Agent System Operations: Categorization, Challenges, and Future Directions
2026-06-01 • Multiagent Systems
Multiagent Systems
AI summaryⓘ
The authors explain that as Large Language Model-based agent systems get smarter, they sometimes run into problems that make them unstable or insecure. To help fix this, the authors studied how these problems happen and created a clear way to manage and maintain these agents, called AgentOps. This method includes watching the system, finding problems, understanding why they happen, and solving them. Their work aims to make agent systems more reliable and easier to handle.
Large Language ModelsAgent SystemsAnomaliesAgentOpsMonitoringAnomaly DetectionRoot Cause LocalizationSystem StabilitySystem Maintenance
Authors
Zexin Wang, Changhua Pei, Yuanhao Liu, Jingjing Li, Yintong Huo, Quan Zhou, Haotian Si, Hang Cui, Zihan Liu, Gaogang Xie, Fei Sun, Dan Pei, David Lo
Abstract
As the reasoning capabilities of Large Language Models (LLMs) continue to advance, LLM-based agent systems offer advantages in flexibility and interpretability over traditional systems, garnering increasing attention. However, despite the widespread research interest and industrial application of agent systems, these systems, like their traditional counterparts, frequently encounter anomalies. These anomalies lead to instability and insecurity, hindering their further development. Therefore, a comprehensive and systematic approach to the operation and maintenance of agent systems is urgently needed. Unfortunately, current research on the operations of agent systems is sparse. To address this gap, we have undertaken a survey on agent system operations with the aim of establishing a clear framework for the field, defining the challenges, and facilitating further development. Specifically, this paper begins by systematically defining anomalies within agent systems, categorizing them into intra-agent anomalies and inter-agent anomalies. Next, we introduce a novel and comprehensive operational framework for agent systems, dubbed Agent System Operations (AgentOps). We provide detailed definitions and explanations of its four key stages: monitoring, anomaly detection, root cause localization, and resolution.