Q8S: Emulation of Heterogeneous Kubernetes Clusters Using QEMU

Kubernetes has emerged as the industry standard for container orchestration in cloud environments, with its scheduler dynamically placing container instances across cluster nodes based on predefined rules and algorithms. Various efforts have been made to extend and improve upon the Kubernetes scheduler. However, as the majority of Kubernetes clusters operate on homogeneous hardware, most scheduling algorithms are also only developed for homogeneous systems. Heterogeneous infrastructures, which include IoT devices or specialized hardware, have become more widespread and require specialized tuning to optimize workload assignment, for which researchers and developers working on scheduling systems require access to heterogeneous hardware for development and testing; such data may not be available. While simulations such as CloudSim or K8sSim can provide insights, the level of detail they can offer to validate new schedulers is limited, as they are only simulations. To address this, we introduce Q8S, a tool for emulating heterogeneous Kubernetes clusters including x86_64 and ARM64 architectures on OpenStack using QEMU. Emulations created through Q8S provide a higher level of detail than simulations and can be used to train machine learning scheduling algorithms. By providing an environment capable of executing real workloads, Q8S enables researchers and developers to test and refine their scheduling algorithms, ultimately leading to more efficient and effective heterogeneous cluster management. We release our implementation of Q8S as open source.

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Publication Details

Journal
Algorithms
Published
2025-05-29
DOI
https://doi.org/10.3390/a18060324
Primary Topic
Cloud Computing and Resource Management
Type
article
Field-Weighted Citation Impact
0.00

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article

Q8S: Emulation of Heterogeneous Kubernetes Clusters Using QEMU

Julian Kunkel, Jonathan Decker, Vincent Florens Hasse
Algorithms
Cloud Computing and Resource Management
article

Q8S: Emulation of Heterogeneous Kubernetes Clusters Using QEMU

Julian Kunkel, Jonathan Decker, Vincent Florens Hasse
article en

Abstract

Kubernetes has emerged as the industry standard for container orchestration in cloud environments, with its scheduler dynamically placing container instances across cluster nodes based on predefined rules and algorithms. Various efforts have been made to extend and improve upon the Kubernetes scheduler. However, as the majority of Kubernetes clusters operate on homogeneous hardware, most scheduling algorithms are also only developed for homogeneous systems. Heterogeneous infrastructures, which include IoT devices or specialized hardware, have become more widespread and require specialized tuning to optimize workload assignment, for which researchers and developers working on scheduling systems require access to heterogeneous hardware for development and testing; such data may not be available. While simulations such as CloudSim or K8sSim can provide insights, the level of detail they can offer to validate new schedulers is limited, as they are only simulations. To address this, we introduce Q8S, a tool for emulating heterogeneous Kubernetes clusters including x86_64 and ARM64 architectures on OpenStack using QEMU. Emulations created through Q8S provide a higher level of detail than simulations and can be used to train machine learning scheduling algorithms. By providing an environment capable of executing real workloads, Q8S enables researchers and developers to test and refine their scheduling algorithms, ultimately leading to more efficient and effective heterogeneous cluster management. We release our implementation of Q8S as open source.

AlgorithmsVol. 18(6)
Gesellschaft für wissenschaftliche Datenverarbeitung mbH Göttingen (DE), University of Göttingen (DE)
Bundesministerium für Bildung und Forschung
Openalex Percentile: Top 83%
Cloud Computing and Resource Management
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