}
  }

  /**
   * Initialize the cache. This will include reading the journal files from the storage and building
   * up the necessary in-memory cache information.
   *
   * The initialization time may vary depending on the journal file size and the current actual
   * cache size. The application needs to be aware of calling this function during the
   * initialization phase and preferably in a background worker thread.
   *

    cacheHit.cacheResponse()
      .assertCode(200)
      .assertHeader("Donut", "a")
      .assertHeader("ETag", "v1")
      .assertRequestUrl(server.url("/"))
      .assertRequestHeader("Accept-Language") // No Vary on Accept-Language.
      .assertRequestHeader("Accept-Charset", "UTF-8") // Because of Vary on Accept-Charset.

  }

  @Test
  fun varyMultipleFieldsWithMatch() {
    server.enqueue(
      MockResponse.Builder()
        .addHeader("Cache-Control: max-age=60")
        .addHeader("Vary: Accept-Language, Accept-Charset")
        .addHeader("Vary: Accept-Encoding")
        .body("A")
        .build(),
    )
    server.enqueue(
      MockResponse.Builder()
        .body("B")
        .build(),
    )

   */
  public static final String KEEP_ALIVE = "Keep-Alive";
  /**
   * The HTTP <a href="https://github.com/WICG/nav-speculation/blob/main/no-vary-search.md">{@code
   * No-Vary-Seearch}</a> header field name.
   *
   * @since 32.0.0
   */
  public static final String NO_VARY_SEARCH = "No-Vary-Search";
  /**
   * The HTTP <a href="https://googlechrome.github.io/OriginTrials/#header">{@code Origin-Trial}</a>
   * header field name.

## Documenting the callback

The actual callback code will depend heavily on your own API app.

And it will probably vary a lot from one app to the next.

It could be just one or two lines of code, like:

```Python
callback_url = "https://example.com/api/v1/invoices/events/"

	OptimizeEnv = "MINIO_STORAGE_CLASS_OPTIMIZE"
	// Inline block indicates the size of the shard
	// that is considered for inlining, remember this
	// shard value is the value per drive shard it
	// will vary based on the parity that is configured
	// for the STANDARD storage_class.
	// inlining means data and metadata are written
	// together in a single file i.e xl.meta
	InlineBlockEnv = "MINIO_STORAGE_CLASS_INLINE_BLOCK"

And of course, the same machine would probably have **other processes** running as well, apart from your application.

An interesting detail is that the percentage of the **CPU used** by each process can **vary** a lot over time, but the **memory (RAM)** normally stays more or less **stable**.

   * The dispatcher used to respond to HTTP requests. The default dispatcher is a [QueueDispatcher],
   * which serves a fixed sequence of responses from a [queue][enqueue].
   *
   * Other dispatchers can be configured. They can vary the response based on timing or the content
   * of the request.
   */
  var dispatcher: Dispatcher = QueueDispatcher()

  private var portField: Int = -1
  val port: Int
    get() {
      before()

    for (int i = 0; i < map.segments.length; i++) {
      assertEquals(segmentSize, map.segments[i].table.length());
    }
  }

  public void testSetMaximumSize() {
    // vary maximumSize wrt concurrencyLevel

    for (int maxSize = 1; maxSize < 100; maxSize++) {
      checkMaximumSize(1, 8, maxSize);
      checkMaximumSize(2, 8, maxSize);
      checkMaximumSize(4, 8, maxSize);

    for (int i = 0; i < map.segments.length; i++) {
      assertEquals(segmentSize, map.segments[i].table.length());
    }
  }

  public void testSetMaximumSize() {
    // vary maximumSize wrt concurrencyLevel

    for (int maxSize = 1; maxSize < 100; maxSize++) {
      checkMaximumSize(1, 8, maxSize);
      checkMaximumSize(2, 8, maxSize);
      checkMaximumSize(4, 8, maxSize);