Struct HPAScalingRules

pub struct HPAScalingRules {
    pub policies: Option<Vec<HPAScalingPolicy>>,
    pub select_policy: Option<String>,
    pub stabilization_window_seconds: Option<i32>,
    pub tolerance: Option<Quantity>,
}

HPAScalingRules configures the scaling behavior for one direction via scaling Policy Rules and a configurable metric tolerance.

Scaling Policy 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.

The tolerance is applied to the metric values and prevents scaling too eagerly for small metric variations. (Note that setting a tolerance requires enabling the alpha HPAConfigurableTolerance feature gate.)

Fields

policies: Option<Vec<HPAScalingPolicy>>

policies is a list of potential scaling polices which can be used during scaling. If not set, use the default values: - For scale up: allow doubling the number of pods, or an absolute change of 4 pods in a 15s window. - For scale down: allow all pods to be removed in a 15s window.

select_policy: Option<String>

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

stabilization_window_seconds: Option<i32>

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).

tolerance: Option<Quantity>

tolerance is the tolerance on the ratio between the current and desired metric value under which no updates are made to the desired number of replicas (e.g. 0.01 for 1%). Must be greater than or equal to zero. If not set, the default cluster-wide tolerance is applied (by default 10%).

For example, if autoscaling is configured with a memory consumption target of 100Mi, and scale-down and scale-up tolerances of 5% and 1% respectively, scaling will be triggered when the actual consumption falls below 95Mi or exceeds 101Mi.

This is an alpha field and requires enabling the HPAConfigurableTolerance feature gate.

Trait Implementations

impl Clone for HPAScalingRules

fn clone(&self) -> HPAScalingRules

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for HPAScalingRules

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl DeepMerge for HPAScalingRules

fn merge_from(&mut self, other: Self)

Merge other into self.

impl Default for HPAScalingRules

fn default() -> HPAScalingRules

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for HPAScalingRules

fn deserialize<D>(deserializer: D) -> Result<Self, D::Error>

where D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl PartialEq for HPAScalingRules

fn eq(&self, other: &HPAScalingRules) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl Serialize for HPAScalingRules

fn serialize<S>(&self, serializer: S) -> Result<S::Ok, S::Error>

where S: Serializer,

Serialize this value into the given Serde serializer.

impl StructuralPartialEq for HPAScalingRules