autoscaling_v2beta2
ContainerResourceMetricSource
lightkube.models.autoscaling_v2beta2.ContainerResourceMetricSource(container, name, target)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.
parameters
- container
str- container is the name of the container in the pods of the scaling target - name
str- name is the name of the resource in question. - target
MetricTarget- target specifies the target value for the given metric
ContainerResourceMetricStatus
lightkube.models.autoscaling_v2beta2.ContainerResourceMetricStatus(container, current, name)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.
parameters
- container
str- Container is the name of the container in the pods of the scaling target - current
MetricValueStatus- current contains the current value for the given metric - name
str- Name is the name of the resource in question.
CrossVersionObjectReference
lightkube.models.autoscaling_v2beta2.CrossVersionObjectReference(kind, name, apiVersion=None)ExternalMetricSource
lightkube.models.autoscaling_v2beta2.ExternalMetricSource(metric, target)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).
parameters
- metric
MetricIdentifier- metric identifies the target metric by name and selector - target
MetricTarget- target specifies the target value for the given metric
ExternalMetricStatus
lightkube.models.autoscaling_v2beta2.ExternalMetricStatus(current, metric)ExternalMetricStatus indicates the current value of a global metric not associated with any Kubernetes object.
parameters
- current
MetricValueStatus- current contains the current value for the given metric - metric
MetricIdentifier- metric identifies the target metric by name and selector
HPAScalingPolicy
lightkube.models.autoscaling_v2beta2.HPAScalingPolicy(periodSeconds, type, value)HPAScalingPolicy is a single policy which must hold true for a specified past interval.
parameters
- periodSeconds
int- 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
str- Type is used to specify the scaling policy. - value
int- Value contains the amount of change which is permitted by the policy. It must be greater than zero
HPAScalingRules
lightkube.models.autoscaling_v2beta2.HPAScalingRules(policies=None, selectPolicy=None, stabilizationWindowSeconds=None)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.
parameters
- policies
HPAScalingPolicy- (optional) 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
str- (optional) selectPolicy is used to specify which policy should be used. If not set, the default value MaxPolicySelect is used. - stabilizationWindowSeconds
int- (optional) 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).
HorizontalPodAutoscaler
lightkube.models.autoscaling_v2beta2.HorizontalPodAutoscaler(apiVersion=None, kind=None, metadata=None, spec=None, status=None)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.
parameters
- apiVersion
str- (optional) APIVersion defines the versioned schema of this representation of an object. Servers should convert recognized schemas to the latest internal value, and may reject unrecognized values. More info - kind
str- (optional) Kind is a string value representing the REST resource this object represents. Servers may infer this from the endpoint the client submits requests to. Cannot be updated. In CamelCase. More info - metadata
meta_v1.ObjectMeta- (optional) metadata is the standard object metadata. More info - spec
HorizontalPodAutoscalerSpec- (optional) spec is the specification for the behaviour of the autoscaler. More info - status
HorizontalPodAutoscalerStatus- (optional) status is the current information about the autoscaler.
HorizontalPodAutoscalerBehavior
lightkube.models.autoscaling_v2beta2.HorizontalPodAutoscalerBehavior(scaleDown=None, scaleUp=None)HorizontalPodAutoscalerBehavior configures the scaling behavior of the target in both Up and Down directions (scaleUp and scaleDown fields respectively).
parameters
- scaleDown
HPAScalingRules- (optional) scaleDown is scaling policy for scaling Down. If not set, the default value is to allow to scale down to minReplicas pods, with a 300 second stabilization window (i.e., the highest recommendation for the last 300sec is used). - scaleUp
HPAScalingRules- (optional) scaleUp is scaling policy for scaling Up. If not set, the default value is the higher of:- increase no more than 4 pods per 60 seconds
- double the number of pods per 60 seconds No stabilization is used.
HorizontalPodAutoscalerCondition
lightkube.models.autoscaling_v2beta2.HorizontalPodAutoscalerCondition(status, type, lastTransitionTime=None, message=None, reason=None)HorizontalPodAutoscalerCondition describes the state of a HorizontalPodAutoscaler at a certain point.
parameters
- status
str- status is the status of the condition (True, False, Unknown) - type
str- type describes the current condition - lastTransitionTime
meta_v1.Time- (optional) lastTransitionTime is the last time the condition transitioned from one status to another - message
str- (optional) message is a human-readable explanation containing details about the transition - reason
str- (optional) reason is the reason for the condition's last transition.
HorizontalPodAutoscalerList
lightkube.models.autoscaling_v2beta2.HorizontalPodAutoscalerList(items, apiVersion=None, kind=None, metadata=None)HorizontalPodAutoscalerList is a list of horizontal pod autoscaler objects.
parameters
- items
HorizontalPodAutoscaler- items is the list of horizontal pod autoscaler objects. - apiVersion
str- (optional) APIVersion defines the versioned schema of this representation of an object. Servers should convert recognized schemas to the latest internal value, and may reject unrecognized values. More info - kind
str- (optional) Kind is a string value representing the REST resource this object represents. Servers may infer this from the endpoint the client submits requests to. Cannot be updated. In CamelCase. More info - metadata
meta_v1.ListMeta- (optional) metadata is the standard list metadata.
HorizontalPodAutoscalerSpec
lightkube.models.autoscaling_v2beta2.HorizontalPodAutoscalerSpec(maxReplicas, scaleTargetRef, behavior=None, metrics=None, minReplicas=None)HorizontalPodAutoscalerSpec describes the desired functionality of the HorizontalPodAutoscaler.
parameters
- maxReplicas
int- maxReplicas is the upper limit for the number of replicas to which the autoscaler can scale up. It cannot be less that minReplicas. - scaleTargetRef
CrossVersionObjectReference- scaleTargetRef points to the target resource to scale, and is used to the pods for which metrics should be collected, as well as to actually change the replica count. - behavior
HorizontalPodAutoscalerBehavior- (optional) 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. - metrics
MetricSpec- (optional) 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
int- (optional) 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.
HorizontalPodAutoscalerStatus
lightkube.models.autoscaling_v2beta2.HorizontalPodAutoscalerStatus(currentReplicas, desiredReplicas, conditions=None, currentMetrics=None, lastScaleTime=None, observedGeneration=None)HorizontalPodAutoscalerStatus describes the current status of a horizontal pod autoscaler.
parameters
- currentReplicas
int- currentReplicas is current number of replicas of pods managed by this autoscaler, as last seen by the autoscaler. - desiredReplicas
int- desiredReplicas is the desired number of replicas of pods managed by this autoscaler, as last calculated by the autoscaler. - conditions
HorizontalPodAutoscalerCondition- (optional) conditions is the set of conditions required for this autoscaler to scale its target, and indicates whether or not those conditions are met. - currentMetrics
MetricStatus- (optional) currentMetrics is the last read state of the metrics used by this autoscaler. - lastScaleTime
meta_v1.Time- (optional) lastScaleTime is the last time the HorizontalPodAutoscaler scaled the number of pods, used by the autoscaler to control how often the number of pods is changed. - observedGeneration
int- (optional) observedGeneration is the most recent generation observed by this autoscaler.
MetricIdentifier
lightkube.models.autoscaling_v2beta2.MetricIdentifier(name, selector=None)MetricIdentifier defines the name and optionally selector for a metric
parameters
- name
str- name is the name of the given metric - selector
meta_v1.LabelSelector- (optional) 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.
MetricSpec
lightkube.models.autoscaling_v2beta2.MetricSpec(type, containerResource=None, external=None, object=None, pods=None, resource=None)MetricSpec specifies how to scale based on a single metric (only type and
one other matching field should be set at once).
parameters
- type
str- 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 - containerResource
ContainerResourceMetricSource- (optional) container resource refers to a resource metric (such as those specified in requests and limits) known to Kubernetes describing a single container in each pod of 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. This is an alpha feature and can be enabled by the HPAContainerMetrics feature flag. - external
ExternalMetricSource- (optional) external refers to a global metric that is not associated with any Kubernetes object. It allows autoscaling based on information coming from components running outside of cluster (for example length of queue in cloud messaging service, or QPS from loadbalancer running outside of cluster). - object
ObjectMetricSource- (optional) object refers to a metric describing a single kubernetes object (for example, hits-per-second on an Ingress object). - pods
PodsMetricSource- (optional) pods refers to 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
ResourceMetricSource- (optional) resource refers to a resource metric (such as those specified in requests and limits) known to Kubernetes 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.
MetricStatus
lightkube.models.autoscaling_v2beta2.MetricStatus(type, containerResource=None, external=None, object=None, pods=None, resource=None)MetricStatus describes the last-read state of a single metric.
parameters
- type
str- 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 - containerResource
ContainerResourceMetricStatus- (optional) container resource refers to a resource metric (such as those specified in requests and limits) known to Kubernetes 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. - external
ExternalMetricStatus- (optional) external refers to a global metric that is not associated with any Kubernetes object. It allows autoscaling based on information coming from components running outside of cluster (for example length of queue in cloud messaging service, or QPS from loadbalancer running outside of cluster). - object
ObjectMetricStatus- (optional) object refers to a metric describing a single kubernetes object (for example, hits-per-second on an Ingress object). - pods
PodsMetricStatus- (optional) pods refers to 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
ResourceMetricStatus- (optional) resource refers to a resource metric (such as those specified in requests and limits) known to Kubernetes 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.
MetricTarget
lightkube.models.autoscaling_v2beta2.MetricTarget(type, averageUtilization=None, averageValue=None, value=None)MetricTarget defines the target value, average value, or average utilization of a specific metric
parameters
- type
str- type represents whether the metric type is Utilization, Value, or AverageValue - averageUtilization
int- (optional) 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
resource.Quantity- (optional) averageValue is the target value of the average of the metric across all relevant pods (as a quantity) - value
resource.Quantity- (optional) value is the target value of the metric (as a quantity).
MetricValueStatus
lightkube.models.autoscaling_v2beta2.MetricValueStatus(averageUtilization=None, averageValue=None, value=None)MetricValueStatus holds the current value for a metric
parameters
- averageUtilization
int- (optional) 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. - averageValue
resource.Quantity- (optional) averageValue is the current value of the average of the metric across all relevant pods (as a quantity) - value
resource.Quantity- (optional) value is the current value of the metric (as a quantity).
ObjectMetricSource
lightkube.models.autoscaling_v2beta2.ObjectMetricSource(describedObject, metric, target)ObjectMetricSource indicates how to scale on a metric describing a kubernetes object (for example, hits-per-second on an Ingress object).
parameters
- describedObject
CrossVersionObjectReference- - metric
MetricIdentifier- metric identifies the target metric by name and selector - target
MetricTarget- target specifies the target value for the given metric
ObjectMetricStatus
lightkube.models.autoscaling_v2beta2.ObjectMetricStatus(current, describedObject, metric)ObjectMetricStatus indicates the current value of a metric describing a kubernetes object (for example, hits-per-second on an Ingress object).
parameters
- current
MetricValueStatus- current contains the current value for the given metric - describedObject
CrossVersionObjectReference- - metric
MetricIdentifier- metric identifies the target metric by name and selector
PodsMetricSource
lightkube.models.autoscaling_v2beta2.PodsMetricSource(metric, target)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.
parameters
- metric
MetricIdentifier- metric identifies the target metric by name and selector - target
MetricTarget- target specifies the target value for the given metric
PodsMetricStatus
lightkube.models.autoscaling_v2beta2.PodsMetricStatus(current, metric)PodsMetricStatus indicates the current value of a metric describing each pod in the current scale target (for example, transactions-processed-per-second).
parameters
- current
MetricValueStatus- current contains the current value for the given metric - metric
MetricIdentifier- metric identifies the target metric by name and selector
ResourceMetricSource
lightkube.models.autoscaling_v2beta2.ResourceMetricSource(name, target)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.
parameters
- name
str- name is the name of the resource in question. - target
MetricTarget- target specifies the target value for the given metric
ResourceMetricStatus
lightkube.models.autoscaling_v2beta2.ResourceMetricStatus(current, name)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.
parameters
- current
MetricValueStatus- current contains the current value for the given metric - name
str- Name is the name of the resource in question.