final byte[] buf = buffer.array();
            int len;
            int amount = 0;
            while ((len = ChannelUtil.read(channel, buffer, amount)) != -1) {
                out.write(buf, 0, len);
                buffer.clear();
                amount += len;
            }
            out.flush();
            return amount;
        } catch (final IOException e) {
            throw new IORuntimeException(e);

            path = ".";
        } else {
            out.println("<b><big>" + path + "</big></b><br>");
            path = "../";
        }
        out.println(dirCount + fileCount + " objects (" + dirCount + " directories, " + fileCount + " files)<br>");
        out.println("<b><a class=\"plain\" href=\".\">normal</a> | <a class=\"plain\" href=\"?fmt=detail\">detailed</a></b>");

            path = ".";
        } else {
            out.println("<b><big>" + path + "</big></b><br>");
            path = "../";
        }
        out.println(dirCount + fileCount + " objects (" + dirCount + " directories, " + fileCount + " files)<br>");
        out.println("<b><a class=\"plain\" href=\".\">normal</a> | <a class=\"plain\" href=\"?fmt=detail\">detailed</a></b>");

  }

  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()
  }

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 { #server-memory }

        }

        try {
            // In real implementation, this would perform RDMA read into the buffer
            // For skeleton implementation, simulate reading the requested amount
            int bytesToRead = Math.min(length, buffer.remaining());

            // Simulate RDMA read operation

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...

    public void test_evaluate_withSpecialCharacters() {
        String template = "Price: $${price} (with ${discount}% off)";
        Map<String, Object> paramMap = new HashMap<>();
        paramMap.put("price", "100");
        paramMap.put("discount", "20");

        Object result = scriptEngine.evaluate(template, paramMap);
        assertEquals("Price: $100 (with 20% off)", result);
    }

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

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

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

  }

  /**
   * Sends the given method call to this thread.
   *
   * @throws TimeoutException if this thread does not accept the request within a reasonable amount
   *     of time
   */
  private void sendRequest(String methodName, Object... arguments) throws Exception {
    if (!requestQueue.offer(new Request(methodName, arguments), TIMEOUT_MILLIS, MILLISECONDS)) {