Awesome LLM AIOps

A list of awesome academic researches and industrial materials about Large Language Model (LLM) and Artificial Intelligence for IT Operations (AIOps).

Content

• Awesome LLM AIOps
  • Content
  • Introduction
    • Keywords Convention
  • 1. LLM for Incident Management
    • 1.1 Incident Lifecycle
    • 1.2 Incident Reporting
    • 1.3 Root Cause Analysis
    • 1.4 Incident Mitigation
    • 1.5 Incident Postmortem Analysis
    • 1.6 AIOps Question Answering
  • 2. LLM for Log Analysis
    • 2.1 Log Parsing
    • 2.2 Log Anomaly Detection
    • 2.3 Logging Statement Generation
  • 3. LLM for Infrastructure Management
    • 3.1 Benchmark
    • 3.2 Vision
    • 3.3 Infrastructure-as-Code
    • 3.4 LLM Training Platform
  • Contribution
    • Contributing to this paper list

Introduction

This is a list of awesome academic researches and industrial materials about Large Language Model (LLM) and Artificial Intelligence for IT Operations (AIOps).

Keywords Convention

The abbreviation of the work.

The utilized LLM techniques used in the work.

The mainly explored task of the work.

Other important information of the work.

1. LLM for Incident Management

1.0 Survey & Benchmark

1. [Preprint 2024] A Survey of AIOps for Failure Management in the Era of Large Language Models.
2. [Preprint 2024] AI Assistants for Incident Lifecycle in a Microservice Environment: A Systematic Literature Review.
3. [MLSys 2025] AIOpsLab: A Holistic Framework for Evaluating AI Agents for Enabling Autonomous Cloud.
4. [ICML 2025] ITBench: Evaluating AI Agents across Diverse Real-World IT Automation Tasks.
5. [ISSRE 2025] An Empirical Study of Production Incidents in Generative AI Cloud Services.

1.1 Incident Management

1. [HotNets 2023] A Holistic View of AI-driven Network Incident Management.
2. [SoCC 2024] Building AI Agents for Autonomous Clouds: Challenges and Design Principles.
3. [VLDB 2024] D-Bot: Database Diagnosis System using Large Language Models [project].
4. [NSDI 2024] NetAssistant: Dialogue Based Network Diagnosis in Data Center Networks.
5. [Preprint 2024] FLASH: A Workflow Automation Agent for Diagnosing Recurring Incidents.
6. [NDSS 2026] Incident Response Planning Using a Lightweight Large Language Model with Reduced Hallucination.

1.2 Incident Reporting

1. [ESEC/FSE Industry 2023] Assess and Summarize: Improve Outage Understanding with Large Language Models.
2. [ICSE-SEIP 2024] Knowledge-aware Alert Aggregation in Large-scale Cloud Systems: a Hybrid Approach.
3. [ISSRE 2024] Large Language Models Can Provide Accurate and Interpretable Incident Triage.
4. [FSE Industry 2024] MonitorAssistant: Simplifying Cloud Service Monitoring via Large Language Models.
5. [Preprint 2024] Large Language Models can Deliver Accurate and Interpretable Time Series Anomaly Detection.
6. [Preprint 2025] Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models.

1.3 Root Cause Analysis

1. [ICSE 2023] Recommending Root-Cause and Mitigation Steps for Cloud Incidents using Large Language Models.
2. [EuroSys 2024] Automatic Root Cause Analysis via Large Language Models for Cloud Incidents.
3. [ICSE 2024] Xpert: Empowering Incident Management with Query Recommendations via Large Language Models.
4. [ASE 2024] The Potential of One-Shot Failure Root Cause Analysis: Collaboration of the Large Language Model and Small Classifier.
5. [FSE Industry 2024] LM-PACE: Confidence Estimation by Large Language Models for Effective Root Causing of Cloud Incidents.
6. [FSE Industry 2024] Automated Root Causing of Cloud Incidents using In-Context Learning with GPT-4.
7. [FSE Industry 2024] .