The University of Southampton
University of Southampton Institutional Repository

Streaming vs. functions: a cost perspective on cloud event processing

Streaming vs. functions: a cost perspective on cloud event processing
Streaming vs. functions: a cost perspective on cloud event processing

In cloud event processing, data generated at the edge is processed in real-time by cloud resources. Both distributed stream processing (DSP) and Function-as-a-Service (FaaS) have been proposed to implement such event processing applications. FaaS emphasizes fast development and easy operation, while DSP emphasizes efficient handling of large data volumes. Despite their architectural differences, both can be used to model and implement loosely-coupled job graphs. In this paper, we consider the selection of FaaS and DSP from a cost perspective. We implement stateless and stateful workflows from the Theodolite benchmarking suite using cloud FaaS and DSP. In an extensive evaluation, we show how application type, cloud service provider, and runtime environment can influence the cost of application deployments and derive decision guidelines for cloud engineers.

cloud data processing, FaaS, scalability, streaming
67-78
IEEE
Pfandzelter, Tobias
a59cad5f-b94f-4668-bf03-91b2fcb94f7a
Henning, Soren
e09ef4ea-8a2f-4d11-903b-db51d6371fcb
Schirmer, Trever
b644f928-93b5-4c4f-bfd5-9e7d0ebcc0b0
Hasselbring, Wilhelm
ee89c5c9-a900-40b1-82c1-552268cd01bd
Bermbach, David
7b2b8091-963d-423a-bb1f-9815f291fdf9
et al.
Pfandzelter, Tobias
a59cad5f-b94f-4668-bf03-91b2fcb94f7a
Henning, Soren
e09ef4ea-8a2f-4d11-903b-db51d6371fcb
Schirmer, Trever
b644f928-93b5-4c4f-bfd5-9e7d0ebcc0b0
Hasselbring, Wilhelm
ee89c5c9-a900-40b1-82c1-552268cd01bd
Bermbach, David
7b2b8091-963d-423a-bb1f-9815f291fdf9

Pfandzelter, Tobias, Henning, Soren and Schirmer, Trever , et al. (2022) Streaming vs. functions: a cost perspective on cloud event processing. In 2022 IEEE International Conference on Cloud Engineering (IC2E). IEEE. pp. 67-78 . (doi:10.1109/IC2E55432.2022.00015).

Record type: Conference or Workshop Item (Paper)

Abstract

In cloud event processing, data generated at the edge is processed in real-time by cloud resources. Both distributed stream processing (DSP) and Function-as-a-Service (FaaS) have been proposed to implement such event processing applications. FaaS emphasizes fast development and easy operation, while DSP emphasizes efficient handling of large data volumes. Despite their architectural differences, both can be used to model and implement loosely-coupled job graphs. In this paper, we consider the selection of FaaS and DSP from a cost perspective. We implement stateless and stateful workflows from the Theodolite benchmarking suite using cloud FaaS and DSP. In an extensive evaluation, we show how application type, cloud service provider, and runtime environment can influence the cost of application deployments and derive decision guidelines for cloud engineers.

This record has no associated files available for download.

More information

e-pub ahead of print date: 16 November 2022
Venue - Dates: 10th IEEE International Conference on Cloud Engineering, IC2E 2022, , Pacific Grove, United States, 2022-09-26 - 2022-09-30
Keywords: cloud data processing, FaaS, scalability, streaming

Identifiers

Local EPrints ID: 488781
URI: http://eprints.soton.ac.uk/id/eprint/488781
PURE UUID: 274c748e-2e4d-4473-8e57-5ef4ea7a6bcf
ORCID for Wilhelm Hasselbring: ORCID iD orcid.org/0000-0001-6625-4335

Catalogue record

Date deposited: 05 Apr 2024 16:38
Last modified: 10 Apr 2024 02:15

Export record

Altmetrics

Contributors

Author: Tobias Pfandzelter
Author: Soren Henning
Author: Trever Schirmer
Author: Wilhelm Hasselbring ORCID iD
Author: David Bermbach
Corporate Author: et al.

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×