Resource-Centric Serverless Computing

06/27/2022
by   Zhiyuan Guo, et al.
0

Today's serverless computing has several key limitations including per-function resource limits, fixed CPU-to-memory ratio, and constant resource allocation throughout a function execution and across different invocations of it. The root cause of these limitations is the "function-centric" model: a function is a fixed-size box that is allocated, executed, and terminated as an inseparable unit. This unit is pre-defined by the cloud provider and cannot properly capture user needs. We propose a "resource-centric" model for serverless computing, which adapts the underlying provider serverless systems to follow applications' natural resource needs. To achieve this vision, we built Scad based on two ideas: disaggregating a serverless application based on its resource features and aggregating disaggregated units for better performance. Our results show that Scad solves various resource-related issues of today's serverless computing, while retaining or even improving its performance.

READ FULL TEXT

Please sign up or login with your details

Forgot password? Click here to reset

Sign in with Google

×

Use your Google Account to sign in to DeepAI

×

Consider DeepAI Pro