Lune

SIGCOMM2023顶会

Achelous: Enabling Programmability, Elasticity, and Reliability in Hyperscale Cloud Networks

Chengkun Wei, Xing Li, Ye Yang, Xiaochong Jiang, Tianyu Xu, Bowen Yang, Taotao Wu, Chao Xu, Yilong Lv, Haifeng Gao, Zhentao Zhang, Zikang Chen

2023年份
25被引次数
9顶会引用

摘要

Cloud computing has witnessed tremendous growth, prompting enterprises to migrate to the cloud for reliable and on-demand computing. Within a single Virtual Private Cloud (VPC), the number of instances (such as VMs, bare metals, and containers) has reached millions, posing challenges related to supporting millions of instances with network location decoupling from the underlying hardware, high elastic performance, and high reliability. However, academic studies have primarily focused on specific issues like high-speed data plane and virtualized routing infrastructure, while existing industrial network technologies fail to adequately address these challenges.

In this paper, we report on the design and experience of Achelous, Alibaba Cloud's network virtualization platform. Achelous consists of three key designs to enhance hyperscale VPC: (𝑖) a novel hierarchical programming architecture based on the collaborative design of both data plane and control plane; (𝑖𝑖) elastic performance strategy and distributed ECMP schemes for seamless scale-up and scale-out, respectively; (𝑖𝑖𝑖) health check scheme and transparent VM live migration mechanisms that ensure stateful flow continuity during the failover. The evaluation results demonstrate that, Achelous scales to over 1, 500, 000 of VMs with elastic network capacity in a single VPC, and reduces 25× programming time, with 99% updating can be completed within 1 second. For failover, it condenses 22.5× downtime during VM live migration, and ensures 99.99% of applications do not experience stall. More importantly, the experience from three years of operation proves the Achelous's serviceability, and versatility independent of any specific hardware platforms.

问问这篇 Paper

智能体会读完全文。

Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。

可以从这些问题问起

智能体调用

Luneget_paper_fulltext

在 Lune 里问

免费开始,无需绑卡

引用它的顶会 Paper9

问问它们各自怎么用它

它引用的顶会 Paper10

相关 Paper

黄昏的海面,两侧是细线勾勒的悬崖