mlsanityData to 7 Oct 2026

STRATUS: A Multi-agent System for Autonomous Reliability Engineering of Modern Clouds

arXiv 2506.02009 ↗First posted 27 May 2025cs.DCcited by 18

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Abstract (arXiv)

In cloud-scale systems, failures are the norm. A distributed computing cluster exhibits hundreds of machine failures and thousands of disk failures; software bugs and misconfigurations are reported to be more frequent. The demand for autonomous, AI-driven reliability engineering continues to grow, as existing humanin-the-loop practices can hardly keep up with the scale of modern clouds. This paper presents STRATUS, an LLM-based multi-agent system for realizing autonomous Site Reliability Engineering (SRE) of cloud services. STRATUS consists of multiple specialized agents (e.g., for failure detection, diagnosis, mitigation), organized in a state machine to assist system-level safety reasoning and enforcement. We formalize a key safety specification of agentic SRE systems like STRATUS, termed Transactional No-Regression (TNR), which enables safe exploration and iteration. We show that TNR can effectively improve autonomous failure mitigation. STRATUS significantly outperforms state-of-the-art SRE agents in terms of success rate of failure mitigation problems in AIOpsLab and ITBench (two SRE benchmark suites), by at least 1.5 times across various models. STRATUS shows a promising path toward practical deployment of agentic systems for cloud reliability.

Key facts. Cited by 18 papers in the map (data through 7 Oct 2026). First posted on arXiv 27 May 2025.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 2; 2026: 16.

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  1. 2026SREGym: A Live Benchmark for AI SRE Agents with High-Fidelity Failure Scenarioscited by 8
  2. 2025Agentic Services Computingcited by 6
  3. 2026OpenRCA 2.0: From Outcome Labels to Causal Process Supervisioncited by 5
  4. 2026Think Locally, Explain Globally: Graph-Guided LLM Investigations via Local Reasoning and Belief Propagationcited by 3
  5. 2026Graph-Free Root Cause Analysiscited by 3
  6. 2025PRAXIS: Integrating Program Analysis with Observability for Root-Cause Analysiscited by 2
  7. 2026Bian Que: An Agentic Framework with Flexible Skill Arrangement for Online System Operationscited by 2
  8. 2026AOI: Turning Failed Trajectories into Training Signals for Autonomous Cloud Diagnosiscited by 1
  9. 2026Rebooting Microreboot: Architectural Support for Safe, Parallel Recovery in Microservice Systemscited by 0
  10. 2026From Natural Language to PromQL: A Catalog-Driven Framework with Dynamic Temporal Resolution for Cloud-Native Observabilitycited by 0
  11. 2026Auditable Graph-Guided Root Cause Analysis for Kubernetes Incidentscited by 0
  12. 2026A Dual-Track Framework for Template-Constrained LaTeX Conversioncited by 0
6 more
  1. 2026KRCA: An Efficient Root Cause Analysis System in Hyper-scale Microservice Systems via Agentic AIcited by 0
  2. 2026Towards a Systems Foundation for Agentic Cloud Managementcited by 0
  3. 2026Beyond Fault Localization: A Trajectory-Level Study of LLM Agents for Microservice Root Cause Analysiscited by 0
  4. 2026ASTRA - Agentic System for Ticket Resolution and Analysiscited by 0
  5. 2026SRE-Marathon: A Continuous, Change-Driven Benchmark for Autonomous Site Reliability Agentscited by 0
  6. 2026Reliability Engineering for AI Systems: Challenges, Methods, and Directionscited by 0