Research And Implementation Of A Private Cloud Management Platform Based On OpenStack

In recent years,with the rapid development and widespread adoption of cloud computing technology,more and more enterprises and individuals are building their own private clouds to meet their business needs.OpenStack,a mature open-source cloud computing platform,is popular among users due to its ease of use,scalability,flexibility,and ecological stability.However,as a commercial product,it still has some drawbacks,such as difficulties in early deployment,lack of cluster automation and scalability,and poor user experience.Against this backdrop,based on the OpenStack open-source cloud platform,this thesis studies and develops a private cloud management platform.The main work of the thesis includes: 1)secondary development using OpenStack’s API to implement the basic management functions of the platform;2)implementing user role-based permission verification and access control on top of the basic management functions,which verifies permissions before user operations reach the server-side,avoiding server errors caused by mistakes,and improving user experience and system security;3)improving OpenStack’s shortcomings in cluster scaling by realizing automatic batch expansion of computing and storage nodes in the cluster through the use of automated deployment scripts to address system resource shortages;4)providing resource integration functions,which reduces cluster resource use by integrating resources through virtual machine migration measures when demand decreases and a large number of nodes are under low load.The system also designs and implements a platform database to store various data information about system operation,reducing access to the OpenStack API,reducing request time,and improving system interaction performance.Finally,the developed private cloud management platform was tested for functionality and performance.The test results showed that the system’s user module,platform resource management module,and cluster scaling module can all be used normally.In terms of performance,it meets expectations and reduces physical machine consumption through its own resource integration strategy,improving resource utilization.