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Service Dependency Graph Analysis in Microservice Architecture

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Perspectives in Business Informatics Research (BIR 2020)

Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 398))

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Abstract

Since microservices have become popular, we see increasingly complex service architectures emerging. Microservice systems, while being well scalable, flexible, and highly available, do not tackle the reliability aspects fully. While the container orchestration solutions like Kubernetes contribute to the fault tolerance against the network or infrastructural failures, the probability of the mistake in the architectural design still exists. Several graph-based anomaly detection approaches could be employed to proactively detect critical nodes and design anti-patterns. The paper, on a simplified example of the microservices-based system, demonstrates the application of graph algorithms that provide direction in assessing the quality of the underlying architecture.

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Author information

Authors and Affiliations

  1. Institute of Applied Computer Systems, Riga Technical University, Riga, Latvia

    Edgars Gaidels & Marite Kirikova

Authors
  1. Edgars Gaidels
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  2. Marite Kirikova
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Corresponding author

Correspondence to Edgars Gaidels .

Editor information

Editors and Affiliations

  1. BabeÈ™-Bolyai University, Cluj Napoca, Romania

    Robert Andrei Buchmann

  2. University of Camerino, Camerino, Italy

    Andrea Polini

  3. Linköping University, Linköping, Sweden

    Björn Johansson

  4. University of Vienna, Vienna, Austria

    Dimitris Karagiannis

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Gaidels, E., Kirikova, M. (2020). Service Dependency Graph Analysis in Microservice Architecture. In: Buchmann, R.A., Polini, A., Johansson, B., Karagiannis, D. (eds) Perspectives in Business Informatics Research. BIR 2020. Lecture Notes in Business Information Processing, vol 398. Springer, Cham. https://doi.org/10.1007/978-3-030-61140-8_9

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  • DOI: https://doi.org/10.1007/978-3-030-61140-8_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-61139-2

  • Online ISBN: 978-3-030-61140-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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