公开(公告)号：US12265446B1

公开(公告)日：2025-04-01

申请号：US17031705

申请日：2020-09-24

Applicant: Amazon Technologies, Inc.

Inventor： Laurent Callot ,  Alexander Zimin ,  Paul M. Vazquez ,  Nam Khanh Tran

IPC: G06F11/07 ,  G05B23/02 ,  G06F9/451 ,  G06N20/20

Abstract: A determination is made that anomaly analysis is to be performed with respect to an application. An anomaly score of the application is generated with respect to observed values of a plurality of metrics of the application. Generation of the anomaly score comprises computing an anomaly score contribution associated with an analysis of a correlation between values of a pair of metrics of the application. In response to a detection that the anomaly score exceeds a threshold, an anomaly response operation is initiated.

公开(公告)号：US11269718B1

公开(公告)日：2022-03-08

申请号：US16915993

申请日：2020-06-29

Applicant: Amazon Technologies, Inc.

Inventor： Qijia Chen ,  Alexander Zimin ,  Nam Khanh Tran ,  Paul M. Vazquez ,  Laurent Callot ,  Meredith Paige Kiessling ,  Joel Dan Castellon Arevalo

IPC: G06F11/07 ,  G06F11/34 ,  G06F9/54 ,  G06F11/30

Abstract: Methods, systems, and computer-readable media for automatically detecting root causes of anomalies occurring in information technology (IT) systems are disclosed. In some embodiments, data of a service graph depicting dependencies between nodes or services of the IT infrastructure is traversed to determine propagation patterns of anomaly symptoms/alarms through the IT infrastructure. Also, a causal inference model is used to determine probabilities that an observed propagation pattern corresponds to a stored propagation pattern, wherein a close correspondence indicates that the current anomaly is likely caused by a similar root cause as a past anomaly that caused the stored propagation pattern.