Skip to main content

Performance Analysis of Monolithic and Micro Service Architectures – Containers Technology

  • Conference paper
  • First Online:
Book cover Trends and Applications in Software Engineering (CIMPS 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 865))

Included in the following conference series:

Abstract

Comparative analysis of the performance of hardware resources, between Monolithic Architecture and Micro services Architecture, using virtualization technology based on development and production environments. Today, the new trend is the development and/or deployment of applications in the Cloud, in this aspect, monolithic applications have flexibility, scalability, maintainability and performance limitations. On the other hand, the focus of Microservices adapts to new trends and solves these limitations. Meanwhile, virtualization with virtual machines is currently not efficient enough with hardware resources. With the appearance of containers, this problem is solved due to its functioning characteristics as independent processes and resources optimization. Now, two scenarios are presented, the first consisting of a Web application based on a Monolithic Architecture that is executed in a Kernel based Virtual Machine - KVM and the second scenario shows the same Web application, this time, based on a Micro services Architecture and running in containers. Each scenario is subjected to the same stress tests; the generated data are recorded in “log” files for further analysis. The hardware resources are the same for both scenarios. The comparison of these scenarios helps to identify the efficiency of the Application and the hardware resources, as well as the development and/or deployment of Applications. This can be improved with the use of Microservices and Containers. In addition, the reduction of costs that would imply the optimization in the resources. For greater reliability in the interpretation of the data, two analysis tools were used: JMeter and NewRelic. Finally, the two resulting cases from the analysis are shown, each case being considered due to the feasibility of the same depending on the needs and availability of resources.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    Works at the hardware level without an intermediary Operating System.

References

  1. Nielsen, C.D.: Investigate availability and maintainability within a microservice architecture (2015). http://cs.au.dk/fileadmin/site_files/cs/AA_pdf/ClausDNielsen_rapport.pdf

  2. Sun, L., Li, Y., Memon, R.A.: An open IoT framework based on microservices architecture. China Commun. 14, 154–162 (2017)

    Article  Google Scholar 

  3. Kratzke, N.: About microservices, containers and their underestimated impact on network performance. In: ResearchGate, Lubeck, Germany (2015)

    Google Scholar 

  4. Fowler, M., Lewis, J.: Microservices. https://martinfowler.com/articles/microservices.html

  5. Fussell, M.: Why a microservices approach to building applications? https://docs.microsoft.com/es-es/azure/service-fabric/service-fabric-overview-microservices

  6. Newman, S.: Building Microservices: Designing Fine-Grained Systems. O’Reilly Media, Inc., Sebastopol (2015)

    Google Scholar 

  7. Felter, W., Ferreira, A., Rajamony, R., Rubio, J.: An updated performance comparison of virtual machines and linux containers. In: 2015 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS), pp. 171–172. IEEE (2015)

    Google Scholar 

  8. Bartholomew, D.: Qemu: a multihost, multitarget emulator. Linux J. 2006, 3 (2006)

    Google Scholar 

  9. Prashant, D.: A survey of performance comparison between virtual machines and containers. 4, (2016)

    Google Scholar 

  10. Scott, J.: A practical guide to microservices and containers: mastering the cloud, data and digital transformation (2017)

    Google Scholar 

  11. Vaughan-Nichols, S.J.: New approach to virtualization is a lightweight. Computer 39, 12–14 (2006)

    Article  Google Scholar 

  12. Khazaei, H., Barna, C., Beigi-Mohammadi, N., Litoiu, M.: Efficiency analysis of provisioning microservices. In: 2016 IEEE International Conference on Cloud Computing Technology and Science (CloudCom), pp. 261–268 (2016)

    Google Scholar 

  13. Stubbs, J., Moreira, W., Dooley, R.: Distributed systems of microservices using docker and serfnode. In: 2015 7th International Workshop on Science Gateways, pp. 34–39 (2015)

    Google Scholar 

  14. Pahl, C.: Containerization and the PaaS Cloud. IEEE Cloud Comput. 2, 24–31 (2015)

    Article  Google Scholar 

  15. Gerlach, W., Tang, W., Keegan, K., Harrison, T., Wilke, A., Bischof, J., D’Souza, M., Devoid, S., Murphy-Olson, D., Desai, N., et al.: Skyport: container-based execution environment management for multi-cloud scientific workflows. In: Proceedings of the 5th International Workshop on Data-Intensive Computing in the Clouds, pp. 25–32. IEEE Press (2014)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Freddy Tapia .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Saransig, A., Tapia, F. (2019). Performance Analysis of Monolithic and Micro Service Architectures – Containers Technology. In: Mejia, J., Muñoz, M., Rocha, Á., Peña, A., Pérez-Cisneros, M. (eds) Trends and Applications in Software Engineering. CIMPS 2018. Advances in Intelligent Systems and Computing, vol 865. Springer, Cham. https://doi.org/10.1007/978-3-030-01171-0_25

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-01171-0_25

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-01170-3

  • Online ISBN: 978-3-030-01171-0

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics