mlsanityData to 14 Oct 2026

A Survey of AIOps in the Era of Large Language Models

arXiv 2507.12472 ↗First posted 23 Jun 2025cs.SE cs.CLcited by 19

Not on the map. Why?

Abstract (arXiv)

As large language models (LLMs) grow increasingly sophisticated and pervasive, their application to various Artificial Intelligence for IT Operations (AIOps) tasks has garnered significant attention. However, a comprehensive understanding of the impact, potential, and limitations of LLMs in AIOps remains in its infancy. To address this gap, we conducted a detailed survey of LLM4AIOps, focusing on how LLMs can optimize processes and improve outcomes in this domain. We analyzed 183 research papers published between January 2020 and December 2024 to answer four key research questions (RQs). In RQ1, we examine the diverse failure data sources utilized, including advanced LLM-based processing techniques for legacy data and the incorporation of new data sources enabled by LLMs. RQ2 explores the evolution of AIOps tasks, highlighting the emergence of novel tasks and the publication trends across these tasks. RQ3 investigates the various LLM-based methods applied to address AIOps challenges. Finally, RQ4 reviews evaluation methodologies tailored to assess LLM-integrated AIOps approaches. Based on our findings, we discuss the state-of-the-art advancements and trends, identify gaps in existing research, and propose promising directions for future exploration.

Key facts. Cited by 19 papers in the map (data through 14 Oct 2026). Builds on 61 of its 175 references that are in the map. First posted on arXiv 23 Jun 2025.

Builds on

61 of 175 references.

References · 61

  1. 2023A Survey on Evaluation of Large Language Modelscited by 1,242
  2. 2023Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMscited by 974
  3. 2023One Fits All:Power General Time Series Analysis by Pretrained LMcited by 632
  4. 2023Large Language Models Are Zero-Shot Time Series Forecasterscited by 500
  5. 2024A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applicationscited by 431
  6. 2023TEMPO: Prompt-based Generative Pre-trained Transformer for Time Series Forecastingcited by 174
  7. 2022PromptCast: A New Prompt-based Learning Paradigm for Time Series Forecastingcited by 172
  8. 2023TEST: Text Prototype Aligned Embedding to Activate LLM's Ability for Time Seriescited by 169
  9. 2023UniTime: A Language-Empowered Unified Model for Cross-Domain Time Series Forecastingcited by 144
  10. 2023LLM4TS: Aligning Pre-Trained LLMs as Data-Efficient Time-Series Forecasterscited by 129
  11. 2022Pretrained Language Models for Text Generation: A Surveycited by 122
  12. 2023Automatic Root Cause Analysis via Large Language Models for Cloud Incidentscited by 84
38 more
  1. 2020Loghub: A Large Collection of System Log Datasets for AI-driven Log Analyticscited by 70
  2. 2021Log-based Anomaly Detection Without Log Parsingcited by 59
  3. 2024LSTPrompt: Large Language Models as Zero-Shot Time Series Forecasters by Long-Short-Term Promptingcited by 59
  4. 2021Anomaly Detection and Failure Root Cause Analysis in (Micro)Service-Based Cloud Applications: A Surveycited by 48
  5. 2023OWL: A Large Language Model for IT Operationscited by 43
  6. 2025AIOpsLab: A Holistic Framework to Evaluate AI Agents for Enabling Autonomous Cloudscited by 40
  7. 2023Interpretable Online Log Analysis Using Large Language Models with Prompt Strategiescited by 38
  8. 2023GATGPT: A Pre-trained Large Language Model with Graph Attention Network for Spatiotemporal Imputationcited by 35
  9. 2023LILAC: Log Parsing using LLMs with Adaptive Parsing Cachecited by 32
  10. 2024LLMParser: An Exploratory Study on Using Large Language Models for Log Parsingcited by 32
  11. 2024Large language models can be zero-shot anomaly detectors for time series?cited by 31
  12. 2024Automated Root Causing of Cloud Incidents using In-Context Learning with GPT-4cited by 28
  13. 2024mABC: multi-Agent Blockchain-Inspired Collaboration for root cause analysis in micro-services architecturecited by 26
  14. 2024X-lifecycle Learning for Cloud Incident Management using LLMscited by 19
  15. 2024Building AI Agents for Autonomous Clouds: Challenges and Design Principlescited by 19
  16. 2025AgentFM: Role-Aware Failure Management for Distributed Databases with LLM-Driven Multi-Agentscited by 19
  17. 2025ThinkFL: Self-Refining Failure Localization for Microservice Systems via Reinforcement Fine-Tuningcited by 18
  18. 2023Assess and Summarize: Improve Outage Understanding with Large Language Modelscited by 17
  19. 2024Face It Yourselves: An LLM-Based Two-Stage Strategy to Localize Configuration Errors via Logscited by 17
  20. 2023Log Parsing: How Far Can ChatGPT Go?cited by 16
  21. 2024Lemur: Log Parsing with Entropy Sampling and Chain-of-Thought Mergingcited by 16
  22. 2024LogLM: From Task-based to Instruction-based Automated Log Analysiscited by 15
  23. 2024Multivariate Log-based Anomaly Detection for Distributed Databasecited by 13
  24. 2021Robust and Transferable Anomaly Detection in Log Data using Pre-Trained Language Modelscited by 12
  25. 2023An Assessment of ChatGPT on Log Datacited by 12
  26. 2024Failure Diagnosis in Microservice Systems: A Comprehensive Survey and Analysiscited by 12
  27. 2024Cloud Atlas: Efficient Fault Localization for Cloud Systems using Language Models and Causal Insightcited by 12
  28. 2024GenKubeSec: LLM-Based Kubernetes Misconfiguration Detection, Localization, Reasoning, and Remediationcited by 11
  29. 2024LogEval: A Comprehensive Benchmark Suite for Large Language Models In Log Analysiscited by 11
  30. 2023Learning DAGs from Data with Few Root Causescited by 8
  31. 2023A Critical Review of Common Log Data Sets Used for Evaluation of Sequence-based Anomaly Detection Techniquescited by 8
  32. 2024Analyzing and Mitigating (with LLMs) the Security Misconfigurations of Helm Charts from Artifact Hubcited by 8
  33. 2024TimeGPT in Load Forecasting: A Large Time Series Model Perspectivecited by 8
  34. 2024Reducing Events to Augment Log-based Anomaly Detection Models: An Empirical Studycited by 8
  35. 2024LLMcap: Large Language Model for Unsupervised PCAP Failure Detectioncited by 7
  36. 2024RAG4ITOps: A Supervised Fine-Tunable and Comprehensive RAG Framework for IT Operations and Maintenancecited by 7
  37. 2023Learning Representations on Logs for AIOpscited by 6
  38. 2024MultiCast: Zero-Shot Multivariate Time Series Forecasting Using LLMscited by 6

50 most cited of 61 All 61 (JSON)

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 3; 2026: 16.

19 papers.

Sort:

By area:

  1. 2025Adaptive Root Cause Localization for Microservice Systems with Multi-Agent Recursion-of-Thoughtcited by 13
  2. 2026Agentic Memory Enhanced Recursive Reasoning for Root Cause Localization in Microservicescited by 9
  3. 2026Hypothesize-Then-Verify: Speculative Root Cause Analysis for Microservices with Pathwise Parallelismcited by 8
  4. 2025Multi-Agent LLM Orchestration Achieves Deterministic, High-Quality Decision Support for Incident Responsecited by 6
  5. 2026From Feedback Loops to Policy Updates: Reinforcement Fine-Tuning for LLM-Based Alpha Factor Discoverycited by 6
  6. 2026Towards Robust LLM Post-Training: Automatic Failure Management for Reinforcement Fine-Tuningcited by 3
  7. 2026Bian Que: An Agentic Framework with Flexible Skill Arrangement for Online System Operationscited by 2
  8. 2026Large Language Models for Agentic NetOps and AIOps: Architectures, Evaluation, and Safetycited by 2
  9. 2026Root Cause Analysis Method Based on Large Language Models with Residual Connection Structurescited by 1
  10. 2026UModel: An Agent-Ready Observability Data Modeling Method at Scalecited by 1
  11. 2026Progressive Crystallization: Turning Agent Exploration into Deterministic, Lower-Cost Workflows in Productioncited by 1
  12. 2025RationAnomaly: Log Anomaly Detection with Rationality via Chain-of-Thought and Reinforcement Learningcited by 0
7 more
  1. 2026MCP-Diag: A Deterministic, Protocol-Driven Architecture for AI-Native Network Diagnosticscited by 0
  2. 2026Auditable Graph-Guided Root Cause Analysis for Kubernetes Incidentscited by 0
  3. 2026Towards a Systems Foundation for Agentic Cloud Managementcited by 0
  4. 2026Beyond Capability Benchmarks: Learning Operational Fingerprints of LLM Cloud Services from Production Incident Metadatacited by 0
  5. 2026Learning-Augmented Algorithms: Guarantees, Construction Mechanisms, and System-Level Implicationscited by 0
  6. 2026SRE-Marathon: A Continuous, Change-Driven Benchmark for Autonomous Site Reliability Agentscited by 0
  7. 2026Playing social deduction games with reinforcement fine-tuned large language modelscited by 0