// +optional
  repeated MetricSpec metrics = 4;

  // behavior configures the scaling behavior of the target
  // in both Up and Down directions (scaleUp and scaleDown fields respectively).
  // If not set, the default HPAScalingRules for scale up and scale down are used.
  // +optional
  optional HorizontalPodAutoscalerBehavior behavior = 5;
}

  // +optional
  repeated MetricSpec metrics = 4;

  // behavior configures the scaling behavior of the target
  // in both Up and Down directions (scaleUp and scaleDown fields respectively).
  // If not set, the default HPAScalingRules for scale up and scale down are used.
  // +optional
  optional HorizontalPodAutoscalerBehavior behavior = 5;
}

  // status defines current status of the scale. More info: https://git.k8s.io/community/contributors/devel/sig-architecture/api-conventions.md#spec-and-status. Read-only.
  // +optional
  optional ScaleStatus status = 3;
}

// ScaleSpec describes the attributes of a scale subresource
message ScaleSpec {
  // replicas is the number of observed instances of the scaled object.
  // +optional
  optional int32 replicas = 1;

message HorizontalPodAutoscalerSpec {
  // reference to scaled resource; horizontal pod autoscaler will learn the current resource consumption
  // and will set the desired number of pods by using its Scale subresource.
  optional CrossVersionObjectReference scaleTargetRef = 1;

  // minReplicas is the lower limit for the number of replicas to which the autoscaler
  // can scale down.  It defaults to 1 pod.  minReplicas is allowed to be 0 if the

// Package-wide variables from generator "generated".
option go_package = "k8s.io/api/autoscaling/v2beta1";

// ContainerResourceMetricSource indicates how to scale on a resource metric known to
// Kubernetes, as specified in requests and limits, describing each pod in the
// current scale target (e.g. CPU or memory).  The values will be averaged
// together before being compared to the target.  Such metrics are built in to

- Replace scale down forbidden window with scale down stabilization window. Rather than waiting a fixed period of time between scale downs HPA now scales down to the highest recommendation it during the scale down stabilization window. ([#68122](https://github.com/kubernetes/kubernetes/pull/68122), [@krzysztof-jastrzebski](https://github.com/krzysztof-jastrzebski))...

    get() = when {
        hasModifier(KtTokens.ABSTRACT_KEYWORD) -> Modality.ABSTRACT
        hasModifier(KtTokens.FINAL_KEYWORD) -> Modality.FINAL
        hasModifier(KtTokens.SEALED_KEYWORD) -> Modality.SEALED
        hasModifier(KtTokens.OPEN_KEYWORD) -> {
            if (this is KtCallableDeclaration && !hasBody()) {
                val parentDeclaration = this.getElementParentDeclaration()

MinIO is a high performance distributed object storage server, designed for large-scale private cloud infrastructure. MinIO is designed in a cloud-native manner to scale sustainably in multi-tenant environments. Orchestration platforms like Kubernetes provide perfect cloud-native environment to deploy and scale MinIO.

## MinIO Deployment on Kubernetes

There are multiple options to deploy MinIO on Kubernetes:

1. [Standalone Deployment](#standalone-deployment)
2. [Distributed Deployment](#distributed-deployment)
3. [Cloud Scale Deployment](#cloud-scale-deployment)

## 1. Standalone Deployment

To host multiple tenants on a single machine, run one MinIO Server per tenant with a dedicated HTTPS port, configuration, and data directory.

            k <= bias -> TMIN
            k >= bias + TMAX -> TMAX
            else -> k - bias
          }
        if (digit < t) break
        val scaleW = BASE - t
        if (w > Int.MAX_VALUE / scaleW) return false // Prevent overflow.
        w *= scaleW
      }
      bias = adapt(i - oldi, codePoints.size + 1, oldi == 0)
      val deltaN = i / (codePoints.size + 1)