* Reduce verbosity of volume reconciler when attaching volumes ([#36900](https://github.com/kubernetes/kubernetes/pull/36900), [@codablock](https://github.com/codablock))
* We change the default attach_detach_controller sync period to 1 minute to reduce the query frequency through cloud provider to check whether volumes are attached or not. ([#41363](https://github.com/kubernetes/kubernetes/pull/41363), [@jingxu97](https://github.com/jingxu97))

- Volumes are no longer detached from healthy nodes after 6 minutes timeout. 6 minute force-detach timeout is used only for unhealthy nodes (`node.status.conditions["Ready"]!= true`). ([#110721](https://github.com/kubernetes/kubernetes/pull/110721), [@jsafrane](https://github.com/jsafrane))

			break
		}
		replLogOnceIf(context.Background(), fmt.Errorf("unable to initialize site replication subsystem: (%w)", err), "site-relication-init")

		duration := max(time.Duration(r.Float64()*float64(time.Minute)),
			// Make sure to sleep at least a second to avoid high CPU ticks.
			time.Second)
		time.Sleep(duration)
	}
	c.RLock()
	defer c.RUnlock()
	if c.enabled {

     *
     * Consequently:
     * 1. If the previous mean is finite and the new value is non-finite then the new mean is that
     *    value (whether it is NaN or infinity).
     * 2. If the new value is finite and the previous mean is non-finite then the mean is unchanged
     *    (whether it is NaN or infinity).
     * 3. If both the previous mean and the new value are non-finite and...

   * is not guaranteed to return zero when the dataset consists of the same value multiple times,
   * due to numerical errors. However, it is guaranteed never to return a negative result.
   *
   * <h3>Non-finite values</h3>
   *
   * <p>If the dataset contains any non-finite values ({@link Double#POSITIVE_INFINITY}, {@link

   *
   * <p>This is guaranteed to return zero if the dataset contains a single pair of finite values. It
   * is not guaranteed to return zero when the dataset consists of the same pair of values multiple
   * times, due to numerical errors.
   *
   * <h3>Non-finite values</h3>
   *
   * <p>If the dataset contains any non-finite values ({@link Double#POSITIVE_INFINITY}, {@link

  public void testSchedule() {
    MockExecutor mock = new MockExecutor();
    TestExecutor testExecutor = new TestExecutor(mock);

    Future<?> unused1 = testExecutor.schedule(DO_NOTHING, 10, MINUTES);
    mock.assertLastMethodCalled("scheduleRunnable", 10, MINUTES);

    Future<?> unused2 = testExecutor.schedule(callable(DO_NOTHING), 5, SECONDS);
    mock.assertLastMethodCalled("scheduleCallable", 5, SECONDS);
  }

   *
   * <p>This is guaranteed to return zero if the dataset contains a single pair of finite values. It
   * is not guaranteed to return zero when the dataset consists of the same pair of values multiple
   * times, due to numerical errors.
   *
   * <h3>Non-finite values</h3>
   *
   * <p>If the dataset contains any non-finite values ({@link Double#POSITIVE_INFINITY}, {@link

    assertThat(TWO_VALUES_PAIRED_STATS.populationCovariance())
        .isWithin(ALLOWED_ERROR)
        .of(TWO_VALUES_SUM_OF_PRODUCTS_OF_DELTAS / 2);
    // For datasets of many double values, we test many combinations of finite and non-finite
    // x-values:
    for (ManyValues values : ALL_MANY_VALUES) {
      PairedStats stats = createPairedStatsOf(values.asIterable(), OTHER_MANY_VALUES);
      double populationCovariance = stats.populationCovariance();

    assertThat(TWO_VALUES_PAIRED_STATS.populationCovariance())
        .isWithin(ALLOWED_ERROR)
        .of(TWO_VALUES_SUM_OF_PRODUCTS_OF_DELTAS / 2);
    // For datasets of many double values, we test many combinations of finite and non-finite
    // x-values:
    for (ManyValues values : ALL_MANY_VALUES) {
      PairedStats stats = createPairedStatsOf(values.asIterable(), OTHER_MANY_VALUES);
      double populationCovariance = stats.populationCovariance();