Anomaly
AWS Cost Anomaly Detection leverages advanced Machine Learning technologies to identify anomalous spend and root causes, so you can quickly take action. You can use Cost Anomaly Detection by creating monitor.
Example Usage
Example
No Java example available.
Example
No Java example available.
Example
No Java example available.
Example
No Java example available.
Example
No Java example available.
Example
No Java example available.
Example
No Java example available.
Example
No Java example available.
Example
No Java example available.
Example
No Java example available.
Example
No Java example available.
Example
No Java example available.
Properties
The date when the monitor was created.
The value for evaluated dimensions.
The date when the monitor last evaluated for anomalies.
The date when the monitor was last updated.
The Amazon Resource Name (ARN) value for the monitor.
The dimensions to evaluate
The name of the monitor.
The array of MonitorSpecification in JSON array format. For instance, you can use MonitorSpecification to specify a tag, Cost Category, or linked account for your custom anomaly monitor. For further information, see the Examples section of this page.
The possible type values.
Tags to assign to monitor.