RCLAgent uses multi-agent recursion-of-thought with parallel reasoning on trace graphs to outperform prior methods in root cause localization accuracy and efficiency for microservice systems.
Lever- aging large language models for the auto-remediation of microservice applications: An experimental study,
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Towards In-Depth Root Cause Localization for Microservices with Multi-Agent Recursion-of-Thought
RCLAgent uses multi-agent recursion-of-thought with parallel reasoning on trace graphs to outperform prior methods in root cause localization accuracy and efficiency for microservice systems.