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

     */
    @Override
    public ResponseData doGet(final String uri) {
        return processRequest(uri, true);
    }

    /**
     * Processes an FTP request to retrieve data from the specified URI.
     * This method handles the complete FTP request lifecycle including timeout management,
     * connection setup, and data retrieval.
     *

    override fun flush() {
    }

    override fun timeout(): Timeout = Timeout.NONE

    @Throws(IOException::class)
    override fun close() {
    }
  }

  /** Processes HTTP requests layered over HTTP/2. */
  private inner class Http2SocketHandler(
    private val connectionIndex: Int,
    private val socket: MockWebServerSocket,
    private val protocol: Protocol,

/// check | **FastAPI** le recommande comme

Le serveur web principal pour exécuter les applications **FastAPI**.

Vous pouvez le combiner avec Gunicorn, pour avoir un serveur multi-processus asynchrone.

Pour plus de détails, consultez la section [Déploiement](deployment/index.md){.internal-link target=_blank}.

///

## Benchmarks et vitesse

As noted already, programmers are strongly encouraged to use appropriate synchronization
to avoid data races.
In the absence of data races, Go programs behave as if all the goroutines
were multiplexed onto a single processor.
This property is sometimes referred to as DRF-SC: data-race-free programs
execute in a sequentially consistent manner.
</p>

<p>
While programmers should write Go programs without data races,

Con **FastAPI** puedes aprovechar la concurrencia que es muy común para el desarrollo web (la misma atracción principal de NodeJS).

Pero también puedes explotar los beneficios del paralelismo y la multiprocesamiento (tener múltiples procesos ejecutándose en paralelo) para cargas de trabajo **CPU bound** como las de los sistemas de Machine Learning.

labels.crawlingThreadCount=Numero di scansioni simultanee
labels.boost=Valore di boost
labels.crawlingConfigName=Nome
labels.crawlingConfigPath=Percorso da scansionare
labels.processType=Tipo di processo
labels.parameters=Parametri
labels.designFile=File da caricare
labels.bulkFile=File di massa
labels.appendQueryParameter=Aggiungi parametro di ricerca
labels.configId=ID configurazione

labels.crawlingThreadCount=Nombre d'explorations simultanées
labels.boost=Boost
labels.crawlingConfigName=Nom
labels.crawlingConfigPath=Chemin à explorer
labels.processType=Type de processus
labels.parameters=Paramètres
labels.designFile=Fichier à téléverser
labels.bulkFile=Fichier en vrac
labels.appendQueryParameter=Ajouter des paramètres de recherche
labels.configId=ID de configuration

		maxLWorkers:     maxLWorkers,
	}

	pool.ResizeLrgWorkers(maxLWorkers, 0)
	pool.ResizeWorkers(workers, 0)
	pool.ResizeFailedWorkers(failedWorkers)
	go pool.resyncer.PersistToDisk(ctx, o)
	go pool.processMRF()
	go pool.persistMRF()
	return pool
}

// AddMRFWorker adds a pending/failed replication worker to handle requests that could not be queued
// to the other workers

for COS images on GCE has changed to `/home/kubernetes/flexvolume`, rather than `/etc/srv/kubernetes/kubelet-plugins/volume/exec`. Existing Flexvolume installations in clusters using COS images must be moved to the new directory, and installation processes must be updated with the new path. ([#58171](https://github.com/kubernetes/kubernetes/pull/58171), [@verult](https://github.com/verult))

* Default values differ between the Kubelet's componentconfig (config file) API and the Kubelet's...