solution Use Case
Behavioral Anomaly Detection
Machine Learning

DataMiner Behavioral Anomaly Detection will alert you to data sources in your system that suddenly start to show unusual behavior. This could be a value that usually fluctuates and suddenly starts flatlining, a sudden upward or downward spike in a trend, an increase or decrease in the slope of a trend, and so on.
In this use case, we will show some examples of such anomalies: an increase in the temperature of a rack after a server has been removed, and a sudden drop in traffic of an internet exchange platform.
USE CASE DETAILS





docs.dataminer.services.
Our tutorial on detecting anomalies will show you step by step how you can configure your own system to detect anomalies, using example data downloaded from dataminer.services. And if you complete the tutorial, you can even earn some DevOps Points.