Serverless Computing: One Step Forward, Two Steps Back

TL;DR

This paper critically examines the limitations of current serverless computing, highlighting its misalignment with modern data-centric and distributed computing trends, and discusses challenges to unlock its full potential.

Contribution

It identifies key gaps in first-generation serverless architectures and proposes challenges to address for enabling innovative cloud and data system development.

Findings

Current serverless offerings are poorly suited for data-centric computing.

Serverless architectures face significant scalability and hardware integration challenges.

Addressing these gaps is essential for realizing the full potential of cloud computing.

Abstract

Serverless computing offers the potential to program the cloud in an autoscaling, pay-as-you go manner. In this paper we address critical gaps in first-generation serverless computing, which place its autoscaling potential at odds with dominant trends in modern computing: notably data-centric and distributed computing, but also open source and custom hardware. Put together, these gaps make current serverless offerings a bad fit for cloud innovation and particularly bad for data systems innovation. In addition to pinpointing some of the main shortfalls of current serverless architectures, we raise a set of challenges we believe must be met to unlock the radical potential that the cloud---with its exabytes of storage and millions of cores---should offer to innovative developers.