mlsanityData to 7 Oct 2026

RCAgent: Cloud Root Cause Analysis by Autonomous Agents with Tool-Augmented Large Language Models

arXiv 2310.16340 ↗First posted 25 Oct 2023cs.SE cs.CLcited by 62

On the map: LLM agents and tool use → Software engineering coding agents

Abstract (arXiv)

Large language model (LLM) applications in cloud root cause analysis (RCA) have been actively explored recently. However, current methods are still reliant on manual workflow settings and do not unleash LLMs' decision-making and environment interaction capabilities. We present RCAgent, a tool-augmented LLM autonomous agent framework for practical and privacy-aware industrial RCA usage. Running on an internally deployed model rather than GPT families, RCAgent is capable of free-form data collection and comprehensive analysis with tools. Our framework combines a variety of enhancements, including a unique Self-Consistency for action trajectories, and a suite of methods for context management, stabilization, and importing domain knowledge. Our experiments show RCAgent's evident and consistent superiority over ReAct across all aspects of RCA -- predicting root causes, solutions, evidence, and responsibilities -- and tasks covered or uncovered by current rules, as validated by both automated metrics and human evaluations. Furthermore, RCAgent has already been integrated into the diagnosis and issue discovery workflow of the Real-time Compute Platform for Apache Flink of Alibaba Cloud.

Key facts. Cited by 62 papers in the map (data through 7 Oct 2026). Placed in Software engineering coding agents, one of 16 directions in LLM agents and tool use. Builds on 53 of its 76 references that are in the map. First posted on arXiv 25 Oct 2023.

Builds on

53 of 76 references.

References · 53

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50 most cited of 53 All 53 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 1; 2024: 10; 2025: 22; 2026: 29.

62 papers.

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  1. 2024A Survey on the Memory Mechanism of Large Language Model based Agentscited by 622
  2. 2024Large Language Model-Based Agents for Software Engineering: A Surveycited by 173
  3. 2024Exploring Large Language Model based Intelligent Agents: Definitions, Methods, and Prospectscited by 130
  4. 2025SWE-Debate: Competitive Multi-Agent Debate for Software Issue Resolutioncited by 52
  5. 2025OrcaLoca: An LLM Agent Framework for Software Issue Localizationcited by 43
  6. 2026SkillForge: Forging Domain-Specific, Self-Evolving Agent Skills in Cloud Technical Supportcited by 43
  7. 2024Argumentative Large Language Models for Explainable and Contestable Claim Verificationcited by 36
  8. 2024Agent Design Pattern Catalogue: A Collection of Architectural Patterns for Foundation Model based Agentscited by 35
  9. 2025Flow-of-Action: SOP Enhanced LLM-Based Multi-Agent System for Root Cause Analysiscited by 32
  10. 2025From Language to Action: A Review of Large Language Models as Autonomous Agents and Tool Userscited by 32
  11. 2024mABC: multi-Agent Blockchain-Inspired Collaboration for root cause analysis in micro-services architecturecited by 26
  12. 2025Issue Localization via LLM-Driven Iterative Code Graph Searchingcited by 22
38 more
  1. 2024Building AI Agents for Autonomous Clouds: Challenges and Design Principlescited by 19
  2. 2023Towards Responsible Generative AI: A Reference Architecture for Designing Foundation Model based Agentscited by 13
  3. 2025TAMO: Fine-Grained Root Cause Analysis via Tool-Assisted LLM Agent with Multi-Modality Observation Data in Cloud-Native Systemscited by 13
  4. 2025Reasoning Language Models for Root Cause Analysis in 5G Wireless Networkscited by 12
  5. 2025SHIELDA: Structured Handling of Exceptions in LLM-Driven Agentic Workflowscited by 12
  6. 2025Adaptive Root Cause Localization for Microservice Systems with Multi-Agent Recursion-of-Thoughtcited by 11
  7. 2024LEMMA-RCA: A Large Multi-modal Multi-domain Dataset for Root Cause Analysiscited by 9
  8. 2025Large Language Models for Security Operations Centers: A Comprehensive Surveycited by 9
  9. 2026Agentic Memory Enhanced Recursive Reasoning for Root Cause Localization in Microservicescited by 8
  10. 2026SREGym: A Live Benchmark for AI SRE Agents with High-Fidelity Failure Scenarioscited by 8
  11. 2026Hypothesize-Then-Verify: Speculative Root Cause Analysis for Microservices with Pathwise Parallelismcited by 7
  12. 2025CodeVisionary: An Agent-based Framework for Evaluating Large Language Models in Code Generationcited by 6
  13. 2025The Multi-Agent Fault Localization System Based on Monte Carlo Tree Search Approachcited by 6
  14. 2025Agentic Services Computingcited by 6
  15. 2026Evaluating LLM-Based 0-to-1 Software Generation in End-to-End CLI Tool Scenarioscited by 5
  16. 2024A Taxonomy of Architecture Options for Foundation Model-based Agents: Analysis and Decision Modelcited by 4
  17. 2025Simplifying Root Cause Analysis in Kubernetes with StateGraph and LLMcited by 4
  18. 2025CyberSleuth: Autonomous Blue-Team LLM Agent for Web Attack Forensicscited by 3
  19. 2025Designing LLM-based Multi-Agent Systems for Software Engineering Tasks: Quality Attributes, Design Patterns and Rationalecited by 3
  20. 2025Generative Caching for Structurally Similar Prompts and Responsescited by 3
  21. 2026Graph-Free Root Cause Analysiscited by 3
  22. 2026SADE: Symptom-Aware Diagnostic Escalation for LLM-Based Network Troubleshootingcited by 3
  23. 2026Can LLMs Really Recover Microservice Failures? A Recovery-Aware Evaluation of Diagnosis-to-Action Reasoningcited by 3
  24. 2025Empowering Real-World: A Survey on the Technology, Practice, and Evaluation of LLM-driven Industry Agentscited by 2
  25. 2025PRAXIS: Integrating Program Analysis with Observability for Root-Cause Analysiscited by 2
  26. 2026Bian Que: An Agentic Framework with Flexible Skill Arrangement for Online System Operationscited by 2
  27. 2026Large Language Models for Agentic NetOps and AIOps: Architectures, Evaluation, and Safetycited by 2
  28. 2024Online Multi-modal Root Cause Identification in Microservice Systemscited by 1
  29. 2025Towards a Playground to Democratize Experimentation and Benchmarking of AI Agents for Network Troubleshootingcited by 1
  30. 2025Task-Aware Reduction for Scalable LLM-Database Systemscited by 1
  31. 2026Bridging Temporal and Textual Modalities: A Multimodal Framework for Automated Cloud Failure Root Cause Analysiscited by 1
  32. 2026LogSieve: Task-Aware CI Log Reduction for Sustainable LLM-Based Analysiscited by 1
  33. 2026GSAR: Typed Grounding for Hallucination Detection and Recovery in Multi-Agent LLMscited by 1
  34. 2026CUJBench: Benchmarking LLM-Agent on Cross-Modal Failure Diagnosis from Browser to Backendcited by 1
  35. 2026TopoEvo: A Topology-Aware Self-Evolving Multi-Agent Framework for Root Cause Analysis in Microservicescited by 1
  36. 2026UModel: An Agent-Ready Observability Data Modeling Method at Scalecited by 1
  37. 2026JustDiag!: A Diagnostic Justification Engine for Accountable Root Cause Analysiscited by 1
  38. 2025Automated Fault Detection in 5G Core Networks Using Large Language Modelscited by 0

50 most cited of 62 All 62 (JSON)

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  1. 2026Stalled, Biased, and Confused: Uncovering Reasoning Failures in LLMs for Cloud-Based Root Cause Analysis
  2. 2026Why Do AI Agents Systematically Fail at Cloud Root Cause Analysis?
  3. 2026Cloud-OpsBench: A Reproducible Benchmark for Agentic Root Cause Analysis in Cloud Systems
  4. 2024Exploring LLM-based Agents for Root Cause Analysis
  5. 2026EviRCA: Decoupling Evidence Extraction from Reasoning for Microservice Root-Cause Analysis
  6. 2026Agentic Diagnostic Reasoning over Telecom and Datacenter Infrastructure
  7. 2026TriCalRAG: A Three-Strategy, Retrieval-Augmented Benchmark for On-Premise LLM-Based Root Cause Analysis in AIOps
  8. 2026STAR: A Stage-attributed Triage and Repair framework for RCA Agents in Microservices