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When quoting this document, please refer to the following
DOI: 10.4230/DARTS.4.1.2
URN: urn:nbn:de:0030-drops-87118
URL: http://drops.dagstuhl.de/opus/volltexte/2018/8711/
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Delnat, Wito ; Heyman, Thomas ; Joosen, Wouter ; Preuveneers, Davy ; Rafique, Ansar ; Truyen, Eddy ; Van Landuyt, Dimitri

K8-Scalar: a workbench to compare autoscalers for container-orchestrated services (Artifact)

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DARTS-4-1-2.pdf (0.4 MB)
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DARTS-4-1-2-artifact-f7a3f4aa8cc0f64c8b8f0b162bda8816.tgz (190 MB)


Abstract

This artifact is an easy-to-use and extensible workbench exemplar, named K8-Scalar, which allows researchers to implement and evaluate different self-adaptive approaches to autoscaling container-orchestrated services. The workbench is based on Docker, a popular technology for easing the deployment of containerized software that also has been positioned as an enabler for reproducible research. The workbench also relies on a container orchestration framework: Kubernetes (K8s), the de-facto industry standard for orchestration and monitoring of elastically scalable container-based services. Finally, it integrates and extends Scalar, a generic testbed for evaluating the scalability of large-scale systems with support for evaluating the performance of autoscalers for database clusters. The associated scholarly paper presents (i) the architecture and implementation of K8-Scalar and how a particular autoscaler can be plugged in, (ii) sketches the design of a Riemann-based autoscaler for database clusters, (iii) illustrates how to design, setup and analyze a series of experiments to configure and evaluate the performance of this autoscaler for a particular database (i.e., Cassandra) and a particular workload type, (iv) and validates the effectiveness of K8-scalar as a workbench for accurately comparing the performance of different auto-scaling strategies. Future work includes extending K8-Scalar with an improved research data management repository.

BibTeX - Entry

@Article{delnat_et_al:DARTS:2018:8711,
  author =	{Wito Delnat and Thomas Heyman and Wouter Joosen and Davy Preuveneers and Ansar Rafique and Eddy Truyen and Dimitri Van Landuyt},
  title =	{{K8-Scalar: a workbench to compare autoscalers for container-orchestrated services (Artifact)}},
  pages =	{2:1--2:6},
  journal =	{Dagstuhl Artifacts Series},
  ISSN =	{2509-8195},
  year =	{2018},
  volume =	{4},
  number =	{1},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2018/8711},
  URN =		{urn:nbn:de:0030-drops-87118},
  doi =		{10.4230/DARTS.4.1.2},
  annote =	{Keywords: Container orchestration, autoscalers, experimentation exemplar}
}

Keywords: Container orchestration, autoscalers, experimentation exemplar
Seminar: DARTS, Volume 4, Issue 1
Related Scholarly Article: https://doi.org/10.1145/3194133.3194162
Issue Date: 2018
Date of publication: 16.05.2018


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