一句话：基于微软超大规模云平台一年生产事件，系统分析监控盲区如何导致检测与缓解延迟，并给出最佳监控实践建议。
云提供商依赖自动化监控持续观测服务可用性并主动报告性能退化，但监控不当会延迟生产事件的检测与缓解，造成客户影响和工程开销。本文以微软超大规模云平台过去一年的生产事件为对象，开展实证研究，回答早期检测失败的主要成因与缓解步骤、检测失败的影响、面向不同服务的最佳监控实践，以及如何利用这些洞见提升云服务可靠性。研究揭示现有监控实践的差距，归纳出相关洞见，并为持续可靠性提供监控实践指导。
Cloud providers use automated watchdogs or monitors to continuously observe service availability and to proactively report incidents when system performance degrades. Improper monitoring can lead to delays in the detection and mitigation of production incidents, which can be extremely expensive in terms of customer impacts and manual toil from engineering resources. Therefore, a systematic understanding of the pitfalls in current monitoring practices and how they can lead to production incidents is crucial for ensuring {continuous} reliability of cloud services. In this work, we carefully study the production incidents from the past year at Microsoft to understand the monitoring gaps in a hyperscale cloud platform. We conduct an extensive empirical study to answer: (1) What are the major causes of failures in early detection of production incidents and what are the steps taken for mitigation, (2) What is the impact of failures in early detection, (3) How do we recommend best monitoring practices for different services, and (4) How can we leverage the insights from this study to enhance the reliability of the cloud services. This study provides a deeper understanding of existing monitoring gaps in cloud platforms, uncover interesting insights and provide guidance for best monitoring practices for ensuring continuous reliability.
@inproceedings{GanatraPGKMBNM23,
title = {Detection Is Better Than Cure: A Cloud Incidents Perspective},
author = {Vaibhav Ganatra and Anjaly Parayil and Supriyo Ghosh and Yu Kang and Minghua Ma and Chetan Bansal and Suman Nath and Jonathan Mace},
booktitle = {FSE},
year = {2023},
doi = {10.1145/3611643.3613898}
}