Data Management Strategies for Microservices: Challenges and Future Research Directions

  • Authors

    • Dr. Ahmed Ben Ali Department of Mechanical Engineering, Tunis National Engineering College, Tunisia. Author

    DOI:

    https://doi.org/10.67228/30713315/IJAIDT-2019PI8Q1D

    Published 03-03-2019

  • Microservices, Data Management, Distributed Systems, Scalability, Research Directions

    Issue

    Vol. 2 No. 1 (2019)

    Section

    Articles

    How to Cite

    [1]
    A. B. Ali, “Data Management Strategies for Microservices: Challenges and Future Research Directions”, IJAIDT, vol. 2, no. 1, pp. 01–07, Mar. 2019, doi: 10.67228/30713315/IJAIDT-2019PI8Q1D.

  • Abstract

    Microservices architecture has gained significant traction in developing scalable, resilient, and flexible applications by decomposing systems into small, autonomous services. This approach allows for specialized data management strategies tailored to each service's unique requirements. However, the distributed nature of microservices introduces complex data management challenges that are not adequately addressed by traditional software engineering practices alone. This paper investigates the current state of data management within microservices architectures, identifies prevalent challenges, and outlines potential research directions to advance the field. Our study combines systematic literature reviews, analysis of open-source applications, and insights from industry practitioners to provide a holistic understanding of the data management landscape in microservices.

  • References

    [1] Newman, S. (2015). Building Microservices: Designing Fine-Grained Systems. O’Reilly Media.

    [2] Richardson, C. (2018). Microservices Patterns: With Examples in Java. Manning Publications.

    [3] Fowler, M., & Lewis, J. (2014). Microservices: A definition of this new architectural term. ThoughtWorks.

    [4] Dragoni, N., Giallorenzo, S., Lafuente, A. L., Mazzara, M., Montesi, F., Mustafin, R., & Safina, L. (2017). Microservices: Yesterday, today, and tomorrow. In Present and Ulterior Software Engineering (pp. 195–216). Springer.

    [5] Pahl, C. (2015). Containerization and the PaaS cloud. IEEE Cloud Computing, 2(3), 24–31.

    [6] Balalaie, A., Heydarnoori, A., & Jamshidi, P. (2016). Microservices architecture enables DevOps: Migration to a cloud-native architecture. IEEE Software, 33(3), 42–52.

    [7] Taibi, D., Lenarduzzi, V., & Pahl, C. (2018). Processes, motivations, and issues for migrating to microservices architectures: An empirical investigation. IEEE Cloud Computing, 5(5), 22–32.

    [8] Viggiato, M., Terra, R., Rocha, H., Valente, M. T., & Figueiredo, E. (2018). Microservices in practice: A survey study. arXiv preprint arXiv:1808.04836.

    [9] Parizi, R. M. (2018). Microservices as an evolutionary architecture of component-based development: A think-aloud study. arXiv preprint arXiv:1805.11757.

    [10] Gysel, M., Kölbener, L., Giersche, W., & Zimmermann, O. (2016). Service cutter: A systematic approach to service decomposition. European Conference on Service-Oriented and Cloud Computing.

    [11] Chen, L. (2018). Microservices: Architecting for continuous delivery and DevOps. IEEE International Conference on Software Architecture.

    [12] Villamizar, M., Garcés, O., Castro, H., Verano, M., Salamanca, L., Casallas, R., & Gil, S. (2015). Infrastructure cost comparison of running web applications in the cloud using AWS Lambda and monolithic and microservice architectures. IEEE/ACM CCGrid.

    [13] Soldani, J., Tamburri, D. A., & Van Den Heuvel, W. J. (2018). The pains and gains of microservices: A systematic grey literature review. Journal of Systems and Software, 146, 215–232.

    [14] Thönes, J. (2015). Microservices. IEEE Software, 32(1), 116–116. Zhang, Q., Chen, M., Li, L., & Jamshidi, P. (2017). Microservices: architecture, challenges, and practice. IEEE International Conference on Web Services.

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