for purposes such as debugging, similar to how `kubectl exec` runs a process in an existing container. Also like `kubectl exec`, no resources are reserved for ephemeral containers and they are not restarted when they exit. Note that container namespace targeting is not yet implemented, so [process namespace sharing](https://kubernetes.io/docs/tasks/configure-pod-container/share-process-namespace/) must be enabled to view process from other containers in the pod. ([#59484](https://github.com/kuber...

	}
	word, cond = p.lex.Text(), ""
	operands = scratch[:0]
	// Zero or more comma-separated operands, one per loop.
	nesting := 0
	colon := -1
	for tok != '\n' && tok != ';' {
		// Process one operand.
		var items []lex.Token
		if cap(operands) > len(operands) {
			// Reuse scratch items slice.
			items = operands[:cap(operands)][len(operands)][:0]
		} else {
			items = make([]lex.Token, 0, 3)

labels.crawlingThreadCount=Número de rastreamentos simultâneos
labels.boost=Valor de impulso
labels.crawlingConfigName=Nome
labels.crawlingConfigPath=Caminho a ser rastreado
labels.processType=Tipo de processo
labels.parameters=Parâmetros
labels.designFile=Arquivo para upload
labels.bulkFile=Arquivo em massa
labels.appendQueryParameter=Adicionar parâmetro de pesquisa
labels.configId=ID da configuração

### 每個容器一個行程 { #one-process-per-container }

在這種情境中，你大概會希望「每個容器只有一個（Uvicorn）行程」，因為你已在叢集層級處理了複本。

所以這種情況下，你「不會」想在容器中使用多個 workers（例如用 `--workers` 命令列選項）。你會想每個容器只執行「一個 Uvicorn 行程」（但可能有多個容器）。

在容器內再放一個行程管理器（如同多 workers 的情況）只會增加「不必要的複雜度」，而你很可能已用叢集系統處理好了。

### 多行程容器與特殊情境 { #containers-with-multiple-processes-and-special-cases }

當然，有些「特殊情況」你可能會想在「一個容器內」執行數個「Uvicorn worker 行程」。

- Added a redundant process to remove tracking finalizers from Pods that belong to Jobs. The process kicks in after the control plane marks a Job as finished. ([#119944](https://github.com/kubernetes/kubernetes/pull/119944), [@Sharpz7](https://github.com/Sharpz7))

labels.crawlingThreadCount=Numero di scansioni simultanee
labels.boost=Valore di boost
labels.crawlingConfigName=Nome
labels.crawlingConfigPath=Percorso da scansionare
labels.processType=Tipo di processo
labels.parameters=Parametri
labels.designFile=File da caricare
labels.bulkFile=File di massa
labels.appendQueryParameter=Aggiungi parametro di ricerca
labels.configId=ID configurazione

		}, index)
	}

	for index, err := range g.Wait() {
		if err != nil {
			sys.addNodeErr(&reply[index], sys.peerClients[index], err)
		}
	}
	return reply
}

// GetProcInfo - Process information
func (sys *NotificationSys) GetProcInfo(ctx context.Context) []madmin.ProcInfo {
	reply := make([]madmin.ProcInfo, len(sys.peerClients))

	g := errgroup.WithNErrs(len(sys.peerClients))

  }

  private Type resolveTypeArgsForSubclass(Class<?> subclass) {
    // If both runtimeType and subclass are not parameterized, return subclass
    // If runtimeType is not parameterized but subclass is, process subclass as a parameterized type
    // If runtimeType is a raw type (i.e. is a parameterized type specified as a Class<?>), we
    // return subclass as a raw type
    if (runtimeType instanceof Class

또한 보통 이 **로드 밸런서**는 클러스터 내 *다른* 앱으로 가는 요청(예: 다른 도메인, 또는 다른 URL 경로 접두사 아래로 가는 요청)도 처리할 수 있으며, 그 통신을 클러스터에서 실행 중인 *그 다른* 애플리케이션의 올바른 컨테이너로 전달할 수 있습니다.

### 컨테이너당 하나의 프로세스 { #one-process-per-container }

이 시나리오에서는 이미 클러스터 레벨에서 복제를 처리하고 있으므로, **컨테이너당 단일 (Uvicorn) 프로세스**를 두는 것이 좋을 가능성이 큽니다.

common --repo_env=ML_WHEEL_BUILD_DATE=""
common --repo_env=ML_WHEEL_VERSION_SUFFIX=""

common --incompatible_default_to_explicit_init_py

# For projects which use TensorFlow as part of a Bazel build process, putting
# nothing in a bazelrc will default to a monolithic build. The following line
# opts in to modular op registration support by default.
common --define framework_shared_object=true