Cloud-native microservices architectures have become the dominant deployment paradigm for enterprise software systems, offering independent scalability, fault isolation, and continuous delivery capabilities. However, these architectural benefits introduce a distinct class of quality assurance challenges that traditional monolithic testing approaches cannot address: services interact through network boundaries that introduce latency and failure modes absent in-process, contracts between services must be validated independently of their runtime counterparts, and system-wide observability must be constructed from distributed telemetry rather than centralized instrumentation. This paper presents CQAMS - the Continuous Quality Assurance for Microservices framework - a structured methodology integrating service contract testing, fault tolerance validation through controlled chaos experimentation, and distributed observability as first-class quality gates within a CI/CD pipeline. CQAMS was developed and empirically evaluated on an eight-service research cluster deployed on a local Kubernetes environment using minikube, with fault injection experiments covering pod termination, inter-service network latency, and complete service outage scenarios. Results demonstrate that the framework detects service degradation patterns that evade conventional health check mechanisms and provides actionable diagnostic signals within the CI/CD feedback loop. CQAMS is designed to be tool-agnostic and applicable across a range of cloud-native infrastructure configurations.
Abhishek Nimdia (Mon,) studied this question.