type NotificationGroup struct {
	workers    *workers.Workers
	errs       []NotificationPeerErr
	retryCount int
}

// WithNPeers returns a new NotificationGroup with length of errs slice upto nerrs,
// upon Wait() errors are returned collected from all tasks.
func WithNPeers(nerrs int) *NotificationGroup {
	if nerrs <= 0 {
		nerrs = 1
	}
	wk, _ := workers.New(nerrs)

COPY ./app /code/app

# (1)!
CMD ["fastapi", "run", "app/main.py", "--port", "80", "--workers", "4"]
```

1. Тут ми використовуємо опцію командного рядка `--workers`, щоб встановити кількість працівників 4.

Ось кілька прикладів, коли це може мати сенс:

#### Простий застосунок { #a-simple-app }

하지만 많은 경우, 여러 워커 프로세스를 동시에 실행하고 싶을 것입니다.

### 여러 프로세스 - 워커 { #multiple-processes-workers }

단일 프로세스가 처리할 수 있는 것보다 클라이언트가 더 많고(예: 가상 머신이 그리 크지 않을 때), 서버 CPU에 **여러 코어**가 있다면, 같은 애플리케이션을 실행하는 **여러 프로세스**를 동시에 띄우고 요청을 분산시킬 수 있습니다.

같은 API 프로그램을 **여러 프로세스**로 실행할 때, 이 프로세스들을 보통 **workers**라고 부릅니다.

### 워커 프로세스와 포트 { #worker-processes-and-ports }

	if err != nil {
		decomLogIf(ctx, fmt.Errorf("invalid workers value err: %v, defaulting to %d", err, len(pool.sets)))
		workerSize = len(pool.sets)
	}

	// Each decom worker needs one List() goroutine/worker
	// add that many extra workers.
	workerSize += len(pool.sets)

	wk, err := workers.New(workerSize)
	if err != nil {
		return err
	}

	var vc *versioning.Versioning

Коли ви запускаєте **кілька процесів** того самого програмного забезпечення API, їх зазвичай називають **працівниками** (workers).

### Процеси-працівники і порти { #worker-processes-and-ports }

Пам'ятаєте з документації [Про HTTPS](https.md), що на сервері лише один процес може слухати певну комбінацію порту та IP-адреси?

Это досі так.

        def projectDir = 'C:\\some\\agent\\workspace'

        expect:

	transitionWorkers = "transition_workers"
	expirationWorkers = "expiration_workers"
	// EnvILMTransitionWorkers env variable to configure number of transition workers
	EnvILMTransitionWorkers = "MINIO_ILM_TRANSITION_WORKERS"
	// EnvILMExpirationWorkers env variable to configure number of expiration workers
	EnvILMExpirationWorkers = "MINIO_ILM_EXPIRATION_WORKERS"
)

var (
	defaultHelpPostfix = func(key string) string {

	replicationRecentBacklogCount      = "recent_backlog_count"
)

var (
	replicationAverageActiveWorkersMD = NewGaugeMD(replicationAverageActiveWorkers,
		"Average number of active replication workers")
	replicationAverageQueuedBytesMD = NewGaugeMD(replicationAverageQueuedBytes,
		"Average number of bytes queued for replication since server start")
	replicationAverageQueuedCountMD = NewGaugeMD(replicationAverageQueuedCount,

// once (i.e., on the main function side) in running distributed functions.
// This test creates a cluster with two workers, create a variable on the
// second worker, and run a distributed function (VariableAddFunction) whose ops
// span the local and remote workers. If the graph optimization pass is executed
// on both the main function side and the component function side, an error will

 * while a worker action that executes in a worker must declare that it executes in
 * a worker.
 *
 * However, a shared library used by both daemon and worker actions does not necessarily
 * care which runtimes it must execute in. The target runtimes it must support is a function
 * of the daemon and worker project that depends on it. Since both a daemon and worker