Serverless Computing: One Step Forward, Two Steps Back
By Joseph M Hellerstein, Jose M. Faleiro, Joseph Gonzalez, Johann Schleier-Smith, Vikram Sreekanti, Alexey Tumanov, Chenggang Wu. Conference on Innovative Data Systems Research, 2018
437 citations recorded by the source corpus.
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.
Subfields: Computer Networks and Communications, Information Systems
View Paper: https://www.semanticscholar.org/paper/810c5e5cd7f83edbd141a6e89981e116b0de405f
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Networks and Communications
- Raluca Ada Popa
- Simon Shillaker
- Peter R. Pietzuch
- Chia-che Tsai
- Haibo Chen
- Ion Stoica
- Binyu Zang
- Scott Shenker
In Information Systems
- Raluca Ada Popa
- Simon Shillaker
- Peter R. Pietzuch
- Chia-che Tsai
- Haibo Chen
- Ion Stoica
- Binyu Zang
- Mosharaf Chowdhury
Citations in the corpus
- Faasm: Lightweight Isolation for Efficient Stateful Serverless Computing (2020, background): “Container initialisation times have been reduced to mitigate the cold-start problem, which can contribute several seconds of latency with standard containers [30,60,70].”
- What serverless computing is and should become (2021, methodology): “13,17 Figure 4 illustrates how network traffic could be much higher if we implement our example using cloud functions, rather than using an application-specific framework such as Cloud Dataflow.”
- Catalyzer: Sub-millisecond Startup for Serverless Computing with Initialization-less Booting (2020, background): “Physics Experiments (with a particular eye on CERN LHC) Executing serverless functions with low latency is critical for user experience [21, 24, 28, 32, 38], and is still a significant challenge for virtualization-based sandbox design.”
- Cloud Programming Simplified: A Berkeley View on Serverless Computing (2019, methodology): “Additional work done by our Berkeley colleagues and some of us emphasizes data-centric, distributed systems, machine learning, and programming model challenges and opportunities for serverless computing [50].”