Research On Microservices Quality Management In Big Data Environment

In recent years,with the rapid development of Internet+,Big Data,AI,IOT,Cloud Computing and mobile payment technology,the scale of data is increasing exponentially.The era of Big Data has long arrived and has penetrated into everyone's life.At the same time,with the rapid expansion of major Internet companies,their system scale is becoming more and more bloated.In order to cope with the rapid changes in the market environment,the Microservices of major systems has become an inevitable trend.Major Internet giants,including Ali,JD,Facebook and Twitter,have actively launched their own practices in the field of Microservices.However,with the popularization of large data technology and Microservices architecture,the complexity of related systems is increasing day by day.How to effectively maintain the quality of systems has gradually become a hot topic it the industry.Microservices system in Big Data environment belongs to a subdivision field of software system,which inherits many characteristics of traditional software quality.On the other hand,Microservices in Big Data environment also have some characteristics different from traditional software systems,such as complex system environment,fast and independent iteration of Microservices,failure of Microservices quality caused by upstream and downstream services and abnormal data sources,and the small size of Microservices teams and difficult to accept tedious process management processes.Such as the above characteristics,leading to Microservices can not copy the traditional software system quality management model,need to try to get a small and refined quality management model suitable for their own.Firstly,this paper combs the relevant theoretical knowledge needed by the research.Then,taking J company's recommendation system as an example,this paper sorted out the common quality problems of Microservices system in Big Data environment,and summarized the core causes of failure in such scenarios.On this basis,combining the knowledge of CMMI,PDCA,Big Data,Microservices,QoS,SOA Governance and other fields,this paper puts forward a process management model with fault-oriented optimization as the core idea,and points out that the quality management of Microservices in Big Data environment should focus on the four elements of fault prevention,detection,stop and recovery.After that,according to the actual work situation,the corresponding practice scheme was formulated,and the model was applied to the recommender system management practice of J Company,and achieved good practice results,which significantly improved the service quality of Microservices under the recommender system.