});

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

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

    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 =

         * 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.
         */

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...

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.

   *       </ol>
   *       Given all these possibilities, it is frequently possible for listeners to execute in UI
   *       threads, RPC network threads, or other latency-sensitive threads. In those cases, slow
   *       listeners can harm responsiveness, slow the system as a whole, or worse. (See also the
   *       note about locking below.)
   *   <li>If many tasks will be triggered by the same event, one heavyweight task may delay other

    assertThrows(
        UnsupportedOperationException.class,
        () -> rangeSet.removeAll(ImmutableRangeSet.of(Range.closed(6, 8))));
  }

  @AndroidIncompatible // slow
  public void testExhaustive() {
    ImmutableSet<Range<Integer>> ranges =
        ImmutableSet.of(
            Range.<Integer>all(),
            Range.<Integer>closedOpen(3, 5),
            Range.singleton(1),

 *       time.
 *   <li>If you only access one end of the queue, and don't use a maximum size, this class is
 *       functionally equivalent to {@link PriorityQueue}, but significantly slower.
 * </ul>
 *
 * @author Sverre Sundsdal
 * @author Torbjorn Gannholm
 * @since 8.0
 */
@GwtCompatible
public final class MinMaxPriorityQueue<E> extends AbstractQueue<E> {

  /**

    try {
      constructor = type.getConstructor();
    } catch (NoSuchMethodException e) {
      return arbitraryConstantInstanceOrNull(type);
    }
    constructor.setAccessible(true); // accessibility check is too slow
    try {
      return constructor.newInstance();
    } catch (InstantiationException | IllegalAccessException impossible) {
      throw new AssertionError(impossible);
    } catch (InvocationTargetException e) {

### Creating the `Settings` only once with `lru_cache` { #creating-the-settings-only-once-with-lru-cache }

Reading a file from disk is normally a costly (slow) operation, so you probably want to do it only once and then reuse the same settings object, instead of reading it for each request.

But every time we do:

```Python
Settings()
```