assertThat(UnsignedLongs.remainder(0xfffffffffffffffeL, 2)).isEqualTo(0);
    assertThat(UnsignedLongs.remainder(0xfffffffffffffffeL, 5)).isEqualTo(4);
  }

  @GwtIncompatible // Too slow in GWT (~3min fully optimized)
  public void testDivideRemainderEuclideanProperty() {
    // Use a seed so that the test is deterministic:
    Random r = new Random(0L);
    for (int i = 0; i < 1000000; i++) {

    try {
      // if waiting works, this should get stuck
      Queues.drain(q, new ArrayList<>(), 1, MAX_VALUE, NANOSECONDS);
      fail();
    } catch (InterruptedException expected) {
      // we indeed waited; a slow thread had enough time to interrupt us
    }
  }

  // same as above; uninterruptible version
  @SuppressWarnings("ThreadPriorityCheck") // TODO: b/175898629 - Consider onSpinWait.

// and returns nil.
func osMkdirAll(dirPath string, perm os.FileMode, baseDir string) error {
	if baseDir != "" {
		if strings.HasPrefix(baseDir, dirPath) {
			return nil
		}
	}

	// Slow path: make sure parent exists and then call Mkdir for path.
	i := len(dirPath)
	for i > 0 && os.IsPathSeparator(dirPath[i-1]) { // Skip trailing path separator.
		i--
	}

	j := i

         * problems can exist with methods like FutureTask.done(), not to mention slow calls to
         * Thread.interrupt() (as discussed in InterruptibleTask). At the end of the day, it's
         * unlikely that cancel() will be slow, so we can probably get away with calling it while
         * holding a lock. Still, it would be nice to avoid somehow.
         */

On the other hand, if you have 2 servers and you are using **100% of their CPU and RAM**, at some point one process will ask for more memory, and the server will have to use the disk as "memory" (which can be thousands of times slower), or even **crash**. Or one process might need to do some computation and would have to wait until the CPU is free again.

   * search for this mapping by randomly varying the hash codes of
   * colliding threads.  Because search is random, and collisions
   * only become known via CAS failures, convergence can be slow,
   * and because threads are typically not bound to CPUS forever,
   * may not occur at all. However, despite these limitations,
   * observed contention rates are typically low in these cases.
   *

    assertTrue(enormous instanceof RegularContiguousSet);
    // We can't use reserializeAndAssert because it calls hashCode, which is enormously slow.
    ContiguousSet<Integer> enormousReserialized = reserialize(enormous);
    assertEquals(enormous, enormousReserialized);
  }

  private static final DiscreteDomain<Integer> UNBOUNDED_THROWING_DOMAIN =

            });

            cbWithMetrics.executeWithCircuitBreaker(() -> {
                try {
                    Thread.sleep(300);
                } catch (InterruptedException e) {}
                return "slow";
            });

            // Check metrics
            assertTrue(cbWithMetrics.getAverageResponseTime() > 0, "Average response time should be tracked");

disabled will be synced to the target cluster. Depending on the number of previously existing objects, the existing objects that are now eligible to be replicated will eventually be synced to the target cluster as the scanner schedules them. This may be slower depending on the load on the cluster, latency and size of the namespace.

In the rare event that target DR site is entirely lost and previously replicated objects to the DR cluster need to be re-replicated, `mc replicate resync start alias/bucket...

    HashTestUtils.assertInvariants(Hashing.fingerprint2011());
    assertThat(Hashing.fingerprint2011().toString()).isEqualTo("Hashing.fingerprint2011()");
  }

  @AndroidIncompatible // slow TODO(cpovirk): Maybe just reduce iterations under Android.
  public void testGoodFastHash() {
    for (int i = 1; i < 200; i += 17) {
      HashFunction hasher = Hashing.goodFastHash(i);