values = {
        "apple_platform_type": "macos",
        "cpu": "darwin",
    },
    visibility = ["//visibility:public"],
)

config_setting(
    name = "macos_arm64_with_framework_shared_object",
    define_values = {
        "framework_shared_object": "true",
    },
    values = {
        "apple_platform_type": "macos",
        "cpu": "darwin_arm64",
    },
    visibility = ["//visibility:public"],

Безусловно, на этом же сервере будут работать и **другие процессы**, которые не относятся к вашему приложению.

Интересная деталь заключается в том, что процент **использования центрального процессора (CPU)** каждым процессом может сильно меняться с течением времени, но объём занимаемой **оперативной памяти (RAM)** остаётся относительно **стабильным**.

	switch madmin.ProfilerType(profilerType) {
	case madmin.ProfilerCPU:
		dirPath, err := os.MkdirTemp("", "profile")
		if err != nil {
			return nil, err
		}
		fn := filepath.Join(dirPath, "cpu.out")
		f, err := Create(fn)
		if err != nil {
			return nil, err
		}
		err = pprof.StartCPUProfile(f)
		if err != nil {
			return nil, err
		}
		prof.stopFn = func() ([]byte, error) {

- Added a new option `strict-cpu-reservation` for CPU Manager static policy. When this option is enabled, CPU cores in `reservedSystemCPUs` will be strictly used for system daemons and interrupt processing no longer available for any workload. ([#130290](https://github.com/kubernetes/kubernetes/pull/130290), [@psasnal...

        final long freeMemory = Runtime.getRuntime().freeMemory();
        final String msg = String.format(
                "%d words from %d %s: {\"time\":{\"parse\":%d,\"index\":%d},\"cpu\":%f,\"mem\":{\"heap\":\"%dmb\",\"used\":\"%dmb\"}}",
                items.length, size, type, parseTime, indexTime, cpuLoad, maxMemory / (1024 * 1024),
                (maxMemory - freeMemory) / (1024 * 1024));

  cleanup_makefile()
  setup_python(environ_cp)

  if is_windows():
    environ_cp['TF_NEED_OPENCL'] = '0'
    environ_cp['TF_CUDA_CLANG'] = '0'
    # TODO(ibiryukov): Investigate using clang as a cpu or cuda compiler on
    # Windows.
    environ_cp['TF_DOWNLOAD_CLANG'] = '0'
    environ_cp['TF_NEED_MPI'] = '0'

  if is_ppc64le():
    # Enable MMA Dynamic Dispatch support if 'gcc' and if linker >= 2.35

  //   have observed 12 micros on 64-bit linux systems to wake up a parked thread). So if the
  //   timeout is small we shouldn't park(). This needs to be traded off with the cpu overhead of
  //   spinning, so we use SPIN_THRESHOLD_NANOS which is what AbstractQueuedSynchronizer uses for
  //   similar purposes.
  // * We want to behave reasonably for timeouts of 0

- A new kubelet command line option, `--reserved-cpus`, is introduced to explicitly define the CPU list that will be reserved for system. For example, if `--reserved-cpus=0,1,2,3` is specified, then cpu 0,1,2,3 will be reserved for the system.  On a system with 24 CPUs, the user may specify `isolcpus=4-23` for the kernel option and use CPU 4-23 for the user containers. ([#83592](https://github.com/kubernetes/kubernetes/pull/83592), [@jianzzha](https://github.com/jianzzha))...

  //   have observed 12 micros on 64-bit linux systems to wake up a parked thread). So if the
  //   timeout is small we shouldn't park(). This needs to be traded off with the cpu overhead of
  //   spinning, so we use SPIN_THRESHOLD_NANOS which is what AbstractQueuedSynchronizer uses for
  //   similar purposes.
  // * We want to behave reasonably for timeouts of 0

- The CPU Manager will now validate the state of the node,  enabling Kubernetes to maintain the CPU topology even if resources change. ([#66718](https://github.com/kubernetes/kubernetes/pull/66718), [@ipuustin](https://github.com/ipuustin))