Resource estimation method and device of cloud platform, electronic equipment and storage medium

Abstract

The embodiment of the invention provides a resource estimation method and device for a cloud platform, the cloud platform is used for running a plurality of application programs, the cloud platform comprises a plurality of resource units, and each resource unit comprises a plurality of terminal devices; the method comprises the following steps: acquiring historical load monitoring data of each application program; calculating a resource usage curve of each application program in a preset period according to the historical load monitoring data, an elastic scaling strategy and the resource configuration information of each terminal device; for each resource unit, aggregating the resource usage curve of each application program corresponding to each resource unit to obtain a resource usage estimation curve; and estimating a resource usage interval of the cloud platform according to the resource usage estimation curve and a preset multiple. According to the embodiment of the invention, manual statistics of the resource capacity of each application program is avoided, the labor cost is reduced, and estimation of the resource capacity of the application program according to artificial experience is also avoided, so that the resource estimation accuracy of the cloud platform is improved.

Description

technical field [0001] The present invention relates to the technical field of the Internet, in particular to a cloud platform resource estimation method, device, electronic equipment and computer-readable storage medium. Background technique [0002] Elastic scaling is a commonly used method in cloud computing, which can automatically expand the capacity of the application program in the cloud platform during the peak period and automatically reduce the capacity during the low peak period, so as to ensure the stability of the application program and save the computing resources of the cloud platform. Due to the advantages of elastic scaling, on-demand use, and automatic scaling, it has become more and more widely used in recent years, and has gradually become a major product highlight and core capability of major cloud computing companies. Resource guarantee is the necessary basis for elastic scaling. Due to the long stocking cycle of physical servers, it is difficult to de...

AI Technical Summary

Problems solved by technology

[0006] The existing cloud platform resource estimation methods have problems such as low estimation accuracy and high cost of manual statistics. The details are as follows:

[0007] 1) Low accuracy rate: the cloud platform prepares goods according to the maximum resource usage of the application, but in fact, the business side of most applications will report the resource usage according to the redundancy of 2-3 times the actual usage, causing the cloud platform to hoard a large amount of redundant resources. spare resources, bear the cost of ineffectiveness

[0008] 2) The cost of manual statistics is high: the estimation of the resource capacity of the application needs to be evaluated by the person in charge of the application based on experience, which increases the cost of manual statistics on the one hand, and on the other hand, the accuracy of manual experience is difficult to guarantee, and it is difficult to cope with holidays and sudden traffic scenarios

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