AWS deploys machine learning based cost analysis

 

Cost control and governance are key issues for AWS deployments. Announced September 24th 2020.

Starting today, customers can use AWS Cost Anomaly Detection to detect unexpected or unusual spend.  AWS Cost Anomaly Detection uses a multi-layered state machine learning model that learns your unique spend patterns to adjust spend thresholds – this means you do not need to worry about determining appropriate thresholds (e.g. 10% increase in daily spend) and maintaining them as your usage changes over time. These machine learning layers allow Anomaly Detection to detect various types of anomalies, such as a one-time cost spike or gradual, consistent cost increases. Anomaly Detection is customizable to segment your spend data and provides tailored alerting preferences so that you are informed as soon as an anomaly is detected