Serverless End Game: Disaggregation enabling Transparency

TL;DR

This paper argues that resource disaggregation in serverless computing can enable full transparency, allowing unmodified code to run seamlessly over cloud resources with performance comparable to local execution.

Contribution

It demonstrates that full transparency is achievable today with disaggregated serverless resources and identifies key open challenges for future research.

Findings

Achieved transparency over disaggregated serverless resources with comparable performance to local execution.

Identified five open research challenges including locality, memory disaggregation, and deployment optimization.

Abstract

For many years, the distributed systems community has struggled to smooth the transition from local to remote computing. Transparency means concealing the complexities of distributed programming like remote locations, failures or scaling. For us, full transparency implies that we can compile, debug and run unmodified single-machine code over effectively unlimited compute, storage, and memory resources. We elaborate in this article why resource disaggregation in serverless computing is the definitive catalyst to enable full transparency in the Cloud. We demonstrate with two experiments that we can achieve transparency today over disaggregated serverless resources and obtain comparable performance to local executions. We also show that locality cannot be neglected for many problems and we present five open research challenges: granular middleware and locality, memory disaggregation, virtualization, elastic programming models, and optimized deployment. If full transparency is possible, who needs explicit use of middleware if you can treat remote entities as local ones? Can we close the curtains of distributed systems complexity for the majority of users?