6 papers
Beyond Fault Localization: A Trajectory-Level Study of LLM Agents for Microservice Root Cause Analysis
Qisheng Lu, Aoyang Fang, Junjielong Xu +5
Existing evaluations of automated root cause analysis (RCA) for microservices assess diagnostic performance mainly by endpoint correctness: whether a method localizes the responsib…
OpenRCA 2.0: From Outcome Labels to Causal Process Supervision
Aoyang Fang, Yifan Yang, Jin'ao Shang +7
Root cause analysis (RCA) poses a holistic test of LLM agentic capabilities, such as long-context understanding, multi-step reasoning, and tool use. However, existing datasets suff…
Gleaner: A Semantically-Rich and Efficient Online Sampler for Microservice Diagnostics
Yifan Yang, Aoyang FANG, Songhan Zhang +1
Distributed tracing in microservices is critical for diagnostics but generates overwhelming data volumes, necessitating intelligent sampling. To maximize fidelity, state-of-the-art…
Rethinking the Evaluation of Microservice RCA with a Fault Propagation-Aware Benchmark
Aoyang Fang, Songhan Zhang, Yifan Yang +7
While cloud-native microservice architectures have revolutionized software development, their inherent operational complexity makes failure Root Cause Analysis (RCA) a critical yet…
DynaCausal: Dynamic Causality-Aware Root Cause Analysis for Distributed Microservices
Songhan Zhang, Aoyang Fang, Yifan Yang +3
Cloud-native microservices enable rapid iteration and scalable deployment but also create complex, fast-evolving dependencies that challenge reliable diagnosis. Existing root cause…
A Goal-Driven Survey on Root Cause Analysis
Aoyang Fang, Haowen Yang, Haoze Dong +3
Root Cause Analysis (RCA) is a crucial aspect of incident management in large-scale cloud services. While the term root cause analysis or RCA has been widely used, different studie…