return
	}

	if w != nil {
		// Increment the prometheus http request response histogram with API, Bucket
		bucketHTTPRequestsDuration.With(prometheus.Labels{
			"api":    api,
			"bucket": bucket,
		}).Observe(w.TTFB().Seconds())
	}

	bh.Lock()
	defer bh.Unlock()

	hstats, ok := bh.httpStats[bucket]
	if !ok {
		hstats = bucketHTTPAPIStats{
			currentS3Requests: &HTTPAPIStats{},

        }
        return activeProxy;
    }

    public Server getServer(String serverId) {
        Server match = null;
        java.util.List<Server> servers = getServers();
        if (servers != null && serverId != null) {
            for (Server server : servers) {
                if (serverId.equals(server.getId())) {
                    match = server;
                    break;
                }
            }

* `@app.get()`
* `@app.post()`
* `@app.put()`
* `@app.delete()`
* etc.

{* ../../docs_src/response_model/tutorial001_py310.py hl[17,22,24:27] *}

/// note | Nota

Observe que `response_model` é um parâmetro do método "decorator" (`get`, `post`, etc). Não da sua *função de operação de rota*, como todos os parâmetros e corpo.

///

   * context class loader will find resources from the class path. In environments where different
   * threads can have different class loaders, for example app servers, the context class loader
   * will typically have been set to an appropriate loader for the current thread.
   *
   * <p>In the unusual case where the context class loader is null, the class loader that loaded

             to quit<b>)</b>
```

</div>

В большинстве случаев этого достаточно. 😎

Этой командой, например, можно запускать приложение **FastAPI** в контейнере, на сервере и т.д.

## ASGI‑серверы { #asgi-servers }

Давайте немного углубимся в детали.

### Beim Hochfahren automatisch ausführen { #run-automatically-on-startup }

Im Allgemeinen möchten Sie wahrscheinlich, dass das Serverprogramm (z. B. Uvicorn) beim Hochfahren des Servers automatisch gestartet wird und kein **menschliches Eingreifen** erforderlich ist, sodass immer ein Prozess mit Ihrer API ausgeführt wird (z. B. Uvicorn, welches Ihre FastAPI-Anwendung ausführt).

    * If you are comparing Uvicorn, compare it against Daphne, Hypercorn, uWSGI, etc. Application servers.
* **Starlette**:
    * Will have the next best performance, after Uvicorn. In fact, Starlette uses Uvicorn to run. So, it probably can only get "slower" than Uvicorn by having to execute more code.

		Buckets: []float64{0.01, 0.1, 1, 2, 5, 10, 60, 5 * 60, 15 * 60, 30 * 60},
	}, []string{"tier"}),
}

func (t *tierMetrics) Observe(tier string, dur time.Duration) {
	t.histogram.With(prometheus.Labels{"tier": tier}).Observe(dur.Seconds())
}

func (t *tierMetrics) logSuccess(tier string) {
	t.Lock()
	defer t.Unlock()

	stat := t.requestsCount[tier]
	stat.success++

![bucket-lookup](https://github.com/minio/minio/blob/master/docs/federation/lookup/bucket-lookup.png?raw=true)

### Environment variables

#### MINIO_ETCD_ENDPOINTS

This is comma separated list of etcd servers that you want to use as the MinIO federation back-end. This should
be same across the federated deployment, i.e. all the MinIO instances within a federated deployment should use same
etcd back-end.

#### MINIO_DOMAIN

      )
    peer.sendFrame().headers(true, 2, expectedResponseHeaders)
    peer.sendFrame().data(true, 3, data(0), 0)
    peer.play()
    val observer = RecordingPushObserver()

    // Play it back.
    val connection = connect(peer, observer, Http2Connection.Listener.REFUSE_INCOMING_STREAMS)
    val client = connection.newStream(headerEntries("b", "banana"), false)