Introducing outlier detection in Datadog

Datadog introduces outlier detection, a feature that automatically identifies any host or group of hosts behaving abnormally compared to their peers. This feature helps users monitor metrics without having to define ahead of time what constitutes "normal" versus "abnormal" values. Outlier detection can be used to alert when one machine starts reporting errors at an aberrant rate, identify the cause of latency spikes, and spot problem hosts on dashboards. The feature offers two algorithms for identifying outliers: DBSCAN (density-based spatial clustering of applications with noise) or MAD (median absolute deviation).