Enterprise cloud service platform dynamic expansion method, device and system

Abstract

The invention discloses a dynamic enterprise cloud service platform expansion method which comprises the following steps: acquiring the operation volume of each operation request of each enterprise user in a first server and / or the frequency of the operation request of each enterprise user in the duration period; judging whether the operation volume of each operation request of each enterprise user in the first server and / or the frequency of the operation request of each enterprise user in the duration period exceed (s)a preset threshold value; distributing a subsequent operation request of the enterprise user into a second server if the frequency of the operation request of the enterprise user in the first server and / or the operation volume each time are (is) judged to exceed the preset threshold value. According to the dynamic enterprise cloud service platform expansion method, device and system, normal operations can be maintained by server clusters in reasonable quantity, the enterprises can be dynamically distributed into standby server clusters, and normal use of the rest enterprise users is not influenced when high performance response speed of the complicated request is guaranteed.

Description

technical field [0001] The invention relates to a method, device and system for dynamically expanding the capacity of an enterprise cloud service platform. Background technique [0002] When a cloud computing-based enterprise service platform provides enterprise services for enterprise users, it generally uses cloud server clusters to centrally process all enterprise requests. The data operation request of each enterprise will be randomly sent to a server in the cluster for processing. Since each enterprise served by the cloud service platform is different in size, use time and method, when some enterprises have complex computing requests in certain uncertain or specific time periods, the computing resources of the corresponding servers will be consumed. Thus, the calculation speed of other enterprises using the corresponding server at the same time is affected. In the prior art, the following solutions are generally adopted to solve the above problems: 1. Purchase a large...

AI Technical Summary

Problems solved by technology

Since each enterprise served by the cloud service platform is different in size, use time and method, when some enterprises have complex computing requests in certain uncertain or specific time periods, the computing resources of the corresponding servers will be consumed. Thus affecting the computing speed of other enterprises using the corresponding server at the same time

In the prior art, the following solutions are generally adopted to solve the above problems: 1. Purchase a large number of servers to form a cluster. This method will bring a lot of cost to the enterprise service platform. When the request volume is very low, a large number of idle servers will be generated. machine, causing a lot of waste

2. Each enterprise deploys its own private cloud server. In this way, the computing power of the server that each enterprise can enjoy is reduced. Although its own complex requests will not affect others, it is the computing performance of the private cloud server and the cloud server cluster. In comparison, the performance is greatly reduced, and the processing speed of complex requests is greatly reduced

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