skip to main content
10.1145/3492323.3495624acmconferencesArticle/Chapter ViewAbstractPublication PagesuccConference Proceedingsconference-collections
research-article

Adaptive brokerage framework for the cloud with functional testing

Published:07 February 2022Publication History

ABSTRACT

In this paper, we present an Adaptive Brokerage for the Cloud (ABC) that can be used to simplify application deployment, monitoring and management processes in the cloud. The broker uses modern cloud infrastructure automation tools to test, deploy, monitor and optimise cloud resources. We used an e-commerce application to evaluate the entire functionality of the broker, we found out that different deployment options such as single-tier vs two-tier lead to interesting hardware and application performance insights. These insights are used to make effective infrastructure optimisation decisions.

References

  1. AWS. [n.d.]. Autoscaling. https://aws.amazon.com/autoscaling/Google ScholarGoogle Scholar
  2. Azure. [n.d.]. Autoscale. https://azure.microsoft.com/en-gb/features/autoscale/Google ScholarGoogle Scholar
  3. Adam Barker, Blesson Varghese, and Long Thai. 2015. Cloud services brokerage: A survey and research roadmap. In 2015 IEEE 8th international conference on cloud computing. IEEE, 1029--1032.Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Yevgeniy Brikman. 2019. Terraform: Up & Running: Writing Infrastructure as Code. O'Reilly Media.Google ScholarGoogle Scholar
  5. Roy T Fielding and Gail Kaiser. 1997. The Apache HTTP server project. IEEE Internet Computing 1, 4 (1997), 88--90.Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. GCP. [n.d.]. Autoscaling goups. https://cloud.google.com/compute/docs/autoscalerGoogle ScholarGoogle Scholar
  7. Stella Gatziu Grivas, Tripathi Uttam Kumar, and Holger Wache. 2010. Cloud broker: Bringing intelligence into the cloud. In 2010 IEEE 3rd International Conference on Cloud Computing. IEEE, 544--545.Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Infracost. [n.d.]. Cloud cost estimates for Infrastructure as Code. https://www.infracost.io/Google ScholarGoogle Scholar
  9. Kief Morris. 2016. Infrastructure as code: managing servers in the cloud. O'Reilly.Google ScholarGoogle Scholar
  10. Syeda Noor Zehra Naqvi, Sofia Yfantidou, and Esteban Zimányi. 2017. Time series databases and influxdb. Studienarbeit, Université Libre de Bruxelles (2017), 12.Google ScholarGoogle Scholar
  11. Przemyslaw Pawluk, Bradley Simmons, Michael Smit, Marin Litoiu, and Serge Mankovski. 2012. Introducing STRATOS: A cloud broker service. In 2012 IEEE fifth international conference on cloud computing. IEEE, 891--898.Google ScholarGoogle Scholar
  12. Pierluigi Riti. 2018. Monitoring in GCP. In Pro DevOps with Google Cloud Platform. Springer, 165--190.Google ScholarGoogle Scholar
  13. Robert Griesemer Rob Pike and Ken Thompson. [n.d.]. Go is an open source programming language that makes it easy to build simple, reliable, and efficient software. https://golang.org/Google ScholarGoogle Scholar
  14. Krzysztof Rzadca, Pawel Findeisen, Jacek Swiderski, Przemyslaw Zych, Przemyslaw Broniek, Jarek Kusmierek, Pawel Nowak, Beata Strack, Piotr Witusowski, Steven Hand, et al. 2020. Autopilot: workload autoscaling at Google. In Proceedings of the Fifteenth European Conference on Computer Systems. 1--16.Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Hassan Jamil Syed, Abdullah Gani, Raja Wasim Ahmad, Muhammad Khurram Khan, and Abdelmuttlib Ibrahim Abdalla Ahmed. 2017. Cloud monitoring: A review, taxonomy, and open research issues. Journal of Network and Computer Applications 98 (2017), 11--26.Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Hoda Taheri, Faeze Ramezani, Neda Mohammadi, Parisa Khoshdel, Bahareh Taghavi, Neda Khorasani, Saeid Abrishami, and Abbas Rasoolzadegan. 2021. Cloud broker: a systematic mapping study. arXiv preprint arXiv:2102.12717 (2021).Google ScholarGoogle Scholar
  17. Sami Yangui, Iain-James Marshall, Jean-Pierre Laisne, and Samir Tata. 2014. CompatibleOne: The open source cloud broker. Journal of Grid Computing 12, 1 (2014), 93--109.Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Josh Padnick Yevgeniy Brikman. [n.d.]. Automated tests for your infrastructure code. https://github.com/gruntwork-io/terratestGoogle ScholarGoogle Scholar

Index Terms

  1. Adaptive brokerage framework for the cloud with functional testing
          Index terms have been assigned to the content through auto-classification.

          Recommendations

          Comments

          Login options

          Check if you have access through your login credentials or your institution to get full access on this article.

          Sign in
          • Published in

            cover image ACM Conferences
            UCC '21: Proceedings of the 14th IEEE/ACM International Conference on Utility and Cloud Computing Companion
            December 2021
            256 pages
            ISBN:9781450391634
            DOI:10.1145/3492323

            Copyright © 2021 ACM

            Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

            Publisher

            Association for Computing Machinery

            New York, NY, United States

            Publication History

            • Published: 7 February 2022

            Permissions

            Request permissions about this article.

            Request Permissions

            Check for updates

            Qualifiers

            • research-article

            Acceptance Rates

            Overall Acceptance Rate38of125submissions,30%
          • Article Metrics

            • Downloads (Last 12 months)28
            • Downloads (Last 6 weeks)1

            Other Metrics

          PDF Format

          View or Download as a PDF file.

          PDF

          eReader

          View online with eReader.

          eReader