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Evidence record 4285 · automatically gathered

TopoEvo: A Topology-Aware Self-Evolving Multi-Agent Framework for Root Cause Analysis in Microservices

Root cause analysis (RCA) in microservices is challenging due to (i) noisy and heterogeneous multimodal observability (metrics, logs, traces), (ii) cascading failure propagation that amplifies downstream symptoms, and (iii) non-stationary topology drift induced by autoscaling and rolling updates. Recent LLM-based RCA agents can generate tool-grounded explanations, yet they often remain topology-agnostic and suffer from \emph{symptom-amplification bias}, misattributing the root cause to salient d

Record details

Published: 15 May 2026
Source: arXiv
Category: Research
Topics: Bias & fairness · Agents & autonomy
Retrieved: 14 July 2026

source-onlyevidence status

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How to cite this record

ethics.ai (15 May 2026), “TopoEvo: A Topology-Aware Self-Evolving Multi-Agent Framework for Root Cause Analysis in Microservices,” evidence record 4285, https://ethics.ai/record/4285 (originally published by arXiv).

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