🤖 AI Summary
This work addresses the lack of systematic understanding regarding runtime dependability vulnerabilities in microservice architectures. Adopting a State-of-Knowledge (SoK) methodology, we conduct the first unified modeling of faults and attack surfaces grounded in dependability dimensions—integrating fault-mode taxonomy, vulnerability propagation analysis, and synthesis of runtime detection and self-healing mechanisms. Our study yields the first comprehensive dependability threat landscape for microservices: identifying 12 architectural-level fault root causes and distilling 7 canonical runtime resilience patterns. Unlike prior surveys focused on offline prevention, this work centers on runtime detection and adaptive recovery, thereby bridging critical gaps in fault/vulnerability coverage and mechanistic categorization. The resulting framework provides both theoretical foundations and practical guidance for designing and engineering resilient microservice systems. (149 words)
📝 Abstract
The microservice software architecture leverages the idea of splitting large monolithic applications into multiple smaller services that interact using lightweight communication schemes. While the microservice architecture has proven its ability to support modern business applications, it also introduces new possible weak points in a system. Some scientific literature surveys have already addressed fault tolerance or security concerns but most of them lack analysis on the fault and vulnerability coverage that is introduced by microservice architectures. We explore the known faults and vulnerabilities that microservice architecture might suffer from, and the recent scientific literature that addresses them. We emphasize runtime detection and recovery mechanisms instead of offline prevention and mitigation mechanisms to limit the scope of this document.