InfiniStore: Elastic Serverless Cloud Storage

Author:

Zhang Jingyuan1,Wang Ao2,Ma Xiaolong3,Carver Benjamin1,Newman Nicholas John1,Anwar Ali4,Rupprecht Lukas5,Tarasov Vasily5,Skourtis Dimitrios6,Yan Feng7,Cheng Yue8

Affiliation:

1. George Mason University

2. George Mason University and Alibaba Group

3. University of Nevada, Reno

4. University of Minnesota

5. IBM Research

6. Redpanda Data

7. University of Houston

8. University of Virginia

Abstract

Cloud object storage such as AWS S3 is cost-effective and highly elastic but relatively slow, while high-performance cloud storage such as AWS ElastiCache is expensive and provides limited elasticity. We present a new cloud storage service called ServerlessMemory, which stores data using the memory of serverless functions. ServerlessMemory employs a sliding-window-based memory management strategy inspired by the garbage collection mechanisms used in the programming language to effectively segregate hot/cold data and provides fine-grained elasticity, good performance, and a pay-per-access cost model with extremely low cost. We then design and implement InfiniStore, a persistent and elastic cloud storage system, which seamlessly couples the function-based ServerlessMemory layer with a persistent, inexpensive cloud object store layer. InfiniStore enables durability despite function failures using a fast parallel recovery scheme built on the auto-scaling functionality of a FaaS (Function-as-a-Service) platform. We evaluate InfiniStore extensively using both microbenchmarking and two real-world applications. Results show that InfiniStore has more performance benefits for objects larger than 10 MB compared to AWS ElastiCache and Anna, and InfiniStore achieves 26.25% and 97.24% tenant-side cost reduction compared to InfiniCache and ElastiCache, respectively.

Publisher

Association for Computing Machinery (ACM)

Subject

General Earth and Planetary Sciences,Water Science and Technology,Geography, Planning and Development

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