IDEAS home Printed from https://ideas.repec.org/h/spr/prochp/978-3-031-56576-2_3.html
   My bibliography  Save this book chapter

Influence of Microservice Design Patterns for Data Science Workflows

In: Artificial Intelligence Tools and Applications in Embedded and Mobile Systems

Author

Listed:
  • Christoph Schröer

    (University of Oldenburg)

  • Raphael Holtmann

    (University of Oldenburg)

  • Jorge Marx Gómez

    (University of Oldenburg)

  • Hergen Pargmann

    (Jade Hochschule)

Abstract

Due to several advantages like scalability or fast development cycles, microservice architectures could also support the development and deployment of data science workflows. In recent literature, many patterns for the development of microservice architectures have evolved mainly for transaction-oriented applications. This paper investigates suitable design patterns for data science workflows. For this, we will implement a data science workflow using a microservice architecture, implemented with two different patterns, the orchestrator and choreography patterns, and with synchronous and asynchronous communication styles. Experiments are conducted to compare these architecture patterns with workloads of volume and velocity criteria. Orchestrator pattern performs best and could be used for inference, while choreography pattern could be used for training of machine learning models due to asynchronous communication. Our paper can provide practical support to software architects in implementing data science workflows using appropriate microservice design patterns. Also, we have now combined microservices pattern with data science workflows.

Suggested Citation

  • Christoph Schröer & Raphael Holtmann & Jorge Marx Gómez & Hergen Pargmann, 2024. "Influence of Microservice Design Patterns for Data Science Workflows," Progress in IS, in: Jorge Marx Gómez & Anael Elikana Sam & Devotha Godfrey Nyambo (ed.), Artificial Intelligence Tools and Applications in Embedded and Mobile Systems, pages 23-32, Springer.
    • Handle: RePEc:spr:prochp:978-3-031-56576-2_3
    DOI: 10.1007/978-3-031-56576-2_3
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:prochp:978-3-031-56576-2_3. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.