lock {\n  width: 100%;\n}\n\n.fade {\n  transition: opacity 0.15s linear;\n}\n\n@media (prefers-reduced-motion: reduce) {\n  .fade {\n    transition: none;\n  }\n}\n\n.fade:not(.show) {\n  opacity: 0;\n}\n\n.collapse:not(.show) {\n  display: none;\n}\n\n.collapsing {\n  position: relative;\n  height: 0;\n  overflow: hidden;\n  transition: height 0.35s ease;\n}\n\n@media (prefers-reduced-motion: reduce) {\n  .collapsing {\n    transition: none;\n  }\n}\n\n.dropup,\n.dropright,\n.dropdown,\n.dropleft...

    Castle is great! But it's a large dependency (6.5 MiB) and its security provider feature
    impacts VM-wide behavior.

 *  New: Reduce contention for applications that make a very high number of concurrent requests.
    Previously OkHttp used its connection pool as a lock when making changes to connections and

* 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))

* **Rápido de programar**: Incrementa la velocidad de desarrollo entre 200% y 300%. *
* **Menos errores**: Reduce los errores humanos (de programador) aproximadamente un 40%. *

	return "Storage reached its minimum free drive threshold."
}

// SlowDown  too many file descriptors open or backend busy .
type SlowDown struct{}

func (e SlowDown) Error() string {
	return "Please reduce your request rate"
}

// RQErrType reason for read quorum error.
type RQErrType int

const (
	// RQInsufficientOnlineDrives - not enough online drives.
	RQInsufficientOnlineDrives RQErrType = 1 << iota

 * order. Any removal invalidates any ordering guarantees.
 *
 * <p>This class should not be assumed to be universally superior to {@code java.util.HashSet}.
 * Generally speaking, this class reduces object allocation and memory consumption at the price of
 * moderately increased constant factors of CPU. Only use this class when there is a specific reason
 * to prioritize memory over CPU.
 *
 * @author Dimitris Andreou

    HashCode expected1 = randomHash(hashFunction, new Random(1L), numActions);
    HashCode expected2 = randomHash(hashFunction, new Random(2L), numActions);

    // equivalent, but overlapping, computations (should produce the same results as above)
    Random random1 = new Random(1L);
    Random random2 = new Random(2L);
    Hasher hasher1 = hashFunction.newHasher();
    Hasher hasher2 = hashFunction.newHasher();

   *     -> attackerIntermediate
   *         -> phonyVictim
   * ```
   *
   * Some implementations fail the TLS handshake when they see the long chain, and don't give
   * CertificatePinner the opportunity to produce a different chain from their own. This includes
   * the OpenJDK 11 TLS implementation, which itself fails the handshake when it encounters a non-CA
   * certificate.
   */
  @Test
  fun signersMustHaveCaBitSet() {

   *
   * @since 22.0
   */
  public long approximateElementCount() {
    long bitSize = bits.bitSize();
    long bitCount = bits.bitCount();

    /**
     * Each insertion is expected to reduce the # of clear bits by a factor of
     * `numHashFunctions/bitSize`. So, after n insertions, expected bitCount is `bitSize * (1 - (1 -

* New flag --endpoint-updates-batch-period in kube-controller-manager can be used to reduce number of endpoints updates generated by pod changes. ([#80509](https://github.com/kubernetes/kubernetes/pull/80509), [@mborsz](https://github.com/mborsz))