Research And Implementation Of Adaptive Traffic Control And Fault Root Cause Localization Mechanisms Of Microservices

With the increasing dynamism and complexity of Internet applications,traditional monolithic software architectures have become difficult to adapt the rapid changes for user requirements.More and more software systems are adopting a modular approach to decompose large applications into smaller,more independent,and easier-to-manage microservices,thereby improving system scalability,flexibility,and maintainability.However,the uncontrollable access traffic and the complex network environment make the service face failure risks such as traffic overload and cascading failures.The existing traffic control methods have problems such as untimely response,single application scenarios,and inability to secure critical service requests.In addition,when service failure occurs,it is difficult to locate the root cause of service failure accurately due to the increase of service scale,dependency,and complexity.The existing approaches ignore the impact of service dynamic dependency and protection mechanism on the probability of anomaly propagation,resulting in inaccurate root cause localization results.This paper focuses on how to guarantee the stability and reliability of services in dynamic microservice scenarios.Firstly,considering the risks of abnormal access and traffic overload on the line services,this paper proposes an adaptive dynamic circuit breaking mechanism based on the overload protection policy,which dynamically adjusts the sensitivity of the circuit breaker to quickly respond to service abnormalities by fine-grained monitoring of network conditions and service conditions,and designs an adaptive multi-level traffic limiting mechanism based on the leaky bucket algorithm,which provides hierarchical traffic control for services according to the service conditions and system load conditions.It is carried out to prioritize the success probability of key service requests,reduce service resource consumption,and guarantee service quality.Secondly,in order to quickly and accurately locate the root cause when service failure occurs,this paper proposes a graph-based service failure root cause localization mechanism.The mechanism dynamically constructs a service attribute graph using service metrics and traces,adopts a two-stage dynamic correction strategy to eliminate the influence of protection mechanisms on the probability of anomaly propagation,and locates the root cause of service failure based on a random walk method.Finally,this paper designs and implements an intelligent operation and maintenance management system for microservices based on the open-source technologies such as Kubernetes,integrates service adaptive traffic control and fault root cause localization modules,and conducts system function and performance verification.Experiments show that the approaches proposed in this paper can effectively reduce service resource consumption,guarantee the quality of critical service requests,and improve the accuracy of service fault root cause localization.