Graph-based trace analysis for microservice architecture understanding and problem diagnosis

Microservice systems are highly dynamic and complex. For such systems, operation engineers and developers highly rely on trace analysis to understand architectures and diagnose various problems such as service failures and quality degradation. However, the huge number of traces produced at runtime makes it challenging to capture the required information in real-time. To address the faced challenges, in this paper, we propose a graph-based microservice trace analysis approach GMTA for understanding architecture and diagnosing various problems. Built on a graph-based representation, GMTA includes efficient processing of traces produced on the fly. It abstracts traces into different paths and further groups them into business flows. To support various analytical applications, GMTA includes an efficient storage and access mechanism by combining a graph database and a real-time analytics database and using a carefully designed storage structure. Based on GMTA, we construct analytical applications for architecture understanding and problem diagnosis, these applications support various needs such as visualizing service dependencies, making architectural decisions, analyzing the changes of services behaviors, detecting performance issues, and locating root causes. GMTA has been implemented and deployed in eBay. An experimental study based on trace data produced by eBay demonstrates GMTA's effectiveness and efficiency for architecture understanding and problem diagnosis. Case studies conducted in eBay's monitoring team and Site Reliability Engineering (SRE) team further confirm GMTA's substantial benefits in industrial-scale microservice systems.