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P2 Cooperative Graceful Degradation in Containerized Clouds

容器化云中的协同优雅降级
ASPLOS Proceedings of the 30th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 12025匹配度 1/10 · 该论文聚焦容器云在故障下的优雅降级、关键性标签与 diagonal scaling,属于分布式系统与云可靠性方向;与用户关注的程序静态分析、LLM/Agent、浮点程序分析及贝叶斯程序分析没有直接交叉。引用 2 inbox
Kapil Agrawal, Sangeetha Abdu Jyothi
crossref: 2026-09-12dblp: 2026-09-12arxiv: 2026-09-12

AI 速览

一句话:提出应用与云运营商协同优雅降级,并利用关键性标签与 diagonal scaling 提升故障下关键服务可用性。

该论文针对云故障和容量紧张时缺乏兼顾应用可用性要求与运营商目标的优雅降级机制这一问题,提出应用与云运营商协同优雅降级的愿景。方法上,利用容器上的 criticality tags 进行 diagonal scaling,在容量危机时关闭非关键容器;设计 Phoenix 自动云弹性管理系统,在 Kubernetes 上最大化关键服务可用性,并开发开源 resilience 基准框架 AdaptLab。实验表明,Phoenix 在大规模故障中可将关键服务可用性提升最多 2 倍,并能在 10 秒内处理 10 万节点集群的故障。

问题
云运营商在故障或容量紧张时,缺乏一种能在满足应用可用性要求的同时执行优雅降级的自动化机制。
方法
提出应用与云运营商协同优雅降级,利用容器关键性标签进行 diagonal scaling,并实现基于 Kubernetes 的 Phoenix 控制器与 AdaptLab 基准框架。
评估
通过实验评估 Phoenix 在大规模故障下的关键服务可用性提升,以及其在 10 万节点集群中的故障处理延迟。
原文摘要(Abstract)

Cloud resilience is crucial for cloud operators and the myriad of applications that rely on the cloud. Today, we lack a mechanism that enables cloud operators to perform graceful degradation of applications while satisfying the application's availability requirements. In this paper, we put forward a vision for automated cloud resilience management with cooperative graceful degradation between applications and cloud operators. First, we investigate techniques for graceful degradation and identify an opportunity for cooperative graceful degradation in public clouds. Second, leveraging criticality tags on containers, we propose diagonal scaling---turning off non-critical containers during capacity crunch scenarios---to maximize the availability of critical services. Third, we design Phoenix, an automated cloud resilience management system that maximizes critical service availability of applications while also considering operator objectives, thereby improving the overall resilience of the infrastructure during failures. We experimentally show that the Phoenix controller running atop Kubernetes can improve critical service availability by up to 2× during large-scale failures. Phoenix can handle failures in a cluster of 100,000 nodes within 10 seconds. We also develop AdaptLab, an open-source resilience benchmarking framework that can emulate realistic cloud environments with real-world application dependency graphs.

链接与引用

DOI 原文 · arXiv · PDF(开放获取) · DBLP

BibTeX
@inproceedings{AgrawalJ25,
  title = {Cooperative Graceful Degradation in Containerized Clouds},
  author = {Kapil Agrawal and Sangeetha Abdu Jyothi},
  booktitle = {ASPLOS},
  year = {2025},
  doi = {10.1145/3669940.3707244}
}