FIFE: an Infrastructure-as-code based Framework for Evaluating VM instances from multiple clouds

Yuhui Lin, Jack Briggs, Adam David Barker

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abstract

To choose an optimal VM, Cloud users often need to step a process of evaluating the performance of VMs by benchmarking or running a black-box search technique such as Bayesian optimisation. To facilitate the process, we develop a generic and highly configurable Framework with Infrastructure-as-Code (IaC) support For VM Evaluation (FIFE). FIFE abstract the process as a searcher, selector, deployer and interpreter. It allows users to specify the target VM sets and evaluation objectives with JSON to automate the process. We demonstrate the use of the framework by setting up of a Bayesian optimization VM searching system. We evaluate the system with various experimental setups, i.e. different combinations of cloud provider numbers and parallel search. The results show that the search efficiency remains the same for the case when the search space is consist of VM from multiple cloud providers, and the parallel search can significantly reduce search time when the number of parallelisation is set properly.
Original languageEnglish
Title of host publication13th IEEE/ACM International Conferencce on Utility and Cloud Computing
PublisherIEEE Computer Society
DOIs
Publication statusPublished - 8 Dec 2020
Event13th IEEE/ACM International Conferencce on Utility and Cloud Computing (UCC 2020) - Online
Duration: 7 Dec 202010 Dec 2020
Conference number: 13
https://www.cs.le.ac.uk/events/UCC2020/index.htm

Conference

Conference13th IEEE/ACM International Conferencce on Utility and Cloud Computing (UCC 2020)
Abbreviated titleUCC 2020
Period7/12/2010/12/20
Internet address

Keywords

  • Cloud computing
  • Infrastructure-as-Code
  • VM evaluation framework
  • Bayesian optimization

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