Interface performance early warning method based on linear regression model and related equipment thereof

Abstract

The embodiment of the invention belongs to the technical field of big data, is applied to the field of smart government affairs, and relates to an interface performance early warning method based on a linear regression model and related equipment thereof. The interface performance early warning method comprises the steps of obtaining interface performance feature data of an API interface corresponding to each agent node of each distributed monitoring system based on a preset time window; performing statistics on the interface performance feature data of each API interface according to the dimensions of the data to obtain a target feature value of each dimension, and constructing a target linear regression model based on the target feature values; predicting an interface feature value of a next time window based on the target linear regression model; and judging whether the interface characteristic value exceeds a characteristic threshold value or not, and if the interface characteristic value exceeds the characteristic threshold value, executing an early warning operation to remind a developer to debug the API, wherein the target linear regression model can be stored in the block chain. According to the invention, the interface with potential performance reduction can be early warned in advance.

Description

technical field [0001] This application relates to the field of big data technology, in particular to an interface performance early warning method based on a linear regression model and related equipment. Background technique [0002] Performance testing is an important part of the entire testing life cycle, and it is also a very important non-functional characteristic of software products, which indicates the economic requirements of the software system for time, timeliness and system resources. It is also a concrete manifestation of software capabilities. For a software system, the faster it runs and takes up less system resources, the more stable the system will be, the better the user experience will be, and the higher the customer satisfaction will be; such software can enable the company to stand out in the fierce industry competition in a favorable position. [0003] Most of the current monitoring systems can collect and display data such as QPS (query rate per sec...

AI Technical Summary

Problems solved by technology

[0003] Most of the current monitoring systems can collect and display data such as QPS (query rate per second), response time, and business volume of the interface, but they cannot predict the performance at a certain point in the future

There are tens of thousands of interfaces in financial systems such as banks. It is a difficult problem to choose which interfaces to perform performance testing. At present, it is impossible to provide early warning for interfaces that may have performance problems. As a result, problems are only discovered when the interface reports an error, which affects the understanding of all parties. interface call

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