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Latest Image Recommendation Method for Automatic Base Image Update in Dockerfile

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Service-Oriented Computing (ICSOC 2020)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 12571))

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Abstract

In recent years, an application deployment method using Docker container has attracted attention by researchers. Docker containers are fast and lightweight, can improve the portability and reproducibility of applications, and are thus often used with CI/CD and DevOps to accelerate the release cycle. However, if a Docker image is not updated, problems such as security risks or a lack of the latest features may occur. Therefore, in this paper, we propose a method for automatically updating the base image to the latest version when the image is considered to be the old version. Our method extracts the information of the base image from the Dockerfile described by the user, and infers the version of the base image that is considered to be certainly used. By applying our method, the user can regularly update the base image. Based on the evaluation result, we confirmed that our method recommends an approximately correct version to the users.

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Notes

  1. 1.

    https://www.docker.com/.

  2. 2.

    https://hub.docker.com/.

  3. 3.

    https://semver.org/.

  4. 4.

    https://docs.docker.com/engine/reference/builder/.

  5. 5.

    https://github.com/.

  6. 6.

    https://git-scm.com/.

  7. 7.

    https://about.gitlab.com/.

  8. 8.

    https://docs.docker.com/registry/spec/api/.

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Author information

Authors and Affiliations

  1. Software Laboratory, FUJITSU LABORATORIES LTD., 4-1-1 Kamikodanaka, Nakahara, Kawasaki, Kanagawa, 211–8588, Japan

    Shinya Kitajima & Atsuji Sekiguchi

Authors
  1. Shinya Kitajima
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  2. Atsuji Sekiguchi
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Corresponding author

Correspondence to Shinya Kitajima .

Editor information

Editors and Affiliations

  1. Zayed University, Dubai, United Arab Emirates

    Eleanna Kafeza

  2. University of New South Wales, Sydney, NSW, Australia

    Boualem Benatallah

  3. IIT National Research Council C.N.R., Pisa, Italy

    Fabio Martinelli

  4. Zayed University, Dubai, United Arab Emirates

    Hakim Hacid

  5. University of Sydney, Darlington, NSW, Australia

    Athman Bouguettaya

  6. Ernst & Young AI Lab, San Jose, CA, USA

    Hamid Motahari

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Kitajima, S., Sekiguchi, A. (2020). Latest Image Recommendation Method for Automatic Base Image Update in Dockerfile. In: Kafeza, E., Benatallah, B., Martinelli, F., Hacid, H., Bouguettaya, A., Motahari, H. (eds) Service-Oriented Computing. ICSOC 2020. Lecture Notes in Computer Science(), vol 12571. Springer, Cham. https://doi.org/10.1007/978-3-030-65310-1_40

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  • DOI: https://doi.org/10.1007/978-3-030-65310-1_40

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-65309-5

  • Online ISBN: 978-3-030-65310-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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