Establishment method of SaaS software deployment scheme supporting performance analysis

Abstract

The invention discloses an establishment method of a SaaS software deployment scheme supporting performance analysis. A deployment environment, a deployment object, a deployment plan and deployment constraints are defined; the deployment environment describes hardware nodes and the resource supply situation which can be provided by a physical environment, including communication capability of virtual machines; the deployment object describes SaaS software to be deployed, the resource demand of the software and service call information in the SaaS software, including basic services and composite services; the deployment plan describes the deployment situations and configuration parameters of the services in the SaaS software on the hardware nodes and comprises multiple deployment units, wherein each deployment unit consists of one virtual machine embodiment and multiple basic service embodiments. The deployment constraints describe various limiting conditions the deployment plan should abide by due to the demands for service technologies, reliability, safety, high efficiency and the like. The establishment method is applicable to the dynamic changing deployment environment and provides necessary information for performance analysis of the SaaS software.

Description

technical field [0001] The invention belongs to the technical field of software deployment and performance analysis, and in particular relates to a method for constructing a SaaS software deployment solution supporting performance analysis. Background technique [0002] SaaS (Software as a Service, software as a service) provides software through cloud services distributed in the Internet. However, SaaS software will experience performance degradation after running for a long time. With the increase of the number of users and the change of the system environment, the existing deployment scheme and the number of resources cannot meet the current software requirements, and the performance and quality of the software will be seriously degraded, such as : (1) When there are many user requests, the service request calls will be queued, prolonging the service response time, or even exceeding the threshold; (2) When the hardware node fails, the request load exceeds the processing...

AI Technical Summary

Problems solved by technology

At present, some researchers have proposed a software resource configuration meta-model for service deployment, including software configuration parameter information and the constraint relationship between parameters, and given a verification rule set and verification algorithm to detect configuration conflicts, that is, whether the deployment is satisfied Constraint relationships, but only focus on deployment co...

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