Anomaly detection

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Anomaly detection

Elementary uses "standard score", also known as "Z-score" for anomaly detection. This score represents the number of standard deviations of a value from the average of a set of values. 
According to the empirical rule, in a standard normal distribution:
~68% of values have an absolute z-score of 1 or less.
~95% of values have an absolute z-score of 2 or less.
~99.7% of values have an absolute z-score of 3 or less. 
Values with a standard score of 3 and above are considered outliers, and this is a recommended threshold for anomaly detection. 
This is the default Elementary uses as well, and it can be changed using the var  anomaly_score_threshold in the global configuration.

You can use the model anomaly_threshold_sensitivity to see if values of metrics from your last run would have been considered anomalies in different scores. This can help you decide if there is a need to adjust the sensitivity:
z_score_sensitiviy model sample
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Data monitors

Monitoring in production

Last modified 2mo ago

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