INS: Identifying and Mitigating Performance Interference in Clouds via Interference-Sensitive Paths
Authors: 
Ziwei Huang, Mengyao Xie, Shibo Tang, Zihao Chang, Zhicheng Yao, Yungang Bao, Sa WangAuthors Info & Claims
Pages 380 - 397
Abstract
Identifying and managing performance interference in clouds has long been a critical and challenging task for cloud providers. They keep seeking useful performance indicators from underlying systems to monitor cloud applications accurately. However, state-of-the-art indicators are either sensitive to limited applications and resource contention or are unrobust to the continually changing production environments. There still lacks a practical and efficient indicator for production environments.
This paper proposes INS, a cloud runtime system that can effectively detect the performance fluctuation of online cloud applications and reallocate resources to curb performance interference. It proposes INSPath as the new performance indicator to describe the degree of performance degradation and pinpoint the resource bottlenecks. Our evaluation of nine widely-used applications demonstrates that INS can detect the SLO violations of applications and identify the resource bottleneck accurately. Meanwhile, INS outperforms state-of-the-art PARTIES with more responsive and effective resource tuning and fewer SLO violations.
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November 2024
1062 pages
ISBN:9798400712869
DOI:10.1145/3698038
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Published: 20 November 2024
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