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Pednekar, Anant Sakharam (2023) A Comparative Analysis of Kubernetes and OpenShift based on Workloads using Different Hardware Architecture. Masters thesis, Dublin, National College of Ireland.
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Abstract
The application deployment and management landscape has undergone a transformative shift with containerization, spearheaded by prominent platforms like Kubernetes and OpenShift. Despite their widespread adoption, a crucial knowledge gap persists in understanding the performance nuances and optimization strategies when deployed on diverse hardware architectures, encompassing x86, IBM ppc64le, and ARM. This research attempts to bridge this knowledge gap by conducting thorough benchmarking and optimization tests tailored for Kubernetes on x86 and ARM and OpenShift on ppc64le platforms. The evaluation encompasses critical performance metrics, including CPU and memory utilization and storage performance. The outcomes of this research are poised to empower businesses and researchers in selecting containerization engines that align with their unique hardware and software requirements. The study aims to improve application performance and operational efficiency in containerized environments by enhancing our understanding of the performance across diverse architectures. The evaluations reveal significant findings from the Sysbench and Kbench tests, showcasing notable differences in performance metrics between x86 and ARM platforms. This research highlights the positive aspects of ARM architecture in terms of CPU speed and efficiency, making it the preferred choice for high-CPU-usage tasks. It also emphasizes the importance of considering workload-specific factors when deciding between x86 and ARM. In addition, the study suggests using OpenShift on ppc64le for situations where performance requirements perfectly match workload needs. These findings offer valuable insights for making informed decisions when choosing the most appropriate hardware architecture for containerized applications.
| Item Type: | Thesis (Masters) |
|---|---|
| Supervisors: | Name Email Haque, Rejwanul UNSPECIFIED |
| Subjects: | Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > QA Mathematics > Computer software T Technology > T Technology (General) > Information Technology > Computer software T Technology > T Technology (General) > Information Technology > Cloud computing |
| Divisions: | School of Computing > Master of Science in Cloud Computing |
| Depositing User: | Ciara O'Brien |
| Date Deposited: | 10 Apr 2025 09:56 |
| Last Modified: | 10 Apr 2025 09:56 |
| URI: | https://norma.ncirl.ie/id/eprint/7402 |
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