Kubernetes application performance benchmarking on heterogeneous CPU architecture: An experimental review Article Swipe
Jannatun Noor
,
MD Badsha Faysal
,
Mahwish Amin
,
Bushra Tabassum
,
Tanvir Zaman Khan
,
Tanvir Rahman
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1016/j.hcc.2024.100276
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1016/j.hcc.2024.100276
With the rapid advancement of cloud technologies, cloud services have enormously contributed to the cloud community for application development life-cycle. In this context, Kubernetes has played a pivotal role as a cloud computing tool, enabling developers to adopt efficient and automated deployment strategies. Using Kubernetes as an orchestration tool and a cloud computing system as a manager of the infrastructures, developers can boost the development and deployment process. With cloud providers such as GCP, AWS, Azure, and Oracle offering Kubernetes services, the availability of both x86 and ARM platforms has become evident. However, while x86 currently dominates the market, ARM-based solutions have seen limited adoption, with only a few individuals actively working on ARM deployments. This study explores the efficiency and cost-effectiveness of implementing Kubernetes on different CPU platforms. By comparing the performance of x86 and ARM platforms, this research seeks to ascertain whether transitioning to ARM presents a more advantageous option for Kubernetes deployments. Through a comprehensive evaluation of scalability, cost, and overall performance, this study aims to shed light on the viability of leveraging ARM on different CPUs by providing valuable insights.
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https://openalex.org/W4405527725Canonical identifier for this work in OpenAlex
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https://doi.org/10.1016/j.hcc.2024.100276Digital Object Identifier
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Kubernetes application performance benchmarking on heterogeneous CPU architecture: An experimental reviewWork title
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articleOpenAlex work type
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enPrimary language
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2024Year of publication
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2024-12-18Full publication date if available
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Jannatun Noor, MD Badsha Faysal, Mahwish Amin, Bushra Tabassum, Tanvir Zaman Khan, Tanvir RahmanList of authors in order
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https://doi.org/10.1016/j.hcc.2024.100276Publisher landing page
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https://doi.org/10.1016/j.hcc.2024.100276Direct OA link when available
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2Total citation count in OpenAlex
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2025: 2Per-year citation counts (last 5 years)
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| abstract_inverted_index.ascertain | 142 |
| abstract_inverted_index.automated | 40 |
| abstract_inverted_index.community | 15 |
| abstract_inverted_index.comparing | 130 |
| abstract_inverted_index.computing | 32, 52 |
| abstract_inverted_index.currently | 95 |
| abstract_inverted_index.different | 126, 178 |
| abstract_inverted_index.dominates | 96 |
| abstract_inverted_index.efficient | 38 |
| abstract_inverted_index.insights. | 183 |
| abstract_inverted_index.platforms | 88 |
| abstract_inverted_index.providers | 70 |
| abstract_inverted_index.providing | 181 |
| abstract_inverted_index.services, | 80 |
| abstract_inverted_index.solutions | 100 |
| abstract_inverted_index.viability | 173 |
| abstract_inverted_index.Kubernetes | 23, 44, 79, 124, 153 |
| abstract_inverted_index.deployment | 41, 66 |
| abstract_inverted_index.developers | 35, 60 |
| abstract_inverted_index.efficiency | 119 |
| abstract_inverted_index.enormously | 10 |
| abstract_inverted_index.evaluation | 158 |
| abstract_inverted_index.leveraging | 175 |
| abstract_inverted_index.platforms, | 137 |
| abstract_inverted_index.platforms. | 128 |
| abstract_inverted_index.advancement | 3 |
| abstract_inverted_index.application | 17 |
| abstract_inverted_index.contributed | 11 |
| abstract_inverted_index.development | 18, 64 |
| abstract_inverted_index.individuals | 109 |
| abstract_inverted_index.life-cycle. | 19 |
| abstract_inverted_index.performance | 132 |
| abstract_inverted_index.strategies. | 42 |
| abstract_inverted_index.advantageous | 150 |
| abstract_inverted_index.availability | 82 |
| abstract_inverted_index.deployments. | 114, 154 |
| abstract_inverted_index.implementing | 123 |
| abstract_inverted_index.performance, | 164 |
| abstract_inverted_index.scalability, | 160 |
| abstract_inverted_index.comprehensive | 157 |
| abstract_inverted_index.orchestration | 47 |
| abstract_inverted_index.technologies, | 6 |
| abstract_inverted_index.transitioning | 144 |
| abstract_inverted_index.infrastructures, | 59 |
| abstract_inverted_index.cost-effectiveness | 121 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 95 |
| countries_distinct_count | 0 |
| institutions_distinct_count | 6 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/7 |
| sustainable_development_goals[0].score | 0.46000000834465027 |
| sustainable_development_goals[0].display_name | Affordable and clean energy |
| citation_normalized_percentile.value | 0.90707424 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |