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

Abstract

A business data monitoring method and system, monitoring architecture, equipment, and storage medium, the method comprising: monitoring business messages in real time, and acquiring business data according to the monitored business messages, including: acquiring in real time a business execution request sent by the first business subsystem The first business data corresponding to the data; obtain the corresponding business execution request data recorded in real time from the associated business subsystem as the third business data; obtain the second business data corresponding to the business processing operation completed by the associated business subsystem in real time; Real-time verification of the business data to obtain the verification results, including: real-time verification of the first business data and the third business data to determine whether they are consistent; real-time verification of the second business data and the first business data to determine whether they are consistent; Check the results to generate corresponding monitoring information and output. Adopting the above solution can improve the real-time performance of business data consistency check and reduce the accumulation of wrong data.

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

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