5 citations · 10 across the 6 of their papers we have counts for
6 papers
Generating representative macrobenchmark microservice systems from distributed traces with Palette
Vaastav Anand, Matheus Stolet, Jonathan Mace +1
Microservices are the dominant design for developing cloud systems today. Advancements for microservice need to be evaluated in representative systems, e.g. with matching scale, to…
Intent-based System Design and Operation
Vaastav Anand, Yichen Li, Alok Gautam Kumbhare +6
Cloud systems are the backbone of today's computing industry. Yet, these systems remain complicated to design, build, operate, and improve. All these tasks require significant manu…
Argos: Agentic Time-Series Anomaly Detection with Autonomous Rule Generation via Large Language Models
Yile Gu, Yifan Xiong, Jonathan Mace +4
Observability in cloud infrastructure is critical for service providers, driving the widespread adoption of anomaly detection systems for monitoring metrics. However, existing syst…
AIOpsLab: A Holistic Framework to Evaluate AI Agents for Enabling Autonomous Clouds
Yinfang Chen, Manish Shetty, Gagan Somashekar +6
AI for IT Operations (AIOps) aims to automate complex operational tasks, such as fault localization and root cause analysis, to reduce human workload and minimize customer impact.…
Building AI Agents for Autonomous Clouds: Challenges and Design Principles
Manish Shetty, Yinfang Chen, Gagan Somashekar +10
The rapid growth in the use of Large Language Models (LLMs) and AI Agents as part of software development and deployment is revolutionizing the information technology landscape. Wh…
Cloud Atlas: Efficient Fault Localization for Cloud Systems using Language Models and Causal Insight
Zhiqiang Xie, Yujia Zheng, Lizi Ottens +3
Runtime failure and performance degradation is commonplace in modern cloud systems. For cloud providers, automatically determining the root cause of incidents is paramount to ensur…