* value slightly too high than slightly too low. If the value is not exact, the {@link
   * ImmutableLongArray} that is built will very likely occupy more memory than strictly necessary;
   * to trim memory usage, build using {@code builder.build().trimmed()}.
   */
  public static Builder builder(int initialCapacity) {
    checkArgument(initialCapacity >= 0, "Invalid initialCapacity: %s", initialCapacity);

   * value slightly too high than slightly too low. If the value is not exact, the {@link
   * ImmutableIntArray} that is built will very likely occupy more memory than strictly necessary;
   * to trim memory usage, build using {@code builder.build().trimmed()}.
   */
  public static Builder builder(int initialCapacity) {
    checkArgument(initialCapacity >= 0, "Invalid initialCapacity: %s", initialCapacity);

### Arbeitsspeicher pro Prozess { #memory-per-process }

Wenn das Programm nun Dinge in den Arbeitsspeicher lädt, zum Beispiel ein Modell für maschinelles Lernen in einer Variablen oder den Inhalt einer großen Datei in einer Variablen, verbraucht das alles **einen Teil des Arbeitsspeichers (RAM – Random Access Memory)** des Servers.

  public abstract HashCode hashBytes(byte[] input, int off, int len);

  @Override
  public HashCode hashBytes(ByteBuffer input) {
    return newHasher(input.remaining()).putBytes(input).hash();
  }

  /** In-memory ByteBuffer-based implementation of {@link Hasher}. */
  private final class ByteBufferHasher extends AbstractHasher {
    ByteBuffer buffer;

    ByteBufferHasher(int expectedInputSize) {

   */
  @Override
  List<V> createCollection() {
    return new ArrayList<>(expectedValuesPerKey);
  }

  /**
   * Reduces the memory used by this {@code ArrayListMultimap}, if feasible.
   *
   * @deprecated For a {@link ListMultimap} that automatically trims to size, use {@link

* Docker en Modo Swarm
* Systemd
* Supervisor
* Manejado internamente por un proveedor de nube como parte de sus servicios
* Otros...

## Replicación - Procesos y Memoria { #replication-processes-and-memory }

Con una aplicación FastAPI, usando un programa servidor como el comando `fastapi` que ejecuta Uvicorn, ejecutarlo una vez en **un proceso** puede servir a múltiples clientes concurrentemente.

## Caveat { #caveat }

If you need to perform heavy background computation and you don't necessarily need it to be run by the same process (for example, you don't need to share memory, variables, etc), you might benefit from using other bigger tools like <a href="https://docs.celeryq.dev" class="external-link" target="_blank">Celery</a>.

And then, right after the `yield`, we unload the model. This code will be executed **after** the application **finishes handling requests**, right before the *shutdown*. This could, for example, release resources like memory or a GPU.

/// tip

The `shutdown` would happen when you are **stopping** the application.

Maybe you need to start a new version, or you just got tired of running it. 🤷

///

```

/// tip

The app above is a minimal and simple example to demonstrate how to handle and broadcast messages to several WebSocket connections.

But keep in mind that, as everything is handled in memory, in a single list, it will only work while the process is running, and will only work with a single process.

- Added memory tracking to scheduler performance tests to help detect memory leaks and monitored memory usage patterns while running `scheduler_perf`. ([#132910](https://github.com/kubernetes/kubernetes/pull/132910), [@utam0k](https://github.com/utam0k)) [SIG Scheduling and Testing]