HorizontalPodAutoscaler [autoscaling/v2]

behavior

object

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

maxReplicas

integer

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

metrics

array

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.

metrics[]

object

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

minReplicas

integer

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.

scaleTargetRef

object

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

scaleDown

object

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.

scaleUp

object

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.

policies

array

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

policies[]

object

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

selectPolicy

string

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

stabilizationWindowSeconds

integer

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).

periodSeconds

integer

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

string

Type is used to specify the scaling policy.

value

integer

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

policies

array

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

policies[]

object

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

selectPolicy

string

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

stabilizationWindowSeconds

integer

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).

periodSeconds

integer

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

string

Type is used to specify the scaling policy.

value

integer

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

containerResource

object

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.

external

object

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).

object

object

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

pods

object

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.

resource

object

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.

type

string

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

container

string

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

name

string

name is the name of the resource in question.

target

object

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

averageUtilization

integer

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

averageValue

Quantity

averageValue is the target value of the average of the metric across all relevant pods (as a quantity)

type

string

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

value

Quantity

value is the target value of the metric (as a quantity).

metric

object

MetricIdentifier defines the name and optionally selector for a metric

target

object

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

name

string

name is the name of the given metric

selector

LabelSelector

selector is the string-encoded form of a standard kubernetes label selector for the given metric When set, it is passed as an additional parameter to the metrics server for more specific metrics scoping. When unset, just the metricName will be used to gather metrics.