// This can not be 0 if MaxSurge is 0.
  // Defaults to 25%.
  // Example: when this is set to 30%, the old ReplicaSet can be scaled down to 70% of desired pods
  // immediately when the rolling update starts. Once new pods are ready, old ReplicaSet
  // can be scaled down further, followed by scaling up the new ReplicaSet, ensuring
  // that the total number of pods available at all times during the update is at

  optional ScaleSpec spec = 2;

  // 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;
}

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

  optional ScaleSpec spec = 2;

  // 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 {
  // desired number of instances for the scaled object.
  // +optional
  optional int32 replicas = 1;
}

#### Optimizations

A naive implementation would simply regenerate all resources, of all subscribed types, for each client, on any configuration change. However, this scales poorly. As a result, we have many levels of optimizations to avoid doing this work.

  // +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 k8s.io.apimachinery.pkg.apis.meta.v1.GroupVersionKind kind = 2;

  // Resource is the fully-qualified resource being requested (for example, v1.pods)
  optional k8s.io.apimachinery.pkg.apis.meta.v1.GroupVersionResource resource = 3;

  // SubResource is the subresource being requested, if any (for example, "status" or "scale")
  // +optional
  optional string subResource = 4;

    override fun getInheritorsOfSealedClass(
        classSymbol: KtNamedClassOrObjectSymbol
    ): List<KtNamedClassOrObjectSymbol> {
        require(classSymbol.modality == Modality.SEALED)
        require(classSymbol is KtFirNamedClassOrObjectSymbol)

        val inheritorClassIds = classSymbol.firSymbol.fir.getSealedClassInheritors(analysisSession.useSiteSession)

        return with(analysisSession) {

  // +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;
}

streaming compression due to its stability and performance.

This algorithm is specifically optimized for machine generated content.
Write throughput is typically at least 500MB/s per CPU core,
and scales with the number of available CPU cores.
Decompression speed is typically at least 1GB/s.

This means that in cases where raw IO is below these numbers

            firDiagnostic as KtPsiDiagnostic,
            token,
        )
    }
    add(FirErrors.SEALED_SUPERTYPE) { firDiagnostic ->
        SealedSupertypeImpl(
            firDiagnostic as KtPsiDiagnostic,
            token,
        )
    }
    add(FirErrors.SEALED_SUPERTYPE_IN_LOCAL_CLASS) { firDiagnostic ->
        SealedSupertypeInLocalClassImpl(
            firDiagnostic.a,