How does Amazon Lookout for Metrics work?
In this section, you will learn how Amazon Lookout for Metrics works by first looking at the different concepts manipulated by the service. You will then dive deeper into how these concepts are orchestrated together to build detectors (this is what Lookout for Metrics calls its anomaly detection models). This section will then end with an overview of the pricing model used by this service.
Key concept definitions
To build models able to spot anomalies in your data, Amazon Lookout for Metrics uses the following concepts and resources:
- Detector: Amazon Lookout for Metrics trains ML models to detect outliers in your data. Such a model is called a detector in this service. A detector continuously learns from your data so that it gets better at understanding the normal behavior and any expected variability.
- Datasource: A datasource is a service that provides time series data that a detector can analyze. Each datasource must provide...