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Boxer: Data Analytics on Network-enabled Serverless Platforms

Authors:
Michael Wawrzoniak, Ingo Müller, Rodrigo Fraga Barcelos Paulus Bruno, Gustavo Alonso
Abstract

Serverless is an attractive platform for a variety of applications in the cloud due to its promise of elasticity, low cost, and fast deployment. Instead of using traditional virtual machine services and a fixed infrastructure, which incurs considerable costs to operate and run, Function-as-a-Service allows triggering short computations on demand with the cost proportional to the time the functions are running. As appealing as the idea is, recent work has shown that for data processing applications (regardless of whether it is OLTP, OLAP, or ML) existing serverless platforms are inadequate and additional services are needed in practice, often to address the lack of communication capabilities between functions. In this paper, we demonstrate how to enable function-to-function communication using conventional TCP/IP and show how the ability to communicate can be used to implement data processing on serverless platforms in a more efficient manner than it was possible until now. Our benchmarks show a speedup as high as 11 × in TPC-H queries over systems that use cloud storage to communicate across functions, sustained function-to-function throughput of 621 Mbit/s, and a round-trip latency of less than 1 ms.