3 citations · 5 across the 5 of their papers we have counts for
5 papers
WorkflowPerturb: Calibrated Stress Tests for Evaluating Multi-Agent Workflow Metrics
Madhav Kanda, Sharad Agarwal, Rodrigo Fonseca +2
Multi-agent LLM systems that generate structured workflows from natural-language requests are now deployed in production across cloud automation, DevOps, and enterprise orchestrati…
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…
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…
Exploring LLM-based Agents for Root Cause Analysis
Devjeet Roy, Xuchao Zhang, Rashi Bhave +4
The growing complexity of cloud based software systems has resulted in incident management becoming an integral part of the software development lifecycle. Root cause analysis (RCA…
PACE-LM: Prompting and Augmentation for Calibrated Confidence Estimation with GPT-4 in Cloud Incident Root Cause Analysis
Dylan Zhang, Xuchao Zhang, Chetan Bansal +3
Major cloud providers have employed advanced AI-based solutions like large language models to aid humans in identifying the root causes of cloud incidents. Despite the growing prev…