...
One thing to notice is that our algorithm, for metrics that are very active, is designed to ignore deviations that lasted less than 8 minutes 3, to reduce alert fatigue, so very short anomalies will not be detected.
The Server Machine Dataset (SMD) contains several metrics for each machine and each machine data coming from several server machines. Each machine will be translated to a node in Eyer. For each machine there is a multivariate time series data (each variable is treated as a metric in Eyer). In the SMD the data are split in two: a train part and a test part. The train part is claimed to be anomaly free, while for the test part anomalies are labelled. Our alerting mechanism is packing the anomalies on all the metrics of a node a single alert, therefore we will test our algorithm in a multivariate way. An anomaly on a single metric is considered to be an anomaly for the full node.
...