TORAI finds fine-grained root causes in microservice failures with blind spots by measuring anomaly severity from multi-source telemetry, clustering services by symptoms, ranking via causal analysis within clusters, and aggregating with hypothesis testing.
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Auto-Diagnose applies LLMs to summarize and diagnose root causes of integration test failures, reporting 90.14% accuracy on 71 manual cases and positive adoption after Google-wide rollout.
citing papers explorer
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TORAI: Multi-source Root Cause Analysis for Blind Spots in Microservice Service Call Graph
TORAI finds fine-grained root causes in microservice failures with blind spots by measuring anomaly severity from multi-source telemetry, clustering services by symptoms, ranking via causal analysis within clusters, and aggregating with hypothesis testing.
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LLM-Based Automated Diagnosis Of Integration Test Failures At Google
Auto-Diagnose applies LLMs to summarize and diagnose root causes of integration test failures, reporting 90.14% accuracy on 71 manual cases and positive adoption after Google-wide rollout.