MinIO is a cloud-native application designed to scale in a sustainable manner in multi-tenant environments. Orchestration platforms provide perfect launchpad for MinIO to scale. Below is the list of MinIO deployment documents for various orchestration platforms:

  }

  static boolean isFinite(double d) {
    return getExponent(d) <= MAX_EXPONENT;
  }

  static boolean isNormal(double d) {
    return getExponent(d) >= MIN_EXPONENT;
  }

  /*
   * 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;

  }

  static boolean isFinite(double d) {
    return getExponent(d) <= MAX_EXPONENT;
  }

  static boolean isNormal(double d) {
    return getExponent(d) >= MIN_EXPONENT;
  }

  /*
   * 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;

				p.errorf("%s doesn't support scaled register format", p.arch.Name)
			} else {
				a.Scale = int16(scale)
			}
		}
		p.get(')')
	} else if scale != 0 {
		if p.arch.Family == sys.ARM64 {
			p.errorf("arm64 doesn't support scaled register format")
		}
		// First (R) was missing, all we have is (R*scale).
		a.Reg = 0
		a.Index = r1
		a.Scale = int16(scale)
	}
}

- Output for the `ScalingReplicaSet` event has changed from:
      Scaled <up|down> replica set <replica-set-name> to <new-value> from <old-value>
  to:

`Policy` optionally took in a `tf.compat.v1.mixed_precision.LossScale` in the constructor, which defaulted to a dynamic loss scale for the `"mixed_float16"` policy and no loss scale for other policies. In `Model.compile`, if the model's policy had a loss scale, the optimizer would be wrapped with a `LossScaleOptimizer`. With the non-experimental `Policy`, there is no loss scale associated with the `Policy`, and `Model.compile` wraps the optimizer with a `LossScaleOptimizer` if and only if the policy...

- Fixed a `v1.28.0` regression where `kube-controller-manager` can crash when `StatefulSet` with `Parallel` policy and PVC labels are scaled up. ([#121142](https://github.com/kubernetes/kubernetes/pull/121142), [@aleksandra-malinowska](https://github.com/aleksandra-malinowska))

   *
   * @param scale the scale for the quantiles to be calculated, i.e. the q of the q-quantiles, which
   *     must be positive
   */
  public static Scale scale(int scale) {
    return new Scale(scale);
  }

  /**
   * Describes the point in a fluent API chain where only the scale (i.e. the q in q-quantiles) has
   * been specified.
   *
   * @since 20.0
   */
  public static final class Scale {

	h.ItemsSkipped = h.ResumeItemsSkipped
	h.BytesDone = h.ResumeBytesDone
	h.BytesFailed = h.ResumeBytesFailed
	h.BytesSkipped = h.ResumeBytesSkipped
}

// bucketDone should be called when a bucket is done healing.
// Adds the bucket to the list of healed buckets and updates resume numbers.
func (h *healingTracker) bucketDone(bucket string) {
	h.mu.Lock()
	defer h.mu.Unlock()

	h.ResumeItemsHealed = h.ItemsHealed

	sync.RWMutex

	// map of heal path to heal sequence
	healSeqMap map[string]*healSequence // Indexed by endpoint
	// keep track of the healing status of disks in the memory
	//   false: the disk needs to be healed but no healing routine is started
	//    true: the disk is currently healing
	healLocalDisks map[Endpoint]bool
	healStatus     map[string]healingTracker // Indexed by disk ID
}