Cloud computing hides the huge possibility of development. It has developed rapidly in recent years. With the development of domestic cloud computing technology, cloud computing technology has become a technology of widespread concern. This research mainly discusses the design of an automated deployment system for computer program applications based on cloud computing. In order to meet the potential load conditions, computer servers usually reserve enough resources for the maximum load, which will greatly reduce resource utilization. At the same time, the server load will be monitored in real time. According to a specific capacity expansion strategy, the capacity expansion operation will be triggered in time to increase or decrease the number of back-end virtual servers to ensure the service quality of the application and increase the resource utilization rate of the server. The allocation strategy of the deployment system adopts a configurable and customizable method, which greatly improves the flexibility of the system. With the goal of expanding component-based computer program applications, format the deployment problem of component-based computer program applications, optimize deployment efficiency based on dynamic scaling algorithms, and design simulation experiments to verify the feasibility of the algorithm. Compared with previous data centers, the success rate of cloud data centers has exceeded 87%. The research results show that the deployment system can meet the specific application requirements of users, and can be properly installed and deployed in some existing systems, and can obtain better scalability according to the particularity of the cloud computing environment.

云计算隐藏了巨大的发展可能性。近年来，它发展迅速。随着国内云计算技术的发展，云计算技术已经成为广泛关注的技术。本研究主要讨论基于云计算的计算机程序应用程序自动部署系统的设计。为了满足潜在的负载条件，计算机服务器通常为最大负载保留足够的资源，这将大大降低资源利用率。同时，将实时监视服务器负载。根据具体的产能扩展策略，将及时触发扩容操作，以增加或减少后端虚拟服务器的数量，以确保应用程序的服务质量，并提高服务器的资源利用率。部署系统的分配策略采用可配置，可定制的方法，大大提高了系统的灵活性。为了扩展基于组件的计算机程序应用程序，格式化基于组件的计算机程序应用程序的部署问题，基于动态缩放算法优化部署效率，并设计仿真实验以验证该算法的可行性。与以前的数据中心相比，云数据中心的成功率已超过87％。