SeMoDe – Simulation and Benchmarking Pipeline for Function as a Service
Faculty/Professorship: | Distributed Systems |
Author(s): | Manner, Johannes ![]() |
Publisher Information: | Bamberg : Otto-Friedrich-Universität |
Year of publication: | 2021 |
Pages: | 56 |
Series ; Volume: | Bamberger Beiträge zur Wirtschaftsinformatik und Angewandten Informatik ; 105 |
Language(s): | English |
DOI: | 10.20378/irb-52238 |
Licence: | Creative Commons - CC BY - Attribution 4.0 International |
URN: | urn:nbn:de:bvb:473-irb-522386 |
Abstract: | Cloud computing started with the promise of delivering computing resources elastically at scale, pay per use and on demand self-service to name a few capabilities. In early 2016, Amazon Web Services (AWS) launched a new product called AWS Lambda which started the so called serverless hype and established a new cloud delivery model, namely Function as a Service (FaaS). FaaS offerings keep the promise of delivering computing resources on demand. They dynamically scale up and down function instances and introduce the most fine-grained billing model across all as-a-service offerings by accounting on a milliseconds basis. Despite this flexibility and the possibility to concentrate on the business functionality, a FaaS user loses operational control. Only a few configuration options remain to tune the functions. The first pay-as-you-go billing model raises new questions for performance-cost trade-offs. In order to choose a suitable configuration dependent on the use case and get a solid understanding of performance impact of FaaS platforms, SeMoDe implements a benchmarking and simulation pipeline. It calibrates a physical developer machine, simulates the function in different settings which are comparable to those of cloud offerings and enables a decision guidance to choose an appropriate configuration when deploying it. Based on a Structured Literature Review (SLR) to show the benchmarking and simulation efforts, I suggest a checklist for conducting fair, repeatable and meaningful benchmarks with a focus on documenting the experiments. |
GND Keywords: | Cloud Computing; Function as a Service; Benchmarking; Simulation |
Keywords: | Cloud Computing, Function as a Service, Benchmarking, Simulation |
DDC Classification: | 004 Computer science |
RVK Classification: | ST 233 |
Type: | Workingpaper |
URI: | https://fis.uni-bamberg.de/handle/uniba/52238 |
Release Date: | 10. December 2021 |
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originated at the
University of Bamberg
University of Bamberg