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 schedu...
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MDPI AG
2025-05-01
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| Series: | Algorithms |
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| Online Access: | https://www.mdpi.com/1999-4893/18/6/324 |
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| author | Jonathan Decker Vincent Florens Hasse Julian Kunkel |
| author_facet | Jonathan Decker Vincent Florens Hasse Julian Kunkel |
| author_sort | Jonathan Decker |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-815d7be192bd4c78bd30ae0e5ec697b1 |
| institution | Kabale University |
| issn | 1999-4893 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Algorithms |
| spelling | doaj-art-815d7be192bd4c78bd30ae0e5ec697b12025-08-20T03:30:29ZengMDPI AGAlgorithms1999-48932025-05-0118632410.3390/a18060324Q8S: Emulation of Heterogeneous Kubernetes Clusters Using QEMUJonathan Decker0Vincent Florens Hasse1Julian Kunkel2Institute for Computer Science, University of Göttingen, Goldschmidtstraße 7, 37077 Göttingen, GermanyInstitute for Computer Science, University of Göttingen, Goldschmidtstraße 7, 37077 Göttingen, GermanyInstitute for Computer Science, University of Göttingen, Goldschmidtstraße 7, 37077 Göttingen, GermanyKubernetes 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.https://www.mdpi.com/1999-4893/18/6/324KubernetesemulationheterogeneousQEMUOpenStackscheduling |
| spellingShingle | Jonathan Decker Vincent Florens Hasse Julian Kunkel Q8S: Emulation of Heterogeneous Kubernetes Clusters Using QEMU Algorithms Kubernetes emulation heterogeneous QEMU OpenStack scheduling |
| title | Q8S: Emulation of Heterogeneous Kubernetes Clusters Using QEMU |
| title_full | Q8S: Emulation of Heterogeneous Kubernetes Clusters Using QEMU |
| title_fullStr | Q8S: Emulation of Heterogeneous Kubernetes Clusters Using QEMU |
| title_full_unstemmed | Q8S: Emulation of Heterogeneous Kubernetes Clusters Using QEMU |
| title_short | Q8S: Emulation of Heterogeneous Kubernetes Clusters Using QEMU |
| title_sort | q8s emulation of heterogeneous kubernetes clusters using qemu |
| topic | Kubernetes emulation heterogeneous QEMU OpenStack scheduling |
| url | https://www.mdpi.com/1999-4893/18/6/324 |
| work_keys_str_mv | AT jonathandecker q8semulationofheterogeneouskubernetesclustersusingqemu AT vincentflorenshasse q8semulationofheterogeneouskubernetesclustersusingqemu AT juliankunkel q8semulationofheterogeneouskubernetesclustersusingqemu |