## Changes since v1.1.1

### Major Themes

  * <strong>Significant scale improvements</strong>. Increased cluster scale by 400% to 1000 nodes with 30,000 pods per cluster.
Kubelet supports 100 pods per node with 4x reduced system overhead.

            "BigInteger cannot be converted to InetAddress because it has more than %d"
                + " bytes: %s",
            numBytes, address);
      }
    }

    // Copy the bytes into the least significant positions.
    System.arraycopy(addressBytes, srcPos, targetCopyArray, destPos, copyLength);

    try {
      return InetAddress.getByAddress(targetCopyArray);
    } catch (UnknownHostException impossible) {

- Kube-proxy iptables probabilities are now more granular and will result in better distribution beyond 319 endpoints. ([#83599](https://github.com/kubernetes/kubernetes/pull/83599), [@robscott](https://github.com/robscott))
- Significant kube-proxy performance improvements for non UDP ports. ([#83208](https://github.com/kubernetes/kubernetes/pull/83208), [@robscott](https://github.com/robscott))

   *
   *  * Invalid percent-encoded sequences like `%xx` will be encoded like `%25xx`.
   *
   *  * Whitespace and control characters in the fragment will be stripped.
   *
   * These differences may have a significant consequence when the URI is interpreted by a
   * web server. For this reason the [URI class][URI] and this method should be avoided.
   */
  @JvmName("uri")
  fun toUri(): URI {

/opt/bin/minio` and process to perform `mc admin service restart alias/`. ### Upgrade Checklist - Test all upgrades in a lower environment (DEV, QA, UAT) before applying to production. Performing blind upgrades in production environments carries significant risk. - Read the release notes for MinIO *before* performing any upgrade, there is no forced requirement to upgrade to latest release upon every release. Some release may not be relevant to your setup, avoid upgrading production environments unnecessarily....

large the value of x is. // // The output will be resized to the size of m and overwritten. // //go:norace func (out *Nat) Mod(x *Nat, m *Modulus) *Nat { out.resetFor(m) // Working our way from the most significant to the least significant limb, // we can insert each limb at the least significant position, shifting all // previous limbs left by _W. This way each limb will get shifted by the // correct number of bits. We can insert at least N - 1 limbs without // overflowing m. After that, we need...

large the value of x is. // // The output will be resized to the size of m and overwritten. // //go:norace func (out *Nat) Mod(x *Nat, m *Modulus) *Nat { out.resetFor(m) // Working our way from the most significant to the least significant limb, // we can insert each limb at the least significant position, shifting all // previous limbs left by _W. This way each limb will get shifted by the // correct number of bits. We can insert at least N - 1 limbs without // overflowing m. After that, we need...

   * Returns x scaled by a power of 2 such that it is in the range [1, 2). Assumes x is positive,
   * normal, and finite.
   */
  static double scaleNormalize(double x) {
    long significand = doubleToRawLongBits(x) & SIGNIFICAND_MASK;
    return longBitsToDouble(significand | ONE_BITS);
  }

  static double bigToDouble(BigInteger x) {
    // This is an extremely fast implementation of BigInteger.doubleValue(). JDK patch pending.

   * Returns x scaled by a power of 2 such that it is in the range [1, 2). Assumes x is positive,
   * normal, and finite.
   */
  static double scaleNormalize(double x) {
    long significand = doubleToRawLongBits(x) & SIGNIFICAND_MASK;
    return longBitsToDouble(significand | ONE_BITS);
  }

  static double bigToDouble(BigInteger x) {
    // This is an extremely fast implementation of BigInteger.doubleValue(). JDK patch pending.

* `tf.keras`
    * `Model.compile` now support `steps_per_execution='auto'` as a parameter, allowing automatic tuning of steps per execution during `Model.fit`,
    `Model.predict`, and `Model.evaluate` for a significant performance boost.

## Thanks to our Contributors

This release contains contributions from many people at Google, as well as: