* close the open underlying stream.
   *
   * <p>Note: The input {@code Iterator} will be copied to an {@code ImmutableList} when this method
   * is called. This will fail if the iterator is infinite and may cause problems if the iterator
   * eagerly fetches data for each source when iterated (rather than producing sources that only
   * load data through their streams). Prefer using the {@link #concat(Iterable)} overload if
   * possible.

      Class<?> cls;
      try {
        cls = classInfo.load();
      } catch (NoClassDefFoundError e) {
        // In case there were linking problems, this is probably not a class we care to test anyway.
        logger.log(Level.SEVERE, "Cannot load class " + classInfo + ", skipping...", e);
        continue;
      }
      if (!cls.isInterface()) {

**replicar los contenedores** en las **máquinas disponibles** teniendo en cuenta la cantidad de memoria necesaria por ellos, y la cantidad disponible en las máquinas en el cluster.

Si tu aplicación es **simple**, probablemente esto **no será un problema**, y puede que no necesites especificar límites de memoria estrictos. Pero si estás **usando mucha memoria** (por ejemplo, con modelos de **Machine Learning**), deberías verificar cuánta memoria estás consumiendo y ajustar el **número de contenedores**...

{* ../../docs_src/response_model/tutorial002_py310.py hl[16] *}

Ahora, cada vez que un navegador esté creando un usuario con una contraseña, la API devolverá la misma contraseña en el response.

En este caso, podría no ser un problema, porque es el mismo usuario que envía la contraseña.

Pero si usamos el mismo modelo para otra *path operation*, podríamos estar enviando las contraseñas de nuestros usuarios a cada cliente.

/// danger | Peligro

Por supuesto, hay algunos casos en los que no hay problema en ejecutar los pasos previos múltiples veces, en ese caso, es mucho más fácil de manejar.

/// tip | Consejo

         * However, we don't expose currentFuture to users, so they can't attach listeners. And the
         * Future might not even be a ListenableFuture, just a plain Future. That said, similar
         * problems can exist with methods like FutureTask.done(), not to mention slow calls to
         * Thread.interrupt() (as discussed in InterruptibleTask). At the end of the day, it's

## Changelog since v1.2.5

### Other notable changes

* Fix watch cache filtering ([#28967](https://github.com/kubernetes/kubernetes/pull/28967), [@liggitt](https://github.com/liggitt))
* Fix problems with container restarts and flocker ([#25874](https://github.com/kubernetes/kubernetes/pull/25874), [@simonswine](https://github.com/simonswine))



# v1.2.5

- Fix problem in updating VolumeAttached in node status ([#112304](https://github.com/kubernetes/kubernetes/pull/112304), [@xing-yang](https://github.com/xing-yang)) [SIG Apps]

            fireEvent(ResolutionListener.UPDATE_SCOPE, listeners, nearest, farthestArtifact);

            // previously we cloned the artifact, but it is more efficient to just update the artifactScope
            // if problems are later discovered that the original object needs its original artifactScope value,
            // cloning may
            // again be appropriate
            nearestArtifact.setScope(farthestArtifact.getScope());

		settings = ParseTagSetting(str, ",")
	)

	// optimize match english letters and midline
	// The following code is basically called in for.
	// In order to avoid the performance problems caused by repeated compilation of regular expressions,
	// it only needs to be done once outside, so optimization is done here.
	if idx != -1 && regEnLetterAndMidline.MatchString(str[0:idx]) {
		name = str[0:idx]
	} else {