Application system capacity expansion method, device and equipment

Abstract

The embodiment of the invention provides an application system capacity expansion method, device and equipment, and the method comprises the steps: carrying out the capacity expansion of a layer withthe highest priority in an application system if the prediction response time corresponding to a prediction service index value is judged to be greater than a preset time threshold value, wherein thepriority of each layer of the application system is related to the weight corresponding to each layer, and the weight corresponding to each layer is obtained according to a Logistic regression algorithm. According to the application system capacity expansion method, device and equipment provided by the embodiment of the invention, the weight is obtained according to the Logistic regression algorithm and then the priority of each layer of the application system is obtained, so that the corresponding priority can be obtained according to the influence degree of each layer on the response time. According to the method and the device, the capacity of the layer with the highest priority is expanded, the capacity of the application system can be accurately expanded under the condition that the application system is not transformed and a production system is not influenced, the maximization of the expansion effect is ensured, the method and the device are more accurate and higher in efficiency, and the stability of the system is not impacted.

Description

technical field [0001] The embodiments of the present invention relate to the field of business support, and more specifically, to a method, device and equipment for expanding the capacity of an application system. Background technique [0002] With the rapid development of computer technology, in order to ensure that the network system supports business growth stably, how to predict the change of business response time under the condition of known possible business growth, and how to accurately expand the system is an important problem that all major IT companies are committed to solving. . [0003] To solve this problem, the existing solution is: firstly, carry out monitoring and early warning, through real-time monitoring of changes in various indicators of the system, and use the experience of operation and maintenance personnel to judge whether the system needs to be expanded and how to expand it. Then perform a performance test, build a test system in equal proportion...

AI Technical Summary

Problems solved by technology

[0004] However, the existing solutions have the following defects: First, for the method of resource expansion through monitoring and early warning, since the threshold of early warning is obtained based on the experience of operation and maintenance personnel, there are cases of inaccuracy

And whether to expand or not is judged subjectively by the operation and maintenance personnel, or jointly discussed and decided by various experts. The judgment process consumes a lot of manpower

Secondly, regarding the method of evaluating the resources required by the production environment through the performance test of the test environment, due to the essential difference in the complexity of the test environment and the production environment, for example, the application will interact with many other applications in the production environment, while the test environment cannot be completely simulated. As a result, the test results have limited practical guidance

Thirdly, the method of full-link stress testing for production generally involves the transformation of the production system, and the stress testing is directly initiated on the production system, which will have an impact on the stability of the production system, and the pollution risk of real production data is also uncontrollable

The simulation of the stress test scenario is based on the future prediction of the operation and maintenance personnel, and there is a certain deviation from the actual situation

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