Service exception detection method and device, electronic equipment and storage equipment

Abstract

The invention discloses a service exception detection method. The method comprises the steps of: obtaining first data, wherein the first data comprises historical business data; obtaining a baseline containing the future trend of the service data according to the first data; and predicting whether the current service point is an abnormal point at least according to the baseline. By adopting the method, the problem of false alarm of service detection is solved.

Description

technical field [0001] The present application relates to the technical field of business monitoring, and specifically relates to a business anomaly detection method, device, electronic equipment and storage equipment. Background technique [0002] In the field of anomaly detection, the existing method is to manually sort out expert knowledge to set a static threshold for alarming. First, create a business scenario that describes the occurrence of an exception. In this scenario, qualitatively describe the time when the exception occurs and set the value of the business exception index. When a new business data appears, anomaly detection is performed by comparing the current business data with the preset business anomaly index value. [0003] In the anomaly detection method provided by the existing technology, when manually setting the threshold, only the rising and falling trend curves of the current time interval (for example, 5 minutes) can be seen, and the periodicity an...

AI Technical Summary

Problems solved by technology

[0004] This application provides a business anomaly detection method, device, electronic equipment, and storage device to solve the problem of false alarms in existing business anomaly detection

Images