Design And Implementation Of Measurement And Risk Detection System For DevOps Software Process

DevOps realizes the standard unification of software R&D(Research & Development)and operation process,strengthens the management of the full cycle of application R&D and operation,breaks down departmental barriers,improves and optimizes the whole process from application requirements to production and operation and maintenance,and combines unified toolchain to achieve the consistency of culture,process and tools improve the overall collaborative efficiency of digital application innovation,and improve the efficiency of software delivery.DevOps transformation is the only way for enterprises to digitally transform,and DevOps process measurement is an indispensable practice for practicing DevOps,and it is also the practice that management attaches the most importance to.Measurement is not an end,but a means.The goal of measurement is ”doing the right thing”,and the means of measurement is ”doing well”.After in-depth research on several successful DevOps practices,this thesis implements a DevOps software process-oriented measurement and risk detection system,which converges the fragmented software development process into one platform,and realizes process monitoring,warning,and monitoring of the entire software development process and risk prediction feedback.The system is divided into three modules: data acquisition module,metrics visualization module,and risk feedback module.The data acquisition module acquires and calculates metric data through a large number of engineered and modular Python scripts,providing a data basis for the operation of the metric system.,The metrics visualization module realizes the visual display of measurement data through the Echarts.js third-party library.The system has a huge amount of data,flexible chart configuration,and customization.The risk feedback module realizes the monitoring of measurement data by establishing an indicator alert system,and timely feedback on the changes of metrics data to users.Risk monitoring helps the relevant person in charge to find out the goal and direction of the project optimization.The system has been running in a stable state since delivery,the metrics data is updated promptly,and the user feedback is good and effective to help the relevant person predict risk factors,control the progress of the project,find out the optimization goals,reasonably adjust the work arrangement,and promote the timely and high-quality delivery of the project.