Research on the Method of Combining and Compressing Alarm Messages in Multiple Microserver Applications

Aiming at the operation and maintenance pressure caused by frequent alarms for multiple servers and the problem of delayed or even missed core alarms, this paper proposes a merging and compression method of alarm information based on the improved Apriori algorithm. The method completes the merging and compression of alarm information through three steps of historical alarm information capture, model training and data validation test, optimizes the confidence calculation of traditional Apriori algorithm, and solves the distortion problem of confidence calculation caused by frequent alarm items. Experiments show that this method effectively merges and compresses alarm information, reduces the pressure of operation and maintenance, improves the emergency operation and maintenance capability, shortens the service recovery time, and achieves significant results in alarm compression and root cause analysis processing. This study provides technical support for the root cause localization of massive alarm information faults, and is of guiding significance for the prediction and merging display of the number of alarms in the future.