### Multiple Processes - An Example

In this example, there's a **Manager Process** that starts and controls two **Worker Processes**.

This Manager Process would probably be the one listening on the **port** in the IP. And it would transmit all the communication to the worker processes.

The only new option here is `--workers` telling Uvicorn to start 4 worker processes.

You can also see that it shows the **PID** of each process, `27365` for the parent process (this is the **process manager**) and one for each worker process: `27368`, `27369`, `27370`, and `27367`.

## Deployment Concepts

A container is running as long as the **main process** (command or program) is running.

A container normally has a **single process**, but it's also possible to start subprocesses from the main process, and that way you will have **multiple processes** in the same container.

But it's not possible to have a running container without **at least one running process**. If the main process stops, the container stops.

These examples run the server program (e.g Uvicorn), starting **a single process**, listening on all the IPs (`0.0.0.0`) on a predefined port (e.g. `80`).

This is the basic idea. But you will probably want to take care of some additional things, like:

* Security - HTTPS
* Running on startup
* Restarts
* Replication (the number of processes running)
* Memory
* Previous steps before starting

이 이미지는 주로 위에서 설명된 상황에서 유용할 것입니다: [다중 프로세스를 가지는 컨테이너와 특수한 경우들](#containers-with-multiple-processes-and-special-cases).

* <a href="https://github.com/tiangolo/uvicorn-gunicorn-fastapi-docker" class="external-link" target="_blank">tiangolo/uvicorn-gunicorn-fastapi</a>.

!!! warning "경고"

このイメージは、主に上記で説明した状況で役に立つでしょう： [複数のプロセスと特殊なケースを持つコンテナ（Containers with Multiple Processes and Special Cases）](#containers-with-multiple-processes-and-special-cases)

* <a href="https://github.com/tiangolo/uvicorn-gunicorn-fastapi-docker" class="external-link" target="_blank">tiangolo/uvicorn-gunicorn-fastapi</a>.

!!! warning

        "start_datetime": "2018-12-22T14:00:00+00:00",
        "end_datetime": "2018-12-24T15:00:00+00:00",
        "repeat_at": "15:30:00",
        "process_after": 300,
    }
    expected_response = data.copy()
    expected_response.update(
        {
            "start_process": "2018-12-22T14:05:00+00:00",
            "duration": 176_100,
            "item_id": item_id,
        }
    )

[19515] [INFO] Booting worker with pid: 19515
[19511] [INFO] Started server process [19511]
[19511] [INFO] Waiting for application startup.
[19511] [INFO] Application startup complete.
[19513] [INFO] Started server process [19513]
[19513] [INFO] Waiting for application startup.
[19513] [INFO] Application startup complete.
[19514] [INFO] Started server process [19514]
[19514] [INFO] Waiting for application startup.

<span style="color: green;">INFO</span>:     Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit)
<span style="color: green;">INFO</span>:     Started reloader process [28720]
<span style="color: green;">INFO</span>:     Started server process [28722]
<span style="color: green;">INFO</span>:     Waiting for application startup.
<span style="color: green;">INFO</span>:     Application startup complete.
```

</div>

### Concurrency + Parallelism: Web + Machine Learning

With **FastAPI** you can take the advantage of concurrency that is very common for web development (the same main attraction of NodeJS).