Service data monitoring method and system, monitoring architecture, equipment and storage medium

Abstract

The invention discloses a service data monitoring method and system, a monitoring architecture, equipment and a storage medium, and the method comprises the steps: monitoring a business message in real time, and obtaining business data according to the monitored business message, and comprises the steps: obtaining first business data corresponding to business execution request data transmitted bya first business subsystem in real time; acquiring recorded corresponding service execution request data from an associated service subsystem in real time to serve as third service data; acquiring second business data corresponding to the business processing operation completed by the associated business subsystem in real time; performing real-time check on the obtained service data to obtain a check result, including: performing real-time check on the first service data and the third service data to determine whether the first service data and the third service data are consistent; checking the second business data and the first business data in real time, and determining whether the two business data are consistent; and generating corresponding monitoring information based on the check result and outputting the monitoring information. By adopting the scheme, the real-time performance of consistency check of the service data can be improved, and accumulation of error data is reduced.

Description

technical field [0001] The embodiments of this specification relate to the field of data processing technology, and in particular to a business data monitoring method and system, a monitoring framework, equipment, and storage media. Background technique [0002] At present, in the O2O (Online To Offline, online to offline) industry, business processing systems usually include multiple business subsystems, and there are generally multiple business subsystems that process their corresponding business logic. Store their respective business data. There will be abnormal communication and abnormal business logic between business subsystems and between business subsystems and databases, which will lead to data inconsistency between business subsystems. Data inconsistency will cause certain impact or loss to the business. Data inconsistencies can be especially severe during peak business periods or in systems with high transaction volumes, sometimes resulting in serious financial ...

AI Technical Summary

Problems solved by technology

[0003] At present, the business data monitoring of the synchronous request method can run well, but for the monitoring of the business data involved in the asynchronous request, the business data consistency check method currently adopted usually takes a period of time to find the business data Inconsistencies, which leave time for the accumulation of erroneous data to occur

In addition, for transaction data, it also leaves time for the risk of capital loss to occur

Images