ANOMALY DETECTION AND CLASSIFICATION USING TELEMETRY DATA

Historical telemetry data can be used to generate predictions for various classes of data at various aggregates of a system that implements an online service. An anomaly detection process can then be utilized to detect anomalies for a class of data at a selected aggregate. An example anomaly detecti...

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Bibliographic Details
Main Authors BARNES, Christopher, NALLABOTHULA, Kiran, PALLA, Nagaraju, PATIL, Nagaraj
Format Patent
LanguageEnglish
Published 18.04.2019
Subjects
ELECTRIC COMMUNICATION TECHNIQUE
ELECTRICITY
TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHICCOMMUNICATION
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Summary:Historical telemetry data can be used to generate predictions for various classes of data at various aggregates of a system that implements an online service. An anomaly detection process can then be utilized to detect anomalies for a class of data at a selected aggregate. An example anomaly detection process includes receiving telemetry data originating from a plurality of client devices, selecting a class of data from the telemetry data, converting the class of data to a set of metrics, aggregating the set of metrics according to a component of interest to obtain values of aggregated metrics over time for the component of interest, determining a prediction error by comparing the values of the aggregated metrics to a prediction, detecting an anomaly based at least in part on the prediction error, and transmitting an alert message of the anomaly to a receiving entity.
Bibliography:Application Number: US201816219221