AWS AWSCloudFormation documentation change
Summary
Added detailed configuration documentation for Random Cut Forest algorithm including query requirements and sampling parameters
Security assessment
Provides operational guidance for algorithm configuration without addressing authentication, authorization, data protection, or security vulnerabilities
Diff
diff --git a/AWSCloudFormation/latest/TemplateReference/aws-properties-aps-anomalydetector-randomcutforestconfiguration.md b/AWSCloudFormation/latest/TemplateReference/aws-properties-aps-anomalydetector-randomcutforestconfiguration.md index a5638dda5..a242d9ff5 100644 --- a//AWSCloudFormation/latest/TemplateReference/aws-properties-aps-anomalydetector-randomcutforestconfiguration.md +++ b//AWSCloudFormation/latest/TemplateReference/aws-properties-aps-anomalydetector-randomcutforestconfiguration.md @@ -9 +9 @@ This is the new _AWS CloudFormation Template Reference Guide_. Please update you -The `RandomCutForestConfiguration` property type specifies Property description not available. for an [AWS::APS::AnomalyDetector](./aws-resource-aps-anomalydetector.html). +Configuration for the Random Cut Forest algorithm used for anomaly detection in time-series data. @@ -44 +44 @@ To declare this entity in your AWS CloudFormation template, use the following sy -Property description not available. +Configuration for ignoring values that are near expected values from above during anomaly detection. @@ -55 +55 @@ _Required_ : No -Property description not available. +Configuration for ignoring values that are near expected values from below during anomaly detection. @@ -66 +66,7 @@ _Required_ : No -Property description not available. +The Prometheus query used to retrieve the time-series data for anomaly detection. + +###### Important + +Random Cut Forest queries must be wrapped by a supported PromQL aggregation operator. For more information, see [Aggregation operators](https://prometheus.io/docs/prometheus/latest/querying/operators/#aggregation-operators) on the _Prometheus docs_ website. + +**Supported PromQL aggregation operators** : `avg`, `count`, `group`, `max`, `min`, `quantile`, `stddev`, `stdvar`, and `sum`. @@ -79 +85 @@ _Required_ : Yes -Property description not available. +The number of data points sampled from the input stream for the Random Cut Forest algorithm. The default number is 256 consecutive data points. @@ -94 +100 @@ _Required_ : No -Property description not available. +The number of consecutive data points used to create a shingle for the Random Cut Forest algorithm. The default number is 8 consecutive data points.