Cela peut être très utile pour configurer des **ressources** dont vous avez besoin pour l'ensemble de l'application, qui sont **partagées** entre les requêtes, et/ou que vous devez **nettoyer** ensuite. Par exemple, un pool de connexions à une base de données, ou le chargement d'un modèle d'apprentissage automatique partagé.

## Cas d'utilisation { #use-case }

Esto puede ser muy útil para configurar **recursos** que necesitas usar para toda la app, y que son **compartidos** entre requests, y/o que necesitas **limpiar** después. Por ejemplo, un pool de conexiones a una base de datos, o cargando un modelo de machine learning compartido.

## Caso de Uso { #use-case }

Empecemos con un ejemplo de **caso de uso** y luego veamos cómo resolverlo con esto.

- Fix a bug that Pods could stuck in the unschedulable pod pool 
  if they're rejected by PreEnqueue plugins that could change its result by a change in resources apart from Pods.
  
  DRA plugin is the only plugin that meets the criteria of the bug in in-tree, 

				return err
			}
			if err := w.mw.Flush(); err != nil {
				return err
			}
			return s2w.Close()
		}
		return nil
	}
}

var s2DecPool = bpool.Pool[*s2.Reader]{New: func() *s2.Reader {
	// Default alloc block for network transfer.
	return s2.NewReader(nil, s2.ReaderAllocBlock(16<<10))
}}

// metacacheReader allows reading a cache stream.

## Changelog since v1.16.13

## Changes by Kind

### Bug or Regression

- Do not add nodes labeled with kubernetes.azure.com/managed=false to backend pool of load balancer. ([#93034](https://github.com/kubernetes/kubernetes/pull/93034), [@matthias50](https://github.com/matthias50)) [SIG Cloud Provider]

* Update cadvisor to v0.23.9 to fix a problem where attempting to gather container filesystem usage statistics could result in corrupted devicemapper thin pool storage for Docker. ([#30307](https://github.com/kubernetes/kubernetes/pull/30307), [@sjenning](https://github.com/sjenning))



# v1.3.5

    *   Added support for `tflite_convert` command line tool in 2.0.
    *   Post-training quantization tool supports quantizing weights shared by
        multiple operations. The models made with versions of this tool will use
        INT8 types for weights and will only be executable interpreters from
        this version onwards.
    *   Post-training quantization tool supports fp16 weights and GPU delegate

	}
	if err != nil {
		return res, toStorageErr(err)
	}

	defer storageRenameDataRPC.PutResponse(resp)
	return *resp, nil
}

// where we keep old *Readers
var readMsgpReaderPool = bpool.Pool[*msgp.Reader]{New: func() *msgp.Reader { return &msgp.Reader{} }}

// mspNewReader returns a *Reader that reads from the provided reader.
// The reader will be buffered.
// Return with readMsgpReaderPoolPut when done.

- The scheduling queue didn't notice any extenders' failures, it could miss some cluster events,
  and it could end up Pods rejected by Extenders stuck in unschedulable pod pool in 5min in the worst-case scenario.

# Changelog since v1.18.6

## Changes by Kind

### Bug or Regression

- Do not add nodes labeled with kubernetes.azure.com/managed=false to backend pool of load balancer. ([#93034](https://github.com/kubernetes/kubernetes/pull/93034), [@matthias50](https://github.com/matthias50)) [SIG Cloud Provider]