US 11,675,646 B2
Systems, apparatuses, and methods for anomaly detection
Jan Gasthaus, Munich (DE); Mohamed El Fadhel Ayed, Berlin (DE); Lorenzo Stella, Berlin (DE); and Tim Januschowski, Berlin (DE)
Assigned to Amazon Technologies, Inc., Seattle, WA (US)
Filed by Amazon Technologies, Inc., Seattle, WA (US)
Filed on Jun. 25, 2020, as Appl. No. 16/912,312.
Prior Publication US 2021/0406671 A1, Dec. 30, 2021
Int. Cl. G06F 11/07 (2006.01); G06F 16/23 (2019.01); G06F 40/20 (2020.01); G06F 11/22 (2006.01)
CPC G06F 11/079 (2013.01) [G06F 11/0793 (2013.01); G06F 11/2263 (2013.01); G06F 16/2379 (2019.01); G06F 40/20 (2020.01)] 20 Claims
OG exemplary drawing
 
1. A computer-implemented method comprising:
receiving, at an anomaly detection service in a multi-tenant provider network, a request to monitor for anomalies from one or more data sources;
analyzing, by an anomaly detection component of the anomaly detection service, time-series data from the one or more data sources by:
ingesting the time-series data from the one or more data sources, wherein the time-series data is time-stamped and has at least one value, and
determining there is an anomaly in the time-series data using at least one distributional time series model by:
dividing a domain space into a plurality of bins using an approximation,
predicting a probability of a value being in one of the plurality of bins using a recurrent neural network, and
performing anomaly detection using the probability and the bins;
generating, by a findings detection service of the anomaly detection service, a recommendation for handling the anomaly, the recommendation generated by performing one or more of a root cause analysis, a heuristic analysis, and an incident similarity analysis; and
reporting, by a findings service in the multi-tenant provider network, the anomaly and the recommendation to a user.