InfiniCache: Exploiting Ephemeral Serverless Functions to Build a Cost-Effective Memory Cache


Ao Wang and Jingyuan Zhang, George Mason University; Xiaolong Ma, University of Nevada, Reno; Ali Anwar, Lukas Rupprecht, Dimitrios Skourtis, and Vasily Tarasov, IBM Research--Almaden; Feng Yan, University of Nevada, Reno; Yue Cheng, George Mason University


Internet-scale web applications are becoming increasingly storage-intensive and rely heavily on in-memory object caching to attain required I/O performance. We argue that the emerging serverless computing paradigm provides a well-suited, cost-effective platform for object caching. We present InfiniCache, a first-of-its-kind in-memory object caching system that is completely built and deployed atop ephemeral serverless functions. InfiniCache exploits and orchestrates serverless functions' memory resources to enable elastic pay-per-use caching. InfiniCache's design combines erasure coding, intelligent billed duration control, and an efficient data backup mechanism to maximize data availability and cost-effectiveness while balancing the risk of losing cached state and performance. We implement InfiniCache on AWS Lambda and show that it: (1) achieves 31 – 96× tenant-side cost savings compared to AWS ElastiCache for a large-object-only production workload, (2) can effectively provide 95.4% data availability for each one hour window, and (3) enables comparative performance seen in a typical in-memory cache.

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@inproceedings {246184,
author = {Ao Wang and Jingyuan Zhang and Xiaolong Ma and Ali Anwar and Lukas Rupprecht and Dimitrios Skourtis and Vasily Tarasov and Feng Yan and Yue Cheng},
title = {{InfiniCache}: Exploiting Ephemeral Serverless Functions to Build a {Cost-Effective} Memory Cache},
booktitle = {18th USENIX Conference on File and Storage Technologies (FAST 20)},
year = {2020},
isbn = {978-1-939133-12-0},
address = {Santa Clara, CA},
pages = {267--281},
url = {},
publisher = {USENIX Association},
month = feb

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