Electronic device, redis-based abnormal warning method and storage medium

Abstract

The electronic device, redis-based abnormality early warning method and storage medium proposed by the present invention generate corresponding preset type identification codes from service requests received by each service system within a preset period of time monitored, and The preset type identification code is stored as a unique key in a predetermined redis task queue, and the valid time corresponding to each unique key is set to form a predetermined redis task lock, and then the call is determined according to a predetermined exception analysis rule. Whether the unique key is abnormal, and send abnormal prompt information to a predetermined data monitoring platform after determining that there is abnormality. It can detect exceptions in time and improve the efficiency of exception handling.

Description

technical field [0001] The invention relates to the field of network communication, in particular to an electronic device, a redis-based abnormality early warning method and a storage medium. Background technique [0002] With the development of Internet communication technology, the normal operation of enterprises is increasingly dependent on the interaction of data between business systems, and abnormalities often occur in the process of data interaction, such as the abnormality of data acquisition failure caused by response delay, which leads to the failure of enterprises. Normal operations are affected. At present, a special data monitoring platform is set up within the enterprise to monitor the interaction of data, so that an early warning can be issued in time when an abnormality is found. However, due to the huge amount of data interaction within the enterprise every day, and the same business system may process multiple business requests at the same time, in practic...

AI Technical Summary

Problems solved by technology

However, due to the large amount of data interaction within the enterprise every day, and the same business system may process multiple business requests at the same time, in practical applications, it is difficult for the monitoring platform to find abnormalities in time, and it is necessary to rely on the data stored in the database. Business data is used to analyze the location of specific exceptions, resulting in the consumption of a large amount of database resources, affecting the performance of database applications, and poor real-time risk warning

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