On-site, Non-speculative Failure Diagnosis with CLODS
Rishikesh Devsot, Yi Fan Yu, ChenXing Yang, Ellen Shi, Ding Yuan
2026年份
摘要
Diagnosing complex production failures is a notoriously difficult task. The bottleneck of diagnosing these failures is often wild goose chases: developers make incorrect hypotheses about the root cause, leading to time and effort spent in verifying these hypotheses, ultimately realizing they were wrong. This is caused by speculations not backed by sufficient evidence because there is insufficient diagnostic data.
问问这篇 Paper
问问你的智能体。
Lune 读过与它相关的顶会 Paper,每个回答都会注明依据哪几篇。
相关 Paper
- Root Cause Analysis of Failures in Microservices through Causal DiscoveryAzam Ikram, Sarthak Chakraborty, Subrata Mitra, Shiv Kumar Saini 等NeurIPS 2022 · 被引用 185 次
- BugDoc: Algorithms to Debug Computational ProcessesRaoni Lourenço, Juliana Freire, Dennis E. ShashaSIGMOD 2020 · 被引用 9 次
- Live forensics for HPC systems: a case study on distributed storage systemsSaurabh Jha, Shengkun Cui, Subho S. Banerjee, Tianyin Xu 等SC 2020 · 被引用 12 次
- PerFlow: a domain specific framework for automatic performance analysis of parallel applicationsYuyang Jin, Haojie Wang, Runxin Zhong, Chen Zhang 等PPoPP 2022 · 被引用 10 次
- Robust Root Cause Diagnosis using In-Distribution InterventionsLokesh Nagalapatti, Ashutosh Srivastava, Sunita Sarawagi, Amit SharmaICLR 2025
