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

Fuente: arXiv
Salvato in:
Dettagli Bibliografici
Autori principali: Zhang, Lingzhe, Zhai, Yunpeng, Jia, Tong, Huang, Xiaosong, Duan, Chiming, Li, Ying
Natura: Preprint
Pubblicazione: 2025
Soggetti:
Accesso online:
Tags: Aggiungi Tag
Nessun Tag, puoi essere il primo ad aggiungerne!!
_version_ 1866910907033976832
author Zhang, Lingzhe
Zhai, Yunpeng
Jia, Tong
Huang, Xiaosong
Duan, Chiming
Li, Ying
author_facet Zhang, Lingzhe
Zhai, Yunpeng
Jia, Tong
Huang, Xiaosong
Duan, Chiming
Li, Ying
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2504_06614
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle AgentFM: Role-Aware Failure Management for Distributed Databases with LLM-Driven Multi-Agents
Zhang, Lingzhe
Zhai, Yunpeng
Jia, Tong
Huang, Xiaosong
Duan, Chiming
Li, Ying
Software Engineering
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.
title AgentFM: Role-Aware Failure Management for Distributed Databases with LLM-Driven Multi-Agents
topic Software Engineering
url https://arxiv.org/abs/2504.06614