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.

Und mehrere Prozesse teilen sich normalerweise keinen Speicher. Das bedeutet, dass jeder laufende Prozess seine eigenen Dinge, eigenen Variablen und eigenen Speicher hat. Und wenn Sie in Ihrem Code viel Speicher verbrauchen,...

	ctx := logger.SetReqInfo(GlobalContext, reqInfo)
	peersLogOnceIf(ctx, err, "add-node-err-"+addr)
	nodeInfo.SetAddr(addr)
	nodeInfo.SetError(err.Error())
}

// GetSysErrors - Memory information
func (sys *NotificationSys) GetSysErrors(ctx context.Context) []madmin.SysErrors {
	reply := make([]madmin.SysErrors, len(sys.peerClients))

	g := errgroup.WithNErrs(len(sys.peerClients))

    assertThat((long) arraysDim1 * arraysDim2).isNotEqualTo((long) (arraysDim1 * arraysDim2));

    boolean[][] arrays = new boolean[arraysDim1][];
    // it's shared to avoid using too much memory in tests
    boolean[] sharedArray = new boolean[arraysDim2];
    Arrays.fill(arrays, sharedArray);

    try {
      Booleans.concat(arrays);
      fail();
    } catch (IllegalArgumentException expected) {

      //    internal char array (hard to avoid using StringBuilder)
      // 2. we avoid extra copies into temporary buffers altogether
      // The downside is that this will cause us to store the file bytes in memory twice for a short
      // amount of time.
      return new String(ByteSource.this.read(), charset);
    }

    @Override
    public String toString() {

   * memory, so it is only likely to be worthwhile if the precomputed matcher is queried very often.
   *
   * <p>This method has no effect (returns {@code this}) when called in GWT: it's unclear whether a
   * precomputed matcher is faster, but it certainly would consume more memory (which doesn't seem
   * like a worthwhile tradeoff in a browser).
   */

    return cycle(Lists.newArrayList(elements));
  }

  /**
   * Returns an Iterator that walks the specified array, nulling out elements behind it. This can
   * avoid memory leaks when an element is no longer necessary.
   *
   * <p>This method accepts an array with element type {@code @Nullable T}, but callers must pass an

    try {
      editor?.abort()
    } catch (_: IOException) {
    }
  }

  /**
   * Initialize the cache. This will include reading the journal files from the storage and building
   * up the necessary in-memory cache information.
   *
   * The initialization time may vary depending on the journal file size and the current actual
   * cache size. The application needs to be aware of calling this function during the

* To reduce memory usage to reasonable levels in smaller clusters, kube-apiserver now sets the deserialization cache size based on the target memory usage. ([#34000](https://github.com/kubernetes/kubernetes/pull/34000), [@wojtek-t](https://github.com/wojtek-t))

          "instant": false,
          "interval": "",
          "legendFormat": "{{server}}",
          "range": true,
          "refId": "A"
        }
      ],
      "title": "Memory Usage ",
      "type": "bargauge"
    },
    {
      "datasource": {
        "type": "prometheus",
        "uid": "${DS_PROMETHEUS}"
      },
      "fieldConfig": {
        "defaults": {

        EMPTY_SET_FIELD_SETTER =
            Serialization.getFieldSetter(ImmutableSetMultimap.class, "emptySet");
  }

  @GwtIncompatible
  @J2ktIncompatible
  // Serialization type safety is at the caller's mercy.
  @SuppressWarnings("unchecked")
  private void readObject(ObjectInputStream stream) throws IOException, ClassNotFoundException {
    stream.defaultReadObject();