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arXiv · 2408.00957

Caching Aided Multi-Tenant Serverless Computing

Chu Qiao·Cong Wang·Zhenkai Zhang·Yuede Ji·Xing Gao
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Abstract

One key to enabling high-performance serverless computing is to mitigate cold-starts. Current solutions utilize a warm pool to keep function alive: a warm-start can be analogous to a CPU cache-hit. However, modern cache has multiple hierarchies and the last-level cache is shared among cores, whereas the warm pool is limited to a single tenant for security concerns. Also, the warm pool keep-alive policy can be further optimized using cache replacement algorithms. In this paper, we borrow practical optimizations from caching, and design FaasCamp, a caching-aided multi-tenant serverless computing framework. FaasCamp extends the single-tier warm pool into multi-tiers, with a reclaim pool introduced enabling secure function instance sharing among tenants. Also, FaasCamp leverages machine learning to approximate the optimal cache replacement policy to improve the warm rate. We have implemented a prototype and conducted extensive experiments under multiple scenarios. The results show that FaasCamp can outperform existing platforms with minimal overhead.

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Chu Qiao, Cong Wang, Zhenkai Zhang, Yuede Ji, Xing Gao. 2024-08-01. Caching Aided Multi-Tenant Serverless Computing. https://arxiv.org/abs/2408.00957

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