Kubernetes application performance benchmarking on heterogeneous CPU architecture: An experimental review

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. • ARM architecture enables heterogeneous CPU design for enhanced performance. • Tests on x86 vs. ARM across clouds revealed varied performance outcomes. • ARM outperformed x86 in most performance comparisons with significant gains.

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Publication Details

Journal
High-Confidence Computing
Published
2024-12-18
DOI
https://doi.org/10.1016/j.hcc.2024.100276
Citations
4
Primary Topic
Cloud Computing and Resource Management
Type
article
Field-Weighted Citation Impact
3.12
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article

Kubernetes application performance benchmarking on heterogeneous CPU architecture: An experimental review

Tanvir Rahman, Tanvir Zaman Khan, Jannatun Noor, Mahwish Amin et al.
4 citations
High-Confidence Computing
Cloud Computing and Resource Management
3.12
article

Kubernetes application performance benchmarking on heterogeneous CPU architecture: An experimental review

Tanvir Rahman, Tanvir Zaman Khan, Jannatun Noor, Mahwish Amin, MD Badsha Faysal, Bushra Tabassum
article en
4 citations

Abstract

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. • ARM architecture enables heterogeneous CPU design for enhanced performance. • Tests on x86 vs. ARM across clouds revealed varied performance outcomes. • ARM outperformed x86 in most performance comparisons with significant gains.

High-Confidence ComputingVol. 5(1)
United International University (BD)
Affordable and clean energy
Openalex Percentile: Top 7%
Cloud Computing and Resource Management
3.12
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Kubernetes application performance benchmarking on heterogeneous CPU architecture: An experimental review — Tanvir Rahman, Tanvir Zaman Khan, et al. · High-Confidence Computing (2024) | TGRS Research Map | TGRS