MinIO in distributed mode lets you pool multiple drives (even on different machines) into a single object storage server. As drives are distributed across several nodes, distributed MinIO can withstand multiple node failures and yet ensure full data protection.

## Why distributed MinIO?

  - [Known Issues](#known-issues)
  - [Urgent Upgrade Notes](#urgent-upgrade-notes)
    - [(No, really, you MUST read this before you upgrade)](#no-really-you-must-read-this-before-you-upgrade)
      - [API Machinery](#api-machinery)
      - [Apps](#apps)
      - [Auth](#auth)
      - [AWS](#aws)
      - [Azure](#azure)
      - [CLI](#cli)
      - [Lifecycle](#lifecycle)
      - [Network](#network)
      - [Node](#node)

	app := cli.NewApp()
	app.Name = name
	app.Author = "MinIO, Inc."
	app.Version = ReleaseTag
	app.Usage = "High Performance Object Storage"
	app.Description = `Build high performance data infrastructure for machine learning, analytics and application data workloads with MinIO`
	app.Flags = GlobalFlags
	app.HideHelpCommand = true // Hide `help, h` command, we already have `minio --help`.
	app.Commands = commands

### Memoria por Proceso { #memory-per-process }

Ahora, cuando el programa carga cosas en memoria, por ejemplo, un modelo de Machine Learning en una variable, o el contenido de un archivo grande en una variable, todo eso **consume un poco de la memoria (RAM)** del servidor.

      - [Alpha](#alpha)
      - [CLI Improvements](#cli-improvements)
      - [Misc](#misc)
    - [API Changes](#api-changes)
    - [Other notable changes](#other-notable-changes-5)
      - [API Machinery](#api-machinery)
      - [Apps](#apps)
      - [Auth](#auth)
      - [CLI](#cli)
      - [Cloud Provider](#cloud-provider)
      - [Cluster Lifecycle](#cluster-lifecycle-1)
      - [Instrumentation](#instrumentation)

                                    + now
                                    + ", lastUpdated = " + lastUpdated + "). Please verify that the clocks of all"
                                    + " deploying machines are reasonably synchronized.");
                    versioning.setLastUpdated(now);
                    changed = true;
                }
            }
        }

        if (changed) {

* <a href="https://unit.nginx.org/howto/fastapi/" class="external-link" target="_blank">NGINX Unit</a>: NGINX Unit es un runtime para aplicaciones web ligero y versátil.

## Máquina Servidor y Programa Servidor { #server-machine-and-server-program }

Hay un pequeño detalle sobre los nombres que hay que tener en cuenta. 💡

```hl_lines="4"
INFO:     Uvicorn running on http://127.0.0.1:8000 (Press CTRL+C to quit)
```

Cette ligne montre l'URL par laquelle l'app est actuellement accessible, sur votre machine locale.

### Allez voir le résultat

Ouvrez votre navigateur à l'adresse <a href="http://127.0.0.1:8000" class="external-link" target="_blank">http://127.0.0.1:8000</a>.

Vous obtiendrez cette réponse JSON :

{* ../../docs_src/path_params/tutorial005_py39.py hl[1,6:9] *}

/// tip

If you are wondering, "AlexNet", "ResNet", and "LeNet" are just names of Machine Learning <abbr title="Technically, Deep Learning model architectures">models</abbr>.

///

### Declare a *path parameter* { #declare-a-path-parameter }

/// tip | Consejo

Si te estás preguntando, "AlexNet", "ResNet" y "LeNet" son solo nombres de <abbr title="Técnicamente, arquitecturas de modelos de Deep Learning">modelos</abbr> de Machine Learning.

///

### Declarar un *path parameter* { #declare-a-path-parameter }

Luego crea un *path parameter* con una anotación de tipo usando la clase enum que creaste (`ModelName`):