Struct aws_sdk_iot::types::BehaviorCriteria

#[non_exhaustive]
pub struct BehaviorCriteria {
    pub comparison_operator: Option<ComparisonOperator>,
    pub value: Option<MetricValue>,
    pub duration_seconds: Option<i32>,
    pub consecutive_datapoints_to_alarm: Option<i32>,
    pub consecutive_datapoints_to_clear: Option<i32>,
    pub statistical_threshold: Option<StatisticalThreshold>,
    pub ml_detection_config: Option<MachineLearningDetectionConfig>,
}

The criteria by which the behavior is determined to be normal.

Fields (Non-exhaustive)

Non-exhaustive structs could have additional fields added in future. Therefore, non-exhaustive structs cannot be constructed in external crates using the traditional Struct { .. } syntax; cannot be matched against without a wildcard ..; and struct update syntax will not work.

comparison_operator: Option<ComparisonOperator>

The operator that relates the thing measured (metric) to the criteria (containing a value or statisticalThreshold). Valid operators include:

• string-list: in-set and not-in-set

• number-list: in-set and not-in-set

• ip-address-list: in-cidr-set and not-in-cidr-set

• number: less-than, less-than-equals, greater-than, and greater-than-equals

value: Option<MetricValue>

The value to be compared with the metric.

duration_seconds: Option<i32>

Use this to specify the time duration over which the behavior is evaluated, for those criteria that have a time dimension (for example, NUM_MESSAGES_SENT). For a statisticalThreshhold metric comparison, measurements from all devices are accumulated over this time duration before being used to calculate percentiles, and later, measurements from an individual device are also accumulated over this time duration before being given a percentile rank. Cannot be used with list-based metric datatypes.

consecutive_datapoints_to_alarm: Option<i32>

If a device is in violation of the behavior for the specified number of consecutive datapoints, an alarm occurs. If not specified, the default is 1.

consecutive_datapoints_to_clear: Option<i32>

If an alarm has occurred and the offending device is no longer in violation of the behavior for the specified number of consecutive datapoints, the alarm is cleared. If not specified, the default is 1.

statistical_threshold: Option<StatisticalThreshold>

A statistical ranking (percentile)that indicates a threshold value by which a behavior is determined to be in compliance or in violation of the behavior.

ml_detection_config: Option<MachineLearningDetectionConfig>

The configuration of an ML Detect

Implementations

impl BehaviorCriteria

pub fn comparison_operator(&self) -> Option<&ComparisonOperator>

The operator that relates the thing measured (metric) to the criteria (containing a value or statisticalThreshold). Valid operators include:

• string-list: in-set and not-in-set

• number-list: in-set and not-in-set

• ip-address-list: in-cidr-set and not-in-cidr-set

• number: less-than, less-than-equals, greater-than, and greater-than-equals

pub fn value(&self) -> Option<&MetricValue>

The value to be compared with the metric.

pub fn duration_seconds(&self) -> Option<i32>

Use this to specify the time duration over which the behavior is evaluated, for those criteria that have a time dimension (for example, NUM_MESSAGES_SENT). For a statisticalThreshhold metric comparison, measurements from all devices are accumulated over this time duration before being used to calculate percentiles, and later, measurements from an individual device are also accumulated over this time duration before being given a percentile rank. Cannot be used with list-based metric datatypes.

pub fn consecutive_datapoints_to_alarm(&self) -> Option<i32>

If a device is in violation of the behavior for the specified number of consecutive datapoints, an alarm occurs. If not specified, the default is 1.

pub fn consecutive_datapoints_to_clear(&self) -> Option<i32>

If an alarm has occurred and the offending device is no longer in violation of the behavior for the specified number of consecutive datapoints, the alarm is cleared. If not specified, the default is 1.

pub fn statistical_threshold(&self) -> Option<&StatisticalThreshold>

A statistical ranking (percentile)that indicates a threshold value by which a behavior is determined to be in compliance or in violation of the behavior.

pub fn ml_detection_config(&self) -> Option<&MachineLearningDetectionConfig>

The configuration of an ML Detect

impl BehaviorCriteria

pub fn builder() -> BehaviorCriteriaBuilder

Creates a new builder-style object to manufacture BehaviorCriteria.

Trait Implementations

impl Clone for BehaviorCriteria

fn clone(&self) -> BehaviorCriteria

Returns a copy of the value.

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

Performs copy-assignment from source.

impl Debug for BehaviorCriteria

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

Formats the value using the given formatter.

impl PartialEq for BehaviorCriteria

fn eq(&self, other: &BehaviorCriteria) -> 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 StructuralPartialEq for BehaviorCriteria