}

  private fun updateMaxConcurrentStreams(
    connection: Http2Connection,
    amount: Int,
  ) {
    val settings = Settings()
    settings[Settings.MAX_CONCURRENT_STREAMS] = amount
    connection.readerRunnable.applyAndAckSettings(true, settings)
    assertThat(connection.peerSettings[Settings.MAX_CONCURRENT_STREAMS]).isEqualTo(amount)
    taskFaker.runTasks()
  }

It would take the same amount of time to finish with or without turns (concurrency) and you would have done the same amount of work.

        network stack is offline.

  [[3]] "Remote" repositories referenced using the file:// protocol may
        be available. However, if that file:// url references a
        file-share, as in the case of an NFS or SMB mount, that will
        be unavailable.

  So, offline mode has several implications, some of which may not be
  altogether obvious:

  * Localhost may be unavailable. Therefore, even locally installed

     * the web socket! It's possible that we're writing faster than the peer can read.
     */
    private const val MAX_QUEUE_SIZE = 16L * 1024 * 1024 // 16 MiB.

    /**
     * The maximum amount of time after the client calls [close] to wait for a graceful shutdown. If
     * the server doesn't respond the web socket will be canceled.
     */
    const val CANCEL_AFTER_CLOSE_MILLIS = 60L * 1000

    /**

      return state.policy.backoffDelayMillis.jitterBy(state.policy.backoffJitterMillis) * 1_000_000
    }
  }

  private fun Long.jitterBy(amount: Int): Long {
    return this + ThreadLocalRandom.current().nextInt(amount * -1, amount)
  }

  class AddressState(
    val address: Address,
    val queue: TaskQueue,
    var policy: ConnectionPool.AddressPolicy,
  ) {
    /**

And multiple processes normally **don't share any memory**. This means that each running process has its own things, variables, and memory. And if you are consuming a large amount of memory in your code, **each process** will consume an equivalent amount of memory.

### Server Memory

  // +optional
  optional bool attachRequired = 1;

  // podInfoOnMount indicates this CSI volume driver requires additional pod information (like podName, podUID, etc.)
  // during mount operations, if set to true.
  // If set to false, pod information will not be passed on mount.
  // Default is false.
  //
  // The CSI driver specifies podInfoOnMount as part of driver deployment.

  // +optional
  optional bool attachRequired = 1;

  // podInfoOnMount indicates this CSI volume driver requires additional pod information (like podName, podUID, etc.)
  // during mount operations, if set to true.
  // If set to false, pod information will not be passed on mount.
  // Default is false.
  //
  // The CSI driver specifies podInfoOnMount as part of driver deployment.

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).

And then you can set those same memory limits and requirements in your configurations for your container management system (for example in **Kubernetes**). That way it will be able to **replicate the containers** in the **available machines** taking into account the amount of memory needed by them, and the amount available in the machines...

 * from this file as necessary.
 *
 * This class also keeps a small buffer of bytes recently read from upstream. This is intended to
 * save a small amount of file I/O and data copying.
 */
class Relay private constructor(
  /**
   * Read/write persistence of the upstream source and its metadata. Its layout is as follows:
   *