numHealers = 4
	}
	// allow overriding this value as well..
	if v := globalHealConfig.GetWorkers(); v > 0 {
		numHealers = uint64(v)
	}

	healingLogEvent(ctx, "Healing drive '%s' - use %d parallel workers.", tracker.disk.String(), numHealers)

	jt, _ := workers.New(int(numHealers))

	healEntryDone := func(name string) healEntryResult {
		return healEntryResult{
			entryDone: true,
			name:      name,

			[]string{"hello", "dir/bar", "readonly"},
		},
		{
			"testdata/subdir.zip",
			[]string{"a/b/c"},
		},
	} {
		test := test
		t.Run(test.file, func(t *testing.T) {
			t.Parallel()
			z, err := OpenReader(test.file)
			if err != nil {
				t.Fatal(err)
			}
			defer z.Close()
			if err := fstest.TestFS(z, test.want...); err != nil {
				t.Error(err)
			}
		})
	}

## 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.

          <type>boolean</type>
          <description>
            Marks this Mojo as being thread-safe, i.e. the Mojo safely supports concurrent execution during parallel
            builds. Mojos without this annotation will make Maven output a warning when used during a parallel build
            session.
            @since Maven 3.0.
          </description>
          <defaultValue>false</defaultValue>
        </field>

	metadataArray := make([]FileInfo, len(disks))

	opts := ReadOptions{
		ReadData: readData,
		Healing:  healing,
	}

	g := errgroup.WithNErrs(len(disks))
	// Read `xl.meta` in parallel across disks.
	for index := range disks {
		g.Go(func() (err error) {
			if disks[index] == nil {
				return errDiskNotFound
			}

// loadFormatErasureAll - load all format config from all input disks in parallel.
func loadFormatErasureAll(storageDisks []StorageAPI, heal bool) ([]*formatErasureV3, []error) {
	// Initialize list of errors.
	g := errgroup.WithNErrs(len(storageDisks))

	// Initialize format configs.
	formats := make([]*formatErasureV3, len(storageDisks))

	// Load format from each disk in parallel
	for index := range storageDisks {
		g.Go(func() error {

	resource := pathJoin(volume, path)

	n.lockMapMutex.Lock()
	nsLk, found := n.lockMap[resource]
	if !found {
		nsLk = &nsLock{
			LRWMutex: lsync.NewLRWMutex(),
		}
		// Add a count to indicate that a parallel unlock doesn't clear this entry.
	}
	nsLk.ref++
	n.lockMap[resource] = nsLk
	n.lockMapMutex.Unlock()

	// Locking here will block (until timeout).
	if readLock {

  /** Confirm that [MultipartBody] and [MultipartReader] can work together. */
  @Test fun `multipart round trip`() {
    val body =
      MultipartBody
        .Builder("boundary")
        .setType(MultipartBody.PARALLEL)
        .addPart("Quick".toRequestBody("text/plain".toMediaType()))
        .addFormDataPart("color", "Brown")
        .addFormDataPart("animal", "fox.txt", "Fox".toRequestBody())
        .build()

  static final String ERROR_ADDED_SELF_LOOP = "Should not be allowed to add a self-loop edge.";
  static final String ERROR_ADDED_PARALLEL_EDGE = "Should not be allowed to add a parallel edge.";
  static final String ERROR_ADDED_EXISTING_EDGE =
      "Reusing an existing edge to connect different nodes succeeded";

  /** Creates and returns an instance of the graph to be tested. */

        }
        return availableSearchers;
    }

    /**
     * Performs concurrent searches using multiple searchers and fuses the results.
     * Executes searches in parallel across all provided searchers, then combines the results
     * using rank fusion algorithms to produce a unified result set.
     *
     * @param searchers array of searchers to use for concurrent searching