Method and equipment for determining abnormity of business platform

Abstract

The invention discloses a method and equipment for determining abnormity of a business platform. The method comprises the steps that the business platform collects first type performance parameters, determines first characteristic information corresponding to the first type performance parameters and maintains the first characteristic information on the business platform; the business platform collects second type performance parameters, determines second characteristic information corresponding to the second type performance parameters and compares the first characteristic information and the second characteristic information; when the first characteristic information and the second characteristic information mutually satisfy a preset condition, the business platform determines that abnormity happens to the business platform. Otherwise, the business platform determines that no abnormity happens to the business platform. In the embodiment of the invention, whether abnormity happens to the business platform or not is accurately judged by comparing the first characteristic information corresponding to the first type performance parameters with the second characteristic information corresponding to the second type performance parameters, the unnecessary checking workload caused by false alarming is reduced for a user, and the redundant alarm data is reduced.

Description

technical field [0001] The invention relates to the technical field of communication, in particular to a method and equipment for determining abnormality of a service platform. Background technique [0002] With the complexity of various business platforms, the monitoring, analysis and abnormal alarm of the business platforms are becoming more and more important. In the prior art, when determining whether the service platform is abnormal, it is necessary to judge whether the performance parameter of the service platform is greater than the preset threshold. If the performance parameter of the service platform is greater than the preset threshold, it is considered that the service platform is abnormal. If the performance of the service platform If the parameter is not greater than the preset threshold, it is considered that there is no abnormality in the business platform. Assuming that the performance parameter is CPU (Center Process Unit, central processing unit) usage rat...

AI Technical Summary

Problems solved by technology

[0003] In the above implementation, the range of the preset threshold is difficult to determine and lacks flexibility. Since the preset threshold cannot be reasonably selected, the misjudgment rate is relatively high, that is, when the business platform does not have an abnormality, it is concluded that the business platform is abnormal.

For example, when the pressure on the business platform is relatively high, it will often cause the CPU usage to exceed the preset threshold of 80%. At this time, it will be concluded that the business platform is abnormal and an alarm will be issued, so that the alarm will be very frequent. This kind of error The alarm will bring a lot of unnecessary audit workload to the user, and at the same time make the real abnormal situation submerged in a lot of invalid information

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