com.coralogix.zio.k8s.model.autoscaling.v2beta2

Type members

Classlikes

case class ContainerResourceMetricSource(container: String, name: String, target: MetricTarget)

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 Kubernetes, and have special scaling options on top of those available to normal per-pod metrics using the "pods" source. Only one "target" type should be set.

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 Kubernetes, and have special scaling options on top of those available to normal per-pod metrics using the "pods" source. Only one "target" type should be set.

Value Params
container

container is the name of the container in the pods of the scaling target

name

name is the name of the resource in question.

Companion
object
class ContainerResourceMetricSourceFields(_prefix: Chunk[String])
case class ContainerResourceMetricStatus(container: String, current: MetricValueStatus, name: String)

ContainerResourceMetricStatus indicates the current value of a resource metric known to Kubernetes, as specified in requests and limits, describing a single container in each pod in the current scale target (e.g. CPU or memory). Such metrics are built in to Kubernetes, and have special scaling options on top of those available to normal per-pod metrics using the "pods" source.

ContainerResourceMetricStatus indicates the current value of a resource metric known to Kubernetes, as specified in requests and limits, describing a single container in each pod in the current scale target (e.g. CPU or memory). Such metrics are built in to Kubernetes, and have special scaling options on top of those available to normal per-pod metrics using the "pods" source.

Value Params
container

Container is the name of the container in the pods of the scaling target

name

Name is the name of the resource in question.

Companion
object
class ContainerResourceMetricStatusFields(_prefix: Chunk[String])
case class CrossVersionObjectReference(apiVersion: Optional[String], kind: String, name: String)

CrossVersionObjectReference contains enough information to let you identify the referred resource.

CrossVersionObjectReference contains enough information to let you identify the referred resource.

Value Params
apiVersion

API version of the referent

kind

Kind of the referent; More info: https://git.k8s.io/community/contributors/devel/sig-architecture/api-conventions.md#types-kinds"

name

Name of the referent; More info: http://kubernetes.io/docs/user-guide/identifiers#names

Companion
object
class CrossVersionObjectReferenceFields(_prefix: Chunk[String])

ExternalMetricSource indicates how to scale on a metric not associated with any Kubernetes object (for example length of queue in cloud messaging service, or QPS from loadbalancer running outside of cluster).

ExternalMetricSource indicates how to scale on a metric not associated with any Kubernetes object (for example length of queue in cloud messaging service, or QPS from loadbalancer running outside of cluster).

Companion
object
class ExternalMetricSourceFields(_prefix: Chunk[String])

ExternalMetricStatus indicates the current value of a global metric not associated with any Kubernetes object.

ExternalMetricStatus indicates the current value of a global metric not associated with any Kubernetes object.

Companion
object
class ExternalMetricStatusFields(_prefix: Chunk[String])
case class HPAScalingPolicy(periodSeconds: Int, `type`: String, value: Int)

HPAScalingPolicy is a single policy which must hold true for a specified past interval.

HPAScalingPolicy is a single policy which must hold true for a specified past interval.

Value Params
periodSeconds

PeriodSeconds specifies the window of time for which the policy should hold true. PeriodSeconds must be greater than zero and less than or equal to 1800 (30 min).

type

Type is used to specify the scaling policy.

value

Value contains the amount of change which is permitted by the policy. It must be greater than zero

Companion
object
class HPAScalingPolicyFields(_prefix: Chunk[String])
case class HPAScalingRules(policies: Optional[Vector[HPAScalingPolicy]], selectPolicy: Optional[String], stabilizationWindowSeconds: Optional[Int])

HPAScalingRules configures the scaling behavior for one direction. These Rules are applied after calculating DesiredReplicas from metrics for the HPA. They can limit the scaling velocity by specifying scaling policies. They can prevent flapping by specifying the stabilization window, so that the number of replicas is not set instantly, instead, the safest value from the stabilization window is chosen.

HPAScalingRules configures the scaling behavior for one direction. These Rules are applied after calculating DesiredReplicas from metrics for the HPA. They can limit the scaling velocity by specifying scaling policies. They can prevent flapping by specifying the stabilization window, so that the number of replicas is not set instantly, instead, the safest value from the stabilization window is chosen.

Value Params
policies

policies is a list of potential scaling polices which can be used during scaling. At least one policy must be specified, otherwise the HPAScalingRules will be discarded as invalid

selectPolicy

selectPolicy is used to specify which policy should be used. If not set, the default value MaxPolicySelect is used.

stabilizationWindowSeconds

StabilizationWindowSeconds is the number of seconds for which past recommendations should be considered while scaling up or scaling down. StabilizationWindowSeconds must be greater than or equal to zero and less than or equal to 3600 (one hour). If not set, use the default values: - For scale up: 0 (i.e. no stabilization is done). - For scale down: 300 (i.e. the stabilization window is 300 seconds long).

Companion
object
class HPAScalingRulesFields(_prefix: Chunk[String])

HorizontalPodAutoscaler is the configuration for a horizontal pod autoscaler, which automatically manages the replica count of any resource implementing the scale subresource based on the metrics specified.

HorizontalPodAutoscaler is the configuration for a horizontal pod autoscaler, which automatically manages the replica count of any resource implementing the scale subresource based on the metrics specified.

Companion
object

HorizontalPodAutoscalerBehavior configures the scaling behavior of the target in both Up and Down directions (scaleUp and scaleDown fields respectively).

HorizontalPodAutoscalerBehavior configures the scaling behavior of the target in both Up and Down directions (scaleUp and scaleDown fields respectively).

Companion
object
class HorizontalPodAutoscalerBehaviorFields(_prefix: Chunk[String])
case class HorizontalPodAutoscalerCondition(lastTransitionTime: Optional[Time], message: Optional[String], reason: Optional[String], status: String, `type`: String)

HorizontalPodAutoscalerCondition describes the state of a HorizontalPodAutoscaler at a certain point.

HorizontalPodAutoscalerCondition describes the state of a HorizontalPodAutoscaler at a certain point.

Value Params
message

message is a human-readable explanation containing details about the transition

reason

reason is the reason for the condition's last transition.

status

status is the status of the condition (True, False, Unknown)

type

type describes the current condition

Companion
object
class HorizontalPodAutoscalerConditionFields(_prefix: Chunk[String])
class HorizontalPodAutoscalerFields(_prefix: Chunk[String])
case class HorizontalPodAutoscalerSpec(behavior: Optional[HorizontalPodAutoscalerBehavior], maxReplicas: Int, metrics: Optional[Vector[MetricSpec]], minReplicas: Optional[Int], scaleTargetRef: CrossVersionObjectReference)

HorizontalPodAutoscalerSpec describes the desired functionality of the HorizontalPodAutoscaler.

HorizontalPodAutoscalerSpec describes the desired functionality of the HorizontalPodAutoscaler.

Value Params
maxReplicas

maxReplicas is the upper limit for the number of replicas to which the autoscaler can scale up. It cannot be less that minReplicas.

metrics

metrics contains the specifications for which to use to calculate the desired replica count (the maximum replica count across all metrics will be used). The desired replica count is calculated multiplying the ratio between the target value and the current value by the current number of pods. Ergo, metrics used must decrease as the pod count is increased, and vice-versa. See the individual metric source types for more information about how each type of metric must respond. If not set, the default metric will be set to 80% average CPU utilization.

minReplicas

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 alpha feature gate HPAScaleToZero is enabled and at least one Object or External metric is configured. Scaling is active as long as at least one metric value is available.

Companion
object
class HorizontalPodAutoscalerSpecFields(_prefix: Chunk[String])
case class HorizontalPodAutoscalerStatus(conditions: Vector[HorizontalPodAutoscalerCondition], currentMetrics: Optional[Vector[MetricStatus]], currentReplicas: Int, desiredReplicas: Int, lastScaleTime: Optional[Time], observedGeneration: Optional[Long])

HorizontalPodAutoscalerStatus describes the current status of a horizontal pod autoscaler.

HorizontalPodAutoscalerStatus describes the current status of a horizontal pod autoscaler.

Value Params
conditions

conditions is the set of conditions required for this autoscaler to scale its target, and indicates whether or not those conditions are met.

currentMetrics

currentMetrics is the last read state of the metrics used by this autoscaler.

currentReplicas

currentReplicas is current number of replicas of pods managed by this autoscaler, as last seen by the autoscaler.

desiredReplicas

desiredReplicas is the desired number of replicas of pods managed by this autoscaler, as last calculated by the autoscaler.

observedGeneration

observedGeneration is the most recent generation observed by this autoscaler.

Companion
object
class HorizontalPodAutoscalerStatusFields(_prefix: Chunk[String])
case class MetricIdentifier(name: String, selector: Optional[LabelSelector])

MetricIdentifier defines the name and optionally selector for a metric

MetricIdentifier defines the name and optionally selector for a metric

Value Params
name

name is the name of the given metric

Companion
object
class MetricIdentifierFields(_prefix: Chunk[String])
case class MetricSpec(containerResource: Optional[ContainerResourceMetricSource], external: Optional[ExternalMetricSource], `object`: Optional[ObjectMetricSource], pods: Optional[PodsMetricSource], resource: Optional[ResourceMetricSource], `type`: String)

MetricSpec specifies how to scale based on a single metric (only type and one other matching field should be set at once).

MetricSpec specifies how to scale based on a single metric (only type and one other matching field should be set at once).

Value Params
type

type is the type of metric source. It should be one of "ContainerResource", "External", "Object", "Pods" or "Resource", each mapping to a matching field in the object. Note: "ContainerResource" type is available on when the feature-gate HPAContainerMetrics is enabled

Companion
object
Companion
class
class MetricSpecFields(_prefix: Chunk[String])

MetricStatus describes the last-read state of a single metric.

MetricStatus describes the last-read state of a single metric.

Value Params
type

type is the type of metric source. It will be one of "ContainerResource", "External", "Object", "Pods" or "Resource", each corresponds to a matching field in the object. Note: "ContainerResource" type is available on when the feature-gate HPAContainerMetrics is enabled

Companion
object
Companion
class
class MetricStatusFields(_prefix: Chunk[String])
case class MetricTarget(averageUtilization: Optional[Int], averageValue: Optional[Quantity], `type`: String, value: Optional[Quantity])

MetricTarget defines the target value, average value, or average utilization of a specific metric

MetricTarget defines the target value, average value, or average utilization of a specific metric

Value Params
averageUtilization

averageUtilization is the target value of the average of the resource metric across all relevant pods, represented as a percentage of the requested value of the resource for the pods. Currently only valid for Resource metric source type

type

type represents whether the metric type is Utilization, Value, or AverageValue

Companion
object
Companion
class
class MetricTargetFields(_prefix: Chunk[String])
case class MetricValueStatus(averageUtilization: Optional[Int], averageValue: Optional[Quantity], value: Optional[Quantity])

MetricValueStatus holds the current value for a metric

MetricValueStatus holds the current value for a metric

Value Params
averageUtilization

currentAverageUtilization is the current value of the average of the resource metric across all relevant pods, represented as a percentage of the requested value of the resource for the pods.

Companion
object
class MetricValueStatusFields(_prefix: Chunk[String])
case class ObjectMetricSource(describedObject: CrossVersionObjectReference, metric: MetricIdentifier, target: MetricTarget)

ObjectMetricSource indicates how to scale on a metric describing a kubernetes object (for example, hits-per-second on an Ingress object).

ObjectMetricSource indicates how to scale on a metric describing a kubernetes object (for example, hits-per-second on an Ingress object).

Companion
object
class ObjectMetricSourceFields(_prefix: Chunk[String])

ObjectMetricStatus indicates the current value of a metric describing a kubernetes object (for example, hits-per-second on an Ingress object).

ObjectMetricStatus indicates the current value of a metric describing a kubernetes object (for example, hits-per-second on an Ingress object).

Companion
object
class ObjectMetricStatusFields(_prefix: Chunk[String])
case class PodsMetricSource(metric: MetricIdentifier, target: MetricTarget)

PodsMetricSource indicates how to scale on a metric describing each pod in the current scale target (for example, transactions-processed-per-second). The values will be averaged together before being compared to the target value.

PodsMetricSource indicates how to scale on a metric describing each pod in the current scale target (for example, transactions-processed-per-second). The values will be averaged together before being compared to the target value.

Companion
object
class PodsMetricSourceFields(_prefix: Chunk[String])

PodsMetricStatus indicates the current value of a metric describing each pod in the current scale target (for example, transactions-processed-per-second).

PodsMetricStatus indicates the current value of a metric describing each pod in the current scale target (for example, transactions-processed-per-second).

Companion
object
class PodsMetricStatusFields(_prefix: Chunk[String])
case class ResourceMetricSource(name: String, target: MetricTarget)

ResourceMetricSource 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 Kubernetes, and have special scaling options on top of those available to normal per-pod metrics using the "pods" source. Only one "target" type should be set.

ResourceMetricSource 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 Kubernetes, and have special scaling options on top of those available to normal per-pod metrics using the "pods" source. Only one "target" type should be set.

Value Params
name

name is the name of the resource in question.

Companion
object
class ResourceMetricSourceFields(_prefix: Chunk[String])
case class ResourceMetricStatus(current: MetricValueStatus, name: String)

ResourceMetricStatus indicates the current value of 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). Such metrics are built in to Kubernetes, and have special scaling options on top of those available to normal per-pod metrics using the "pods" source.

ResourceMetricStatus indicates the current value of 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). Such metrics are built in to Kubernetes, and have special scaling options on top of those available to normal per-pod metrics using the "pods" source.

Value Params
name

Name is the name of the resource in question.

Companion
object
class ResourceMetricStatusFields(_prefix: Chunk[String])