mlsanityData to 14 Oct 2026

AgentFM: Role-Aware Failure Management for Distributed Databases with LLM-Driven Multi-Agents

arXiv 2504.06614 ↗First posted 9 Apr 2025cs.SEcited by 19

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

Abstract (arXiv)

Distributed databases are critical infrastructures for today's large-scale software systems, making effective failure management essential to ensure software availability. However, existing approaches often overlook the role distinctions within distributed databases and rely on small-scale models with limited generalization capabilities. In this paper, we conduct a preliminary empirical study to emphasize the unique significance of different roles. Building on this insight, we propose AgentFM, a role-aware failure management framework for distributed databases powered by LLM-driven multi-agents. AgentFM addresses failure management by considering system roles, data roles, and task roles, with a meta-agent orchestrating these components. Preliminary evaluations using Apache IoTDB demonstrate the effectiveness of AgentFM and open new directions for further research.

Key facts. Cited by 19 papers in the map (data through 14 Oct 2026). Placed in Software engineering coding agents, one of 16 directions in LLM agents and tool use. Builds on 9 of its 30 references that are in the map. First posted on arXiv 9 Apr 2025.

Builds on

9 of 30 references.

References · 9

  1. 2024Root Cause Analysis In Microservice Using Neural Granger Causal Discoverycited by 32
  2. 2024Automated Root Causing of Cloud Incidents using In-Context Learning with GPT-4cited by 28
  3. 2024mABC: multi-Agent Blockchain-Inspired Collaboration for root cause analysis in micro-services architecturecited by 26
  4. 2023Robust Failure Diagnosis of Microservice System through Multimodal Datacited by 24
  5. 2024X-lifecycle Learning for Cloud Incident Management using LLMscited by 19
  6. 2024Multivariate Log-based Anomaly Detection for Distributed Databasecited by 13
  7. 2023Heterogeneous Anomaly Detection for Software Systems via Semi-supervised Cross-modal Attentioncited by 9
  8. 2024Reducing Events to Augment Log-based Anomaly Detection Models: An Empirical Studycited by 8
  9. 2023Twin Graph-based Anomaly Detection via Attentive Multi-Modal Learning for Microservice Systemcited by 7

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 8; 2026: 11.

19 papers.

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  1. 2025KVCOMM: Online Cross-context KV-cache Communication for Efficient LLM-based Multi-agent Systemscited by 40
  2. 2025A Survey of Reasoning and Agentic Systems in Time Series with Large Language Modelscited by 21
  3. 2025A Survey of AIOps in the Era of Large Language Modelscited by 19
  4. 2025Adaptive Root Cause Localization for Microservice Systems with Multi-Agent Recursion-of-Thoughtcited by 13
  5. 2025Towards Transparent and Incentive-Compatible Collaboration in Decentralized LLM Multi-Agent Systems: A Blockchain-Driven Approachcited by 12
  6. 2025MicroRemed: Benchmarking LLMs in Microservices Remediationcited by 11
  7. 2026Agentic Memory Enhanced Recursive Reasoning for Root Cause Localization in Microservicescited by 9
  8. 2026Hypothesize-Then-Verify: Speculative Root Cause Analysis for Microservices with Pathwise Parallelismcited by 8
  9. 2025LogAction: Consistent Cross-system Anomaly Detection through Logs via Active Domain Adaptationcited by 6
  10. 2026From Feedback Loops to Policy Updates: Reinforcement Fine-Tuning for LLM-Based Alpha Factor Discoverycited by 6
  11. 2026RuntimeSlicer: Towards Generalizable Unified Runtime State Representation for Failure Managementcited by 5
  12. 2025A Survey on AgentOps: Categorization, Challenges, and Future Directionscited by 4
7 more
  1. 2026E2E-REME: Towards End-to-End Microservices Auto-Remediation via Experience-Simulation Reinforcement Fine-Tuningcited by 4
  2. 2026Towards Robust LLM Post-Training: Automatic Failure Management for Reinforcement Fine-Tuningcited by 3
  3. 2026When Planning Fails Despite Correct Execution: On Epistemic Calibration for LLM-Based Multi-Agent Systemscited by 3
  4. 2026Towards In-Depth Root Cause Localization for Microservices with Multi-Agent Recursion-of-Thoughtcited by 1
  5. 2026LLM Agents for Time-Series: A Surveycited by 1
  6. 2026Agent System Operations: Categorization, Challenges, and Future Directionscited by 0
  7. 2026Playing social deduction games with reinforcement fine-tuned large language modelscited by 0

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  1. 2026DBA-Bench: A Production-Fidelity Benchmark for LLM-Based Database Operations Agents
  2. 2025Demystifying the Lifecycle of Failures in Platform-Orchestrated Agentic Workflows
  3. 2026AgentFixer: From Failure Detection to Fix Recommendations in LLM Agentic Systems
  4. 2026A Self-Healing Framework for Reliable LLM-Based Autonomous Agents
  5. 2026Position: Multi-Agent Systems Should Prioritize Concurrency Control
  6. 2026Orchestral AI: A Framework for Agent Orchestration
  7. 2026When Agents Fail to Act: A Diagnostic Framework for Tool Invocation Reliability in Multi-Agent LLM Systems
  8. 2026Maat: Independent Deterministic Contract-Based Governance for Multi-Agent LLM Workflows