Machine Learning With Go

Anomaly detection

As mentioned in the introduction to this chapter, we might not always be interested in forecasting a time series. We might want to detect anomalous behavior in a time series. For example, we might want to know when out of the ordinary bursts of traffic come across our network, or we may want an alert when out of the ordinary numbers of users are attempting certain things inside of our application. These events could be tied to security concerns or may just be used to adjust our infrastructure or application settings.

Thankfully, due to Go's history of usage in monitoring and infrastructure, there are a variety of Go-based options to detect anomalies in time series data. This tooling has been used in production to detect ...