Design And Implementation Of Work Order Acceptance System Based On Microservice Architecture

With the rapid development of information technology,the way companies solve customer problems has gradually shifted from offline to online.From the customer needs to find the company's offline service center,to the customer,only a call can be directly connected to the enterprise customer service center.The company's service approach has undergone a huge change.Professional customer service to solve or circulate corresponding customer problems can not only solve customer problems quickly,improve the service image of the enterprise,but also lay a solid foundation for the future business development of the enterprise.By analyzing the demand of the work order system of the sports lottery customer service call center,a work order processing system based on a microservice architecture is constructed in the article.This article mainly explains and implements the five modules of incoming call management,outgoing call management,permission management,questionnaire management,and customer management.The system is implemented using software development methods such as the Spring Cloud distributed system framework and Redis.The service deployment methods of cluster services and master-slave services were adopted.The Docker platform technology was used to configure the system's operating environment,and the JMeter stress test tool was used to test the system's high-availability aspects during the test.Strongly expandable work order system.At the same time,the system uses the Word2 vec module in Python to construct a short text keyword extraction method,exposes the service API,and registers it with the service registration center for use by the work order acceptance system,improving the agent's tagging of work orders.s efficiency.Aiming at the research of software development architecture and work order text data,the article designs and implements the system stability and high availability.The results show that in the cluster mode and the master-slave service mode,the system's fault tolerance and self-recovery performance are good,and the single machine failure problem of the work order system is solved.Under the balanced routing of requests by intelligent routing,compared to the stand-alone architecture mode,the average request response time of the microservices cluster deployment mode is reduced by 36%,and the system throughput is increased by 64%.The use of the Docker platform improves the efficiency of system test environment setup and deployment,saving time and hardware resource costs during system development and test environment setup.The use of the keyword extraction additional function also makes it easier and clearer for the agent to obtain the core points of the work order when tagging the work order,which improves the work efficiency.