Cacheman: A Comprehensive Last-Level Cache Management System for Multi-tenant Clouds

View at publisher
Authors: Xiaokang Hu, Yuchao Cao, Naixuan Guan, Yifan Wu, Xishi Qiu, Shuting Dai, Bangping Luo, Sheng Cheng, Fudong Qiu, Yibin Shen, Jiesheng Wu
Cited by: 1
References: 16

Abstract

Competition for the last-level cache (LLC) is a long-standing issue in multi-tenant cloud environments, often leading to severe performance interference among co-located virtual machines. LLC management in the cloud faces unique challenges, including unpredictable tenant workloads, misaligned performance metrics, and the need to ensure fairness under service level agreements (SLAs). Existing LLC allocation methods fall short in addressing these challenges. We present Cacheman, a comprehensive LLC management system designed from real-world cloud deployment experience. Cacheman introduces a novel gradient-based sharing mechanism for LLC ways, enabling smooth LLC allocation adjustments that simultaneously improve fairness and utilization efficiency. Its real-time allocation algorithm promptly detects and mitigates unfair LLC allocation, adapting to dynamic workloads with second-scale responsiveness. Additionally, Cacheman supports performance consistency for tenants running distributed applications by enforcing negotiated upper bounds on cache usage. Extensive experiments demonstrate that Cacheman effectively achieves its multi-dimensional goals, and long-term production deployment further shows that it significantly reduces SLA violations caused by LLC contention.

Fields of Study & Subjects

Cloud Computing and Resource Management IoT and Edge/Fog Computing Caching and Content Delivery

Publication details

Journal / source
Proceedings of the 31st ACM SIGPLAN Annual Symposium on Principles and Practice of Parallel Programming
Publisher
ACM
Pages
329–341
Publication date
28 January 2026