* der Task
* der Hintergrundtask
* die Taskfunktion

* das Template
* die Template-Engine

* die Typannotation
* der Typhinweis

* der Serverworker
* der Uvicorn-Worker
* der Gunicorn-Worker
* der Workerprozess
* die Workerklasse
* die Workload

* das Deployment
* deployen

* das SDK
* das Software Development Kit

* der `APIRouter`
* die `requirements.txt`

	if (checkOld > 0 && len(p.workers) != checkOld) || n == len(p.workers) || n < 1 {
		// Either already satisfied or worker count changed while we waited for the lock.
		return
	}
	for len(p.workers) < n {
		input := make(chan ReplicationWorkerOperation, 10000)
		p.workers = append(p.workers, input)

		go p.AddWorker(input, &p.activeWorkers)
	}
	for len(p.workers) > n {
		worker := p.workers[len(p.workers)-1]

        failureConditions {
            // JavaExecDebugIntegrationTest.debug session fails without debugger might cause JVM crash
            // Some soak tests produce OOM exceptions
            // There are also random worker crashes for some tests.
            // We have test-retry to handle the crash in tests
            javaCrash = false
        }
    })

fun getTestTaskName(
    testCoverage: TestCoverage,

type ReplicationStats struct {
	// map of site deployment ID to site replication status
	// for site replication - maintain stats at global level
	srStats *SRStats
	// active worker stats
	workers *ActiveWorkerStat
	// queue stats cache
	qCache queueCache

	pCache proxyStatsCache
	// mrf backlog stats
	mrfStats ReplicationMRFStats
	// for bucket replication, continue to use existing cache

		// If the channel reaches above half capacity
		// we spawn more workers. The workers spawned
		// from this main worker routine will exit
		// once the channel drops below half capacity
		// and when it's been at least 30 seconds since
		// we launched a new worker.
		if mainWorker && len(h.logCh) > cap(h.logCh)/2 {
			nWorkers := h.workers.Load()
			if nWorkers < h.maxWorkers {
				if time.Since(h.lastStarted).Milliseconds() > 10 {

    val promotionBuild: Property<Boolean>

    val releasedVersions: Property<ReleasedVersionsDetails>

}

interface ModuleTargetRuntimes {

    /**
     * Declare that this Gradle module runs as part of worker process.
     */
    val usedInWorkers: Property<Boolean>

    /**
     * Declare that this Gradle module runs as part of the wrapper or as part of a client process.

HSPLkotlinx/coroutines/scheduling/CoroutineScheduler$Worker;->nextInt(I)I
HSPLkotlinx/coroutines/scheduling/CoroutineScheduler$Worker;->pollGlobalQueues()Lkotlinx/coroutines/scheduling/Task;
HSPLkotlinx/coroutines/scheduling/CoroutineScheduler$Worker;->run()V
HSPLkotlinx/coroutines/scheduling/CoroutineScheduler$Worker;->setIndexInArray(I)V
HSPLkotlinx/coroutines/scheduling/CoroutineScheduler$Worker;->setNextParkedWorker(Ljava/lang/Object;)V

            <option value="$PROJECT_DIR$/platforms/core-execution/scoped-persistent-cache" />
            <option value="$PROJECT_DIR$/platforms/core-execution/snapshots" />
            <option value="$PROJECT_DIR$/platforms/core-execution/worker-main" />
            <option value="$PROJECT_DIR$/platforms/core-execution/workers" />

### 复制工具和策略示例

可以通过多种方法来实现这一目标，我将在接下来的章节中向您详细介绍具体策略，例如在谈论 Docker 和容器时。

要考虑的主要限制是必须有一个**单个**组件来处理**公共IP**中的**端口**。 然后它必须有一种方法将通信**传输**到复制的**进程/worker**。

以下是一些可能的组合和策略：

* **Gunicorn** 管理 **Uvicorn workers**
     * Gunicorn 将是监听 **IP** 和 **端口** 的 **进程管理器**，复制将通过 **多个 Uvicorn 工作进程** 进行
* **Uvicorn** 管理 **Uvicorn workers**
     * 一个 Uvicorn **进程管理器** 将监听 **IP** 和 **端口**，并且它将启动 **多个 Uvicorn 工作进程**

        }

        def stylesheetFile = new File(getTemporaryDir(), "dslHtml.xsl")
        def xslthlConfigFile = getStylesheetHighlightFile().get().asFile.toURI()

        // TODO: Implement this with the worker API
        workerLeaseService.runAsIsolatedTask({
            source.visit { FileVisitDetails fvd ->
                if (fvd.isDirectory()) {
                    return
                }