### Memory per Process

Now, when the program loads things in memory, for example, a machine learning model in a variable, or the contents of a large file in a variable, all that **consumes a bit of the memory (RAM)** of the server.

* Restarts
* Replication (the number of processes running)
* Memory
* Previous steps before starting

## Memory

If you run **a single process per container** you will have a more or less well-defined, stable, and limited amount of memory consumed by each of those containers (more than one if they are replicated).

podAnnotations: {}

# Additional pod labels
podLabels: {}

## Configure resource requests and limits
## ref: http://kubernetes.io/docs/user-guide/compute-resources/
##
resources:
  requests:
    memory: 16Gi

## List of policies to be created after minio install
##
## In addition to default policies [readonly|readwrite|writeonly|consoleAdmin|diagnostics]

   * Stream.of("foo", "quux", "banana", "elephant")
   *     .collect(least(2, comparingInt(String::length)))
   * // returns {"foo", "quux"}
   * }</pre>
   *
   * <p>This {@code Collector} uses O(k) memory and takes expected time O(n) (worst-case O(n log
   * k)), as opposed to e.g. {@code Stream.sorted(comparator).limit(k)}, which currently takes O(n
   * log n) time and O(n) space.
   *

   * 2^n}, its memory usage is only {@code O(n)}. When the power set is constructed, the input set
   * is merely copied. Only as the power set is iterated are the individual subsets created, and
   * these subsets themselves occupy only a small constant amount of memory.
   *
   * @param set the set of elements to construct a power set from

    *   Object metadata has now been deprecated and no longer saved to the
        SavedModel.

*   TF Core:

    *   Added `tf.config.experimental.reset_memory_stats` to reset the tracked
        peak memory returned by `tf.config.experimental.get_memory_info`.

*   `tf.data`:

    *   Added `target_workers` param to `data_service_ops.from_dataset_id` and

```

!!! 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.

"OnRootMismatch" readOnlyRootFilesyst: false # Additational pod annotations podAnnotations: {} # Additional pod labels podLabels: {} ## Configure resource requests and limits ## ref: http://kubernetes.io/docs/user-guide/compute-resources/ ## resources: requests: memory: 16Gi ## List of policies to be created after minio install ## ## In addition to default policies [readonly|readwrite|writeonly|consoleAdmin|diagnostics] ## you can define additional policies with custom supported actions and resources policies: []...

This is the basic idea. But you will probably want to take care of some additional things, like:

* Security - HTTPS
* Running on startup
* Restarts
* Replication (the number of processes running)
* Memory
* Previous steps before starting

    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