Advertisement

Abstract

Responding to the rising wave of demands brought forward by the digital economy requires injecting accelerated agility and speed into the software development life cycle. To build a technology stack that helps meet this demand, the DevOps methodology bridges the gap between software developers and the IT maintenance and operation professionals, by combining them into a unified team aligned around shared business goals, based on automation solutions that support rapid response to user demand while preserving stability and reliability. The concept of DevOps with its high pressure on automation, extended from application development to the maintenance and operation infrastructure, fosters more in-depth attention to the performance of infrastructure management.

This paper discusses how dynamic orchestration of infrastructure delivery in Cloud environment accelerates agility in the DevOps process, by enabling rapid deployment of dynamic workload.

Keywords

DevOps Infrastructure agility Dynamic orchestration 

Notes

Acknowledgments

The authors are grateful to Alessandro Menti and Giacomo Tirabassi of Kiratech, Italy, for the precious comments they provided on the intent and contents of this paper.

References

  1. 1.
    Armbrust, M., et al.: A view of cloud computing. Commun. ACM 53(4), 50–58 (2010)CrossRefGoogle Scholar
  2. 2.
    The Kubernetes Authors: Automated container deployment, scaling, and management (2018). https://kubernetes.io/
  3. 3.
    Red Hat OpenShift: Automated container deployment, scaling, and management (2018). https://www.openshift.com/
  4. 4.
    Balalaie, A., Heydarnoori, A., Jamshidi, P.: Microservices architecture enables devops: migration to a cloud-native architecture. IEEE Softw. 33(3), 42–52 (2016)CrossRefGoogle Scholar
  5. 5.
    Bang, S.K., Chung, S., Choh, Y., Dupuis, M.: A grounded theory analysis of modern web applications: knowledge, skills, and abilities for DevOps. In: Proceedings of the 2nd Annual Conference on Research in Information Technology, pp. 61–62. ACM (2013)Google Scholar
  6. 6.
    de Bayser, M., Azevedo, L.G., Cerqueira, R.: Researchops: the case for DevOps in scientific applications. In: 2015 IFIP/IEEE International Symposium on Integrated Network Management (IM), pp. 1398–1404. IEEE (2015)Google Scholar
  7. 7.
    Calheiros, R.N., Masoumi, E., Ranjan, R., Buyya, R.: Workload prediction using ARIMA model and its impact on cloud applications QoS. IEEE Trans. Cloud Comput. 3(4), 449–458 (2015)CrossRefGoogle Scholar
  8. 8.
    Chapman, D.: Introduction to DevOps on AWS (2014). https://aws.amazon.com/whitepapers/introduction-to-devops-on-aws/
  9. 9.
    Davis, J., Daniels, R.: Effective DevOps: Building a Culture of Collaboration, Affinity, and Tooling at Scale. O’Reilly Media Inc., Sebastopol (2016)Google Scholar
  10. 10.
    Debois, P.: Agile infrastructure and operations: how infra-gile are you? In: Agile 2008 Conference, pp. 202–207. IEEE (2008)Google Scholar
  11. 11.
    Dragoni, N., et al.: Microservices: yesterday, today, and tomorrow. In: Mazzara, M., Meyer, B. (eds.) Present and Ulterior Software Engineering, pp. 195–216. Springer, Cham (2017).  https://doi.org/10.1007/978-3-319-67425-4_12CrossRefGoogle Scholar
  12. 12.
    Dragoni, N., Lanese, I., Larsen, S.T., Mazzara, M., Mustafin, R., Safina, L.: Microservices: how to make your application scale. In: Petrenko, A.K., Voronkov, A. (eds.) PSI 2017. LNCS, vol. 10742, pp. 95–104. Springer, Cham (2018).  https://doi.org/10.1007/978-3-319-74313-4_8CrossRefGoogle Scholar
  13. 13.
    Ebert, C., Gallardo, G., Hernantes, J., Serrano, N.: DevOps. IEEE Softw. 33(3), 94–100 (2016)CrossRefGoogle Scholar
  14. 14.
    Erich, F., Amrit, C., Daneva, M.: A mapping study on cooperation between information system development and operations. In: Jedlitschka, A., Kuvaja, P., Kuhrmann, M., Männistö, T., Münch, J., Raatikainen, M. (eds.) PROFES 2014. LNCS, vol. 8892, pp. 277–280. Springer, Cham (2014).  https://doi.org/10.1007/978-3-319-13835-0_21CrossRefGoogle Scholar
  15. 15.
    Fitzgerald, B., Stol, K.J.: Continuous software engineering and beyond: trends and challenges. In: Proceedings of the 1st International Workshop on Rapid Continuous Software Engineering, pp. 1–9. ACM (2014)Google Scholar
  16. 16.
    Fowler, M.: Continuous delivery (2006). https://martinfowler.com/books/continuousDelivery.html
  17. 17.
    Fowler, M.: Continuous integration (2006). https://www.martinfowler.com/articles/continuousIntegration.html
  18. 18.
    Ho, V.: Bringing DevOps to the masses with Microsoft’s Donovan Brown (2016). https://blogs.microsoft.com/firehose/2016/11/29/bringing-devops-to-the-masses-with-microsofts-donovan-brown/
  19. 19.
    Humble, J., Farley, D.: Continuous Delivery: Reliable Software Releases Through Build, Test, and Deployment Automation. Pearson Education, London (2010)Google Scholar
  20. 20.
    Docker Inc.: Docker datacenter enables DevOps (2018). https://www.docker.com/use-cases/devops
  21. 21.
    Jabbari, R., bin Ali, N., Petersen, K., Tanveer, B.: What is DevOps?: A systematic mapping study on definitions and practices. In: Proceedings of the Scientific Workshop Proceedings of XP2016, p. 12. ACM (2016)Google Scholar
  22. 22.
    Khan, A.: Key characteristics of a container orchestration platform to enable a modern application. IEEE Cloud Comput. 4(5), 42–48 (2017)CrossRefGoogle Scholar
  23. 23.
    Kim, G., Debois, P., Willis, J., Humble, J.: The DevOps Handbook: How to Create World-Class Agility, Reliability, and Security in Technology Organizations. IT Revolution, Portland (2016)Google Scholar
  24. 24.
    Matthew Skelton, M.P.: Devops topologies. https://web.devopstopologies.com/anti-types
  25. 25.
    Morris, K.: Infrastructure as Code: Managing Servers in the Cloud. O’Reilly Media Inc., Sebastopol (2016)Google Scholar
  26. 26.
    Numenta: The numenta anomaly benchmark (2018). https://github.com/numenta/NAB
  27. 27.
    Pahl, C.: Containerization and the PaaS cloud. IEEE Cloud Comput. 2(3), 24–31 (2015)CrossRefGoogle Scholar
  28. 28.
    Radcliffe, R.: DevOps today: what does it mean to you (2018). http://schedule.interop.com/session/devops-today-what-does-it-mean-to-you-/852618
  29. 29.
    rakyll/hey: rakyll/hey (2018). https://github.com/rakyll/hey
  30. 30.
    Salehinejad, H., Baarbe, J., Sankar, S., Barfett, J., Colak, E., Valaee, S.: Recent advances in recurrent neural networks. arXiv preprint arXiv:1801.01078 (2017)
  31. 31.
    Thönes, J.: Microservices. IEEE Softw. 32(1), 116 (2015)CrossRefGoogle Scholar
  32. 32.
  33. 33.
    Virmani, M.: Understanding DevOps & bridging the gap from continuous integration to continuous delivery. In: 2015 Fifth International Conference on Innovative Computing Technology (INTECH), pp. 78–82. IEEE (2015)Google Scholar
  34. 34.
    Zhao, Z., Chen, W., Wu, X., Chen, P.C., Liu, J.: LSTM network: a deep learning approach for short-term traffic forecast. IET Intell. Transport Syst. 11(2), 68–75 (2017)CrossRefGoogle Scholar
  35. 35.
    Zhu, L., Bass, L., Champlin-Scharff, G.: DevOps and its practices. IEEE Softw. 33(3), 32–34 (2016)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.University of PaduaPaduaItaly

Personalised recommendations