* Docker Compose
* Docker в режиме Swarm (Swarm Mode)
* Systemd
* Supervisor
* Обработка внутри облачного провайдера как часть его услуг
* Прочие...

## Репликация — процессы и память { #replication-processes-and-memory }

В приложении FastAPI, используя серверную программу (например, команду `fastapi`, которая запускает Uvicorn), запуск в **одном процессе** уже позволяет обслуживать нескольких клиентов одновременно.

     * Get the name service client for NetBIOS name resolution
     *
     * @return the name server client
     */
    NameServiceClient getNameServiceClient();

    /**
     * Get the buffer cache for efficient memory management
     *
     * @return the buffer cache
     */
    BufferCache getBufferCache();

    /**
     * Get the transport pool for managing SMB connections
     *
     * @return the transport pool

import org.junit.jupiter.api.Test;
import org.junit.jupiter.api.Timeout;
import org.mockito.Mockito;

import jcifs.CIFSContext;
import jcifs.Configuration;
import jcifs.Credentials;

/**
 * Simple memory management tests to validate basic resource cleanup functionality
 */
public class SimpleMemoryManagementTest {

    private CIFSContext mockContext;
    private SmbTransportImpl mockTransport;

  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) {

- A maximum of 100M inside a single zip is allowed. However, a reasonable limit of 100,000 files inside a single ZIP archive is recommended for best performance and memory usage trade-off.

## Content-Type

 * offering expected O(n + k log k) performance (worst case O(n log k)) for n calls to {@link
 * #offer} and a call to {@link #topK}, with O(k) memory. In comparison, quickselect has the same
 * asymptotics but requires O(n) memory, and a {@code PriorityQueue} implementation takes O(n log
 * k). In benchmarks, this implementation performs at least as well as either implementation, and

### 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.

   * 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

            final MessageDigest md4 = Crypto.getMD4();
            md4.update(Strings.getUNIBytes(tempStr));
            return md4.digest();
        } finally {
            // Clear the temporary string from memory (best effort)
            if (tempStr != null) {
                tempStr.intern();
            }
        }
    }

    /**
     * Generates the NTOWFv1 hash for the given password.
     *

      description: If compiling from source
  - type: input
    id: Cuda
    attributes:
      label: CUDA/cuDNN version
  - type: input
    id: Gpu
    attributes:
      label: GPU model and memory
      description: If compiling from source
  - type: textarea
    id: what-happened
    attributes:
      label: Current behavior?
      description: Also tell us, what did you expect to happen?