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Model-Based Generation of Self-adaptive Cloud Services

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Book cover Cloud Computing and Services Science (CLOSER 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1073))

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Abstract

An important shift in software delivery is the definition of a cloud service as an independently deployable unit by following the microservices architectural style. Container virtualization facilitates development and deployment by ensuring independence from the runtime environment. Thus, cloud services are built as container-based systems - a set of containers that control the lifecycle of software and middleware components. However, using containers leads to a new paradigm for service development and operation: Self-service environments enable software developers to deploy and operate container-based systems on their own - you build it, you run it. Following this approach, more and more operational aspects are transferred towards the responsibility of software developers. In this work, we propose a concept for self-adaptive cloud services based on container virtualization in line with the microservices architectural style and present a model-based approach that assists software developers in building these services. Based on operational models specified by developers, the mechanisms required for self-adaptation are automatically generated. As a result, each container automatically adapts itself in a reactive, decentralized manner. We evaluate a prototype, which leverages the emerging TOSCA standard to specify operational behavior in a portable manner.

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Notes

  1. 1.

    https://mesosphere.github.io/marathon.

  2. 2.

    https://mesos.apache.org.

  3. 3.

    https://kubernetes.io.

  4. 4.

    https://12factor.net/config.

  5. 5.

    https://12factor.net.

  6. 6.

    https://www.consul.io.

  7. 7.

    https://github.com/coreos/etcd.

  8. 8.

    https://zookeeper.apache.org.

  9. 9.

    https://memcached.org.

  10. 10.

    A root process is a process with UNIX PID 1.

  11. 11.

    For example, POSIX signals are an inter-process communication mechanism typically used in Unix-like operating systems and employed by state of the art container runtime environments.

  12. 12.

    https://github.com/appc/spec.

  13. 13.

    https://www.opencontainers.org.

  14. 14.

    https://github.com/skynetservices/skydns.

  15. 15.

    https://github.com/Netflix/eureka.

  16. 16.

    https://github.com/ha/doozerd.

  17. 17.

    http://supervisord.org.

  18. 18.

    https://github.com/joyent/containerpilot.

  19. 19.

    https://docker.com.

  20. 20.

    https://hub.docker.com/_/registry.

  21. 21.

    https://github.com/hashicorp/envconsul.

  22. 22.

    http://freemarker.org.

  23. 23.

    https://github.com/spotify/docker-client.

  24. 24.

    https://hub.docker.com/_/php.

  25. 25.

    https://hub.docker.com/_/debian.

  26. 26.

    https://hub.docker.com/_/oraclelinux.

  27. 27.

    https://hub.docker.com/_/python.

  28. 28.

    https://www.serf.io.

  29. 29.

    http://microservices.io/patterns/microservice-chassis.html.

  30. 30.

    http://projects.spring.io/spring-cloud.

  31. 31.

    https://github.com/Netflix/Prana.

  32. 32.

    https://netflix.github.io.

  33. 33.

    https://github.com/gliderlabs/registrator.

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Authors and Affiliations

  1. Parallel and Distributed Computing Group, Reutlingen University, Alteburgstrasse 150, 72762, Reutlingen, Germany

    Stefan Kehrer & Wolfgang Blochinger

Authors
  1. Stefan Kehrer
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  2. Wolfgang Blochinger
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Correspondence to Stefan Kehrer .

Editor information

Editors and Affiliations

  1. Escola d’Enginyeria, Bellaterra, Barcelona, Spain

    Víctor Méndez Muñoz

  2. Columbia University, New York, USA

    Donald Ferguson

  3. Dublin City University, Dublin 9, Ireland

    Markus Helfert

  4. Free University of Bozen-Bolzano, Bolzano, Bolzano, Italy

    Claus Pahl

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Kehrer, S., Blochinger, W. (2019). Model-Based Generation of Self-adaptive Cloud Services. In: Muñoz, V., Ferguson, D., Helfert, M., Pahl, C. (eds) Cloud Computing and Services Science. CLOSER 2018. Communications in Computer and Information Science, vol 1073. Springer, Cham. https://doi.org/10.1007/978-3-030-29193-8_3

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  • DOI: https://doi.org/10.1007/978-3-030-29193-8_3

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  • Online ISBN: 978-3-030-29193-8

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