Root-Cause Analysis and Fine Tuning for Run-Time Quality Issues in Transboundary Services

In order to solve the quality issues caused by the status change of the internal elements as well as the external environment while transboundary service system is running, this paper proposes a root-cause analysis and fine tuning method for the run-Time quality issues of transboundary services. After receiving feedback on the run-Time quality issues, this method first built a causal diagram model for root-cause analysis on the basis of a large amount of quality and capability data generated by the operation of transboundary service system, and then based on the constructed causal diagram model, locate the problematic quality/capability parameters by tracing back to the source of quality issues, and finally aiming at the problematic quality/capability configuration scheme, carry out fine tuning through the data mining method that combines data clustering with decision tree, so as to ensure the continuous and healthy operation of transboundary service system with the minimum tuning cost. Finally, the effectiveness and practicability of the method is verified through the case of the Rural taobao service.