## Zusammenfassung

Sie können **Gunicorn** (oder auch Uvicorn) als Prozessmanager mit Uvicorn-Workern verwenden, um **Multikern-CPUs** zu nutzen und **mehrere Prozesse parallel** auszuführen.

Sie können diese Tools und Ideen nutzen, wenn Sie **Ihr eigenes Deployment-System** einrichten und sich dabei selbst um die anderen Deployment-Konzepte kümmern.

	aoMetricsGroup         = grid.NewArrayOf[*MetricV2](func() *MetricV2 { return &MetricV2{} })
	madminBgHealState      = grid.NewJSONPool[madmin.BgHealState]()
	madminCPUs             = grid.NewJSONPool[madmin.CPUs]()
	madminMemInfo          = grid.NewJSONPool[madmin.MemInfo]()
	madminNetInfo          = grid.NewJSONPool[madmin.NetInfo]()
	madminOSInfo           = grid.NewJSONPool[madmin.OSInfo]()

- [PRF](#prf): HMAC-SHA-256
- [AEAD](#aead): AES-256-GCM if the CPU supports AES-NI, ChaCha20-Poly1305 otherwise. More specifically AES-256-GCM is only selected for X86-64 CPUs with AES-NI extension.

Further any secret key (apart from the KMS-generated ones) is 256 bits long. The KMS-generated keys may be 256 bits but this depends on the KMS capabilities and configuration.

## Recap

You can use **Gunicorn** (or also Uvicorn) as a process manager with Uvicorn workers to take advantage of **multi-core CPUs**, to run **multiple processes in parallel**.

You could use these tools and ideas if you are setting up **your own deployment system** while taking care of the other deployment concepts yourself.

# gRPC on MacOS requires this #define
build:macos --copt=-DGRPC_BAZEL_BUILD

# Avoid hitting command line argument limit
build:macos --features=archive_param_file

# Settings for MacOS on ARM CPUs.
build:macos_arm64 --cpu=darwin_arm64
build:macos_arm64 --macos_minimum_os=11.0

# iOS configs for each architecture and the fat binary builds.
build:ios --apple_platform_type=ios

in the pictures of him), while the rest waited in silence.  At
last the Dodo said, `EVERYBODY has won, and all must have
prizes.'

  `But who is to give the prizes?' quite a chorus of voices
asked.

  `Why, SHE, of course,' said the Dodo, pointing to Alice with
one finger; and the whole party at once crowded round her,
calling out in a confused way, `Prizes! Prizes!'

void TFE_SetLogicalCpuDevices(TFE_Context* ctx, int num_cpus,
                              const char* prefix, TF_Status* status) {
  std::vector<std::unique_ptr<tensorflow::Device>> devices;

  if (prefix == nullptr || strlen(prefix) == 0)
    prefix = "/job:localhost/replica:0/task:0";

  tensorflow::SessionOptions sess_options;
  (*sess_options.config.mutable_device_count())["CPU"] = num_cpus;
  status->status =

			peersLogOnceIf(logger.SetReqInfo(ctx, reqInfo), nErr.Err, nErr.Host.String())
		}
	}
}

// GetCPUs - Get all CPU information.
func (sys *NotificationSys) GetCPUs(ctx context.Context) []madmin.CPUs {
	reply := make([]madmin.CPUs, len(sys.peerClients))

	g := errgroup.WithNErrs(len(sys.peerClients))
	for index, client := range sys.peerClients {
		if client == nil {
			continue
		}
		index := index

## Resource Utilization

Your server(s) is (are) a **resource**, you can consume or **utilize**, with your programs, the computation time on the CPUs, and the RAM memory available.

How much of the system resources do you want to be consuming/utilizing? It might be easy to think "not much", but in reality, you will probably want to consume **as much as possible without crashing**.

## Ressourcennutzung

Ihr(e) Server ist (sind) eine **Ressource**, welche Sie mit Ihren Programmen, der Rechenzeit auf den CPUs und dem verfügbaren RAM-Speicher verbrauchen oder **nutzen** können.