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Horizontal Scaling in Cloud Using Contextual Bandits

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Euro-Par 2021: Parallel Processing (Euro-Par 2021)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12820))

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Abstract

One characteristic of the Cloud is elasticity: it provides the ability to adapt resources allocated to applications as needed at runtime. This capacity relies on scaling and scheduling. In this article online horizontal scaling is studied. The aim is to determine dynamically applications deployment parameters and to adjust them in order to respect a Quality of Service level without any human parameters tuning. This work focuses on CaaS (container-based) environments and proposes an algorithm based on contextual bandits (HSLinUCB). Our proposal has been evaluated on a simulated platform and on a real Kubernetes’s platform. The comparison has been done with several baselines: threshold based auto-scaler, Q-Learning, and Deep Q-Learning. The results show that HSLinUCB gives very good results compared to other baselines, even when used without any training period.

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Notes

  1. 1.

    https://aws.amazon.com/ec2/autoscaling/.

  2. 2.

    https://docs.openstack.org/senlin/latest/tutorial/autoscaling.html.

  3. 3.

    https://aws.amazon.com/blogs/aws/new-predictive-scaling-for-ec2-powered-by-machine-learning/.

  4. 4.

    https://github.com/Orange-OpenSource/HSLinUCB.

  5. 5.

    https://kubernetes.io/docs/concepts/configuration/manage-resources-containers/.

  6. 6.

    https://github.com/kubernetes/kubernetes/tree/master/pkg/controller/podautoscaler.

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Authors and Affiliations

  1. Orange Labs, Lannion, France

    David Delande, Raphaël Feraud & André Bottaro

  2. IRIT, Université de Toulouse, 31062, Toulouse, France

    David Delande, Patricia Stolf & Jean-Marc Pierson

Authors
  1. David Delande
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  2. Patricia Stolf
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  3. Raphaël Feraud
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  4. Jean-Marc Pierson
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  5. André Bottaro
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Corresponding author

Correspondence to David Delande .

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Editors and Affiliations

  1. Universidade de Lisboa, Lisbon, Portugal

    Leonel Sousa

  2. Universidade de Lisboa, Lisbon, Portugal

    Nuno Roma

  3. Universidade de Lisboa, Lisbon, Portugal

    Pedro Tomás

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Delande, D., Stolf, P., Feraud, R., Pierson, JM., Bottaro, A. (2021). Horizontal Scaling in Cloud Using Contextual Bandits. In: Sousa, L., Roma, N., Tomás, P. (eds) Euro-Par 2021: Parallel Processing. Euro-Par 2021. Lecture Notes in Computer Science(), vol 12820. Springer, Cham. https://doi.org/10.1007/978-3-030-85665-6_18

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  • DOI: https://doi.org/10.1007/978-3-030-85665-6_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-85664-9

  • Online ISBN: 978-3-030-85665-6

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