Design And Implementation Of Data Center System Based On Distributed Architecture

As the business scope of enterprises and governments expands,the amount of data they have grows exponentially.When the data reaches a certain scale,how to manage these huge and messy data,play the value of the data,improve the quality of service,reduce operating costs,so as to quickly respond to user needs,has become a problem that must be considered.At the same time,many large enterprises have designed a set of middleware systems that fit their own organizational structure and business characteristics,and precisely because of the high coupling with business,the same model cannot be transplanted to other enterprises or organizations,so it is not universal.In order to improve the efficiency of managing heterogeneous data from multiple sources,to solve the problems of inconsistent data standards,diverse and heterogeneous data sources,and poor data quality in the traditional chimney business model,and to provide feedback to business through data services,this thesis designs and implements a data middleware system with the help of cutting-edge data governance ideas and excellent microservice architecture technology.The system is divided into five functional modules:data aggregation,data assets,data quality,data security,and data services.In order to ensure the scalability,performance,and development efficiency of the system,the system adopts a front and back-end separation architecture.The view layer directly facing the user is implemented using Vue framework,the server side using Spring Cloud to build the overall framework,and using Spring Boot to implement specific microservices,the database layer using Mysql and Redis,and the implementation process using Spring Cloud ecology of some excellent open source components such as Feign,Hystrix,etc.to improve the system,while the use of Docker container technology to complete the project deployment.The system is suitable for enterprises or government departments that have data governance-related needs,as it is highly versatile and not strongly related to business.After rigorous testing,the system meets user requirements in various aspects such as data aggregation,management,service and security,as well as system performance,and can be of great value in the direction of data governance.