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

Authors: Wito Delnat, Thomas Heyman, Wouter Joosen, Davy Preuveneers, Ansar Rafique, Eddy Truyen, and Dimitri Van Landuyt

Published in: DARTS, Volume 4, Issue 1, Special Issue of the 13th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 2018)


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.

Cite as

Wito Delnat, Thomas Heyman, Wouter Joosen, Davy Preuveneers, Ansar Rafique, Eddy Truyen, and Dimitri Van Landuyt. K8-Scalar: a workbench to compare autoscalers for container-orchestrated services (Artifact). In Special Issue of the 13th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS 2018). Dagstuhl Artifacts Series (DARTS), Volume 4, Issue 1, pp. 2:1-2:6, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)


Copy BibTex To Clipboard

@Article{delnat_et_al:DARTS.4.1.2,
  author =	{Delnat, Wito and Heyman, Thomas and Joosen, Wouter and Preuveneers, Davy and Rafique, Ansar and Truyen, Eddy and Van Landuyt, Dimitri},
  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},
  editor =	{Delnat, Wito and Heyman, Thomas and Joosen, Wouter and Preuveneers, Davy and Rafique, Ansar and Truyen, Eddy and Van Landuyt, Dimitri},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DARTS.4.1.2},
  URN =		{urn:nbn:de:0030-drops-87118},
  doi =		{10.4230/DARTS.4.1.2},
  annote =	{Keywords: Container orchestration, autoscalers, experimentation exemplar}
}
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