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CAREER: Towards Gray-Fault Tolerant Cloud through Harnessing and Enhancing System Observability

CAREER: Towards Gray-Fault Tolerant Cloud through Harnessing and Enhancing System Observability
职业:通过利用和增强系统可观测性迈向灰色容错云
批准号:
1942794
负责人:
Peng Huang
金额:
$60.95万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-07-01 至 2023-04-30

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中文摘要
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英文摘要
Cloud systems are the crucial infrastructure to many services existing today. Ensuring cloud software runs continuously without disruptions is both vital and challenging. Decades of research have developed mature techniques to detect and mask faults in distributed systems. But these techniques often use a simple model that assumes a system component either works or completely stops. Numerous real-world cloud incidents, however, suggest that production cloud systems frequently experience gray failures---a degraded operational mode in which a system component appears to be working but is in fact severely impaired. Gray failures cannot be effectively dealt with by current solutions. The overall objective of this proposal is to develop a holistic approach to detect, pinpoint and diagnose gray failures in production cloud systems. To realize the objective, four synergistic research activities are proposed. Specifically, the project conducts a study on real-world gray failure cases in popular distributed systems, measure and characterize the observability of existing systems. The project then designs a novel hybrid analysis that automatically inserts report-generation hooks across the whole systems stack to harness observability for detecting gray failures. To pinpoint the culprit component, this project further proposes algorithms to infer causality from the collected observations. Lastly, this project designs a runtime checking framework for increasing observability and online diagnosis of gray failures. Gray failures are a common cause of cloud service outages, resulting in significant financial loss. This project can effectively improve our understandings of gray failures and help detect and debug gray failures to reduce their impact on the ubiquitous cloud infrastructures. Software is moving to be more distributed with increasing subtle failure modes. Observability, fault detection, and localization are critical skills for this paradigm shift but are rarely covered in the existing curriculum. This project addresses this educational gap through curriculum development and student training. This project also promotes Computer Science education to underrepresented Baltimore high school students by organizing workshops in partnership with a non-profit organization, Code in the Schools, for local high school students to showcase cloud and system failure concepts.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(5)
专著(0)
科研奖励(0)
会议论文
Demystifying and Checking Silent Semantic Violations in Large Distributed Systems
揭秘并检查大型分布式系统中的无声语义违规
DOI: --
发表时间: 2022
期刊: 16th USENIX Symposium on Operating Systems Design and Implementation
影响因子: --
作者: [Lou, Chang, Jing, Yuzhuo, Huang, Peng]
通讯作者: Huang, Peng
DOI: 10.1145/3447786.3456252
发表时间: 2021-04
期刊: Proceedings of the Sixteenth European Conference on Computer Systems
影响因子: --
作者: [Brian Choi;R. Burns;Peng Huang]
通讯作者: Brian Choi;R. Burns;Peng Huang
DOI: --
发表时间: 2020-12
期刊:
影响因子: --
作者: [Sebastien Levy;Randolph Yao;Youjiang Wu;Yingnong Dang;Peng Huang;Zheng Mu;Pu Zhao;Tarun Ramani;N. Govindaraju;Xukun Li;Qingwei Lin;Gil Lapid Shafriri;Murali Chintalapati]
通讯作者: Sebastien Levy;Randolph Yao;Youjiang Wu;Yingnong Dang;Peng Huang;Zheng Mu;Pu Zhao;Tarun Ramani;N. Govindaraju;Xukun Li;Qingwei Lin;Gil Lapid Shafriri;Murali Chintalapati
DOI: --
发表时间: 2020
期刊:
影响因子: --
作者: [Chang Lou;Peng Huang;Scott F. Smith]
通讯作者: Chang Lou;Peng Huang;Scott F. Smith
CNS Core: Small: Intelligent Fault Injection to Expose and Reproduce Production-Grade Bugs in Cloud Systems
FMitF: Track I: Synthesizing Semantic Checkers for Runtime Verification of Production Distributed Systems
CAREER: Towards Gray-Fault Tolerant Cloud through Harnessing and Enhancing System Observability
CNS Core: Small: Intelligent Fault Injection to Expose and Reproduce Production-Grade Bugs in Cloud Systems
  • 批准号:
    2149664
  • 项目类别:
    Standard Grant
  • 资助金额:
    $50.0万
  • 财政年份:
    2021
  • 负责人:
    Peng Huang
  • 依托单位:
海外基金