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"

      Header("server", ""),
      Header("set-cookie", ""),
      Header("strict-transport-security", ""),
      Header("transfer-encoding", ""),
      Header("user-agent", ""),
      Header("vary", ""),
      Header("via", ""),
      Header("www-authenticate", ""),
    )

  val NAME_TO_FIRST_INDEX = nameToFirstIndex()

  // http://tools.ietf.org/html/draft-ietf-httpbis-header-compression-12#section-3.1

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**.

}

// Tests validate the order of result of ListBuckets.
func testListBucketsOrder(obj ObjectLayer, instanceType string, t TestErrHandler) {
	// if implementation contains a map, order of map keys will vary.
	// this ensures they return in the same order each time.
	// add one and test exists.
	err := obj.MakeBucket(context.Background(), "bucket1", MakeBucketOptions{})
	if err != nil {

   * 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);

 *  Fix: Websockets no longer rebuffer socket streams.
 *  Fix: Websockets are now better at handling close frames.
 *  Fix: Content type matching is now case insensitive.
 *  Fix: `Vary` headers are not lost with `android.net.http.HttpResponseCache`.
 *  Fix: HTTP/2 wasn't enforcing stream timeouts when writing the underlying
    connection. Now it is.

   * without contention. Because assignment of entries to these partitions is not necessarily
   * uniform, the actual concurrency observed may vary. Ideally, you should choose a value to
   * accommodate as many threads as will ever concurrently modify the table. Using a significantly
   * higher value than you need can waste space and time, and a significantly lower value can lead

    return new Or(this, other);
  }

  /**
   * Returns a {@code char} matcher functionally equivalent to this one, but which may be faster to
   * query than the original; your mileage may vary. Precomputation takes time and is likely to be
   * worthwhile only if the precomputed matcher is queried many thousands of times.
   *