Scaling Serverless Functions: Horizontal or Vertical? Both!

The Function-as-a-Service (FaaS) execution model has dominated cloud computing [1-6]. FaaS applications are developed as standalone functions for which users provide the source code, while providers secure the dependencies (e.g., runtime) and the necessary resources (e.g., memory, CPU) for their execution. This simplifies programming, i.e. developers are alleviated from the burden to manage an entire system, and enables better resource management, i.e. providers can scale dynamically and transparently the resources allocated per function based on the incoming load of requests. Typically, resource allocation is controlled by increasing or decreasing the number of function instances that serve requests.

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Publication Details

Published
2025-03-29
DOI
https://doi.org/10.1145/3721465.3721865
Citations
1
Primary Topic
Parallel Computing and Optimization Techniques
Type
article
Field-Weighted Citation Impact
2.27
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article

Scaling Serverless Functions: Horizontal or Vertical? Both!

Stratos Psomadakis, Nectarios Koziris, Georgios Goumas, Chloe Alverti et al.
1 citations
Parallel Computing and Optimization Techniques
2.27
article

Scaling Serverless Functions: Horizontal or Vertical? Both!

Stratos Psomadakis, Nectarios Koziris, Georgios Goumas, Chloe Alverti, Orestis Lagkas Nikolos
article en
1 citations

Abstract

The Function-as-a-Service (FaaS) execution model has dominated cloud computing [1-6]. FaaS applications are developed as standalone functions for which users provide the source code, while providers secure the dependencies (e.g., runtime) and the necessary resources (e.g., memory, CPU) for their execution. This simplifies programming, i.e. developers are alleviated from the burden to manage an entire system, and enables better resource management, i.e. providers can scale dynamically and transparently the resources allocated per function based on the incoming load of requests. Typically, resource allocation is controlled by increasing or decreasing the number of function instances that serve requests.

University of Illinois Urbana-Champaign (US), National Technical University of Athens (GR)
Openalex Percentile: Top 17%
Parallel Computing and Optimization Techniques
2.27
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