Microservice Architecture

Follow this topic Ask about this topic

Momentum

0 papers in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

Jul 13Week of Sep 28

Latest papers 12

All topics

GALA: Graph-Augmented LLM Agents for Root Cause Analysis and Incident Response in Microservices
Aug 10, 2026Yifang Tian, Yaming Liu, Zichun Chong +3Tool-Augmented Language Model Agents LLM Agent Evaluation
University of Toronto Toronto, Canada
From Textual Requirements to Microservice Architectures - A Comprehensive Evaluation of LLM-Based Design Synthesis
Jul 30, 2026Danyllo Albuquerque, José Renan, Guillermo Rodríguez +6LLM Prompting Microservice Architecture
VIRTUS/UFCG Federal University of Campina Grande (UFCG), Paraiba Brazil · Federal University of Campina Grande (UFCG), Paraiba Brazil · Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Universidad Nacional del Centro de la Provincia de Buenos Aires (UNICEN), Argentina +2
A Multi-Dataset Benchmark for Evaluating LLM Agents in Microservice Failure Diagnosis
Jun 28, 2026Yuanhong Cai, Xiaohui Nie, Kanglin Yin +8Software Engineering LLM Agent Evaluation
Computer Network Information Center, Chinese Academy of Sciences, Beijing, China · Key Laboratory for Satellite Digitalization Technology, Chinese Academy of Sciences, Shanghai, China · Nankai University, Tianjin, China +2
A Topology-Aware, Memory-Centric Architecture that Separates Root-Cause Derivation from Root-Cause Explanation
Jun 18, 2026Momil SeedatSoftware Engineering Microservice Architecture
Independent Research Prototype
Anomaly Detection and Root Cause Analysis for Microservice Systems
Jun 8, 2026Luan PhamSoftware Engineering Microservice Architecture
Viet Nam National University Ho Chi Minh City - University of Technology (HCMUT) · School of Computing Technologies, College of Science, Technology, Engineering and Maths, Royal Melbourne Institute of Technology (RMIT University), Melbourne, Victoria, Australia
TopoEvo: A Topology-Aware Self-Evolving Multi-Agent Framework for Root Cause Analysis in Microservices
May 15, 2026Junle Wang, Xingchuang Liao, Wenjun WuSoftware Engineering Multi-Agent Orchestration
School of Artificial Intelligence, Beihang University Beijing, China
Towards In-Depth Root Cause Localization for Microservices with Multi-Agent Recursion-of-Thought
May 14, 2026Lingzhe Zhang, Tong Jia, Kangjin Wang +8Software Engineering Multi-Agent LLM Systems
Peking University, Beijing, China · Huawei Theory Lab, China
LLM-Based Robustness Testing of Microservice Applications: An Empirical Study
May 13, 2026Hrushitha Goud Tigulla, Marco VieiraSoftware Engineering Automated Software Testing
College of Computing and Informatics University of North Carolina at Charlotte Charlotte, USA
Operationalizing Document AI: A Microservice Architecture for OCR and LLM Pipelines in Production
May 12, 2026Yao Fehlis, Benjamin Bengfort, Zhangzhang Si +9Software Engineering Document Information Extraction
Hypergraph and Latent ODE Learning for Multimodal Root Cause Localization in Microservices
May 1, 2026Xin Liu, Yuhang He, Sichen Zhao +2Microservice Architecture Root Cause Analysis
Independent Researcher New York, USA · Independent Researcher Chicago, USA · Northeastern University Boston, USA +2
KAYRA: A Microservice Architecture for AI-Assisted Karyotyping with Cloud and On-Premise Deployment
Apr 29, 2026Attila Pintér, Javier Rico, Attila Répai +5Microservice Architecture Medical Image Segmentation
Jedlik Innovation Ltd., Budapest, Hungary · Pázmány Péter Catholic University, Faculty of Information Technology and Bionics, Budapest, Hungary · Central Hospital of Southern Pest — National Institute of Hematology and Infectious Diseases, Laboratory of Molecular Genetics, Budapest, Hungary
STLGT: A Scalable Trace-Based Linear Graph Transformer for Tail Latency Prediction in Microservices
Apr 29, 2026Yongliang Ding, Qigong Bi, Peng PuEfficient Neural Network Inference Microservice Architecture
East China Normal University Shanghai, China

Aug 10, 2026, cs.SEJ/K move · Enter open · S save

GALA: Graph-Augmented LLM Agents for Root Cause Analysis and Incident Response in Microservices

Yifang Tian, Yaming Liu, Zichun Chong, Zihang Huang+2

University of Toronto Toronto, Canada

Tool-Augmented Language Model Agents LLM Agent Evaluation Microservice Architecture LLM Agents Root Cause Analysis

Open paper AskPDF arXiv

Microservice root cause analysis (RCA) requires correlating failures across heterogeneous telemetry within complex service dependency graphs. Existing methods often rely on a single telemetry modality; recent LLM-based approaches can suffer from unconstrained exploration and hallucination; and most systems stop at fault ranking without producing actionable incident response. We present GALA+, a graph-augmented LLM agentic framework centered on graph-guided investigation, which uses service dependencies to bound exploration and refine diagnosis through localized multi-modal evidence. For initial hypothesis generation, GALA+ combines complementary telemetry signals with STRIX, a novel trace- and graph-structure-aware scoring module. GALA+ then produces ranked diagnoses, incident summaries, and stratified action recommendations. We further introduce SURE-Score, a human-guided evaluation framework co-developed with industry SRE experts for assessing RCA-specific output quality beyond conventional text similarity metrics. On two microservice benchmarks, GALA+ consistently achieves the strongest overall results, surpassing the best LLM-based baseline by more than 25 percentage points in AC@1, while also receiving the highest ratings from both SURE-Score and independent human SRE evaluation.

Momentum

Related topics

Latest papers 12