 with a new worker in server_def_0 and server_def_1.
  ReplaceTaskInServerDef(&server_def_0, /*task_index=*/1, "localhost", port);
  ReplaceTaskInServerDef(&server_def_1, /*task_index=*/1, "localhost", port);
  // 4. Start a new task to replace worker1.
  server_def_0.set_task_index(1);
  worker_server1.release();

///

## Кілька працівників { #multiple-workers }

Ви можете запустити кілька працівників за допомогою параметра командного рядка `--workers`:

//// tab | `fastapi`

Якщо ви використовуєте команду `fastapi`:

<div class="termy">

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

		// If the channel reaches above half capacity
		// we spawn more workers. The workers spawned
		// from this main worker routine will exit
		// once the channel drops below half capacity
		// and when it's been at least 30 seconds since
		// we launched a new worker.
		if mainWorker && len(h.logCh) > cap(h.logCh)/2 {
			nWorkers := h.workers.Load()
			if nWorkers < h.maxWorkers {
				if time.Since(h.lastStarted).Milliseconds() > 10 {

    <!-- These packages are duplicated in workers and daemon-server-worker, don't require a package-info.java in each place -->
    <suppress checks="JavadocPackage"
              files=".*[/\\]platforms[/\\]core-execution[/\\]daemon-server-worker[/\\]src[/\\]main[/\\]java[/\\]org[/\\]gradle[/\\]workers[/\\][^/\\]+"/>

    <!-- These packages are duplicated in code-quality and code-quality-workers, don't require a package-info.java in each place -->

    "crossVersionTests": false
  },
  {
    "name": "scala-compiler-worker",
    "path": "platforms/jvm/scala-compiler-worker",
    "unitTests": false,
    "functionalTests": false,
    "crossVersionTests": false
  },
  {
    "name": "scaladoc-worker",
    "path": "platforms/jvm/scaladoc-worker",
    "unitTests": false,
    "functionalTests": false,
    "crossVersionTests": false

RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt

COPY ./app /code/app

# (1)!
CMD ["fastapi", "run", "app/main.py", "--port", "80", "--workers", "4"]
```

1. Burada worker sayısını 4 yapmak için `--workers` komut satırı seçeneğini kullanıyoruz.

Bunun mantıklı olabileceği birkaç örnek:

#### Basit Bir Uygulama { #a-simple-app }

Here are some possible combinations and strategies:

* **Uvicorn** with `--workers`
    * One Uvicorn **process manager** would listen on the **IP** and **port**, and it would start **multiple Uvicorn worker processes**.
* **Kubernetes** and other distributed **container systems**

And if you need to have multiple workers, you can simply use the `--workers` command line option.

/// note | Technical Details

The Docker image was created when Uvicorn didn't support managing and restarting dead workers, so it was needed to use Gunicorn with Uvicorn, which added quite some complexity, just to have Gunicorn manage and restart the Uvicorn worker processes.

因此，这种情况下你**不希望**在容器内再启多个 workers（例如通过 `--workers` 命令行选项）。你会希望每个容器仅有一个**单独的 Uvicorn 进程**（但可能会有多个容器）。

在容器内再放一个进程管理器（就像启多个 workers 一样）只会引入**不必要的复杂性**，而这些你很可能已经在集群系统中处理了。

### 具有多个进程和特殊情况的容器 { #containers-with-multiple-processes-and-special-cases }

当然，也有一些**特殊情况**，你可能希望让**一个容器**里运行多个 **Uvicorn worker 进程**。

在这些情况下，你可以使用 `--workers` 命令行选项来设置要运行的 worker 数量：

```{ .dockerfile .annotate }
FROM python:3.14

Donc, dans ce cas, vous **ne voudrez pas** avoir plusieurs workers dans le conteneur, par exemple avec l'option de ligne de commande `--workers`. Vous voudrez avoir **un seul processus Uvicorn** par conteneur (mais probablement plusieurs conteneurs).