A Comprehensive Experimentation Framework for Energy-Efficient Design of Cloud-Native Applications
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arXiv
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| Auteurs principaux: | , , , |
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| Format: | Preprint |
| Publié: |
2025
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| _version_ | 1866929753718521856 |
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| author | Werner, Sebastian Borges, Maria C. Wolf, Karl Tai, Stefan |
| author_facet | Werner, Sebastian Borges, Maria C. Wolf, Karl Tai, Stefan |
| contents | Current approaches to designing energy-efficient applications typically rely on measuring individual components using readily available local metrics, like CPU utilization. However, these metrics fall short when applied to cloud-native applications, which operate within the multi-tenant, shared environments of distributed cloud providers. Assessing and optimizing the energy efficiency of cloud-native applications requires consideration of the complex, layered nature of modern cloud stacks.
To address this need, we present a comprehensive, automated, and extensible experimentation framework that enables developers to measure energy efficiency across all relevant layers of a cloud-based application and evaluate associated quality trade-offs. Our framework integrates a suite of service quality and sustainability metrics, providing compatibility with any Kubernetes-based application. We demonstrate the feasibility and effectiveness of this approach through initial experimental results, comparing architectural design alternatives for a widely used open-source cloud-native application. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_08641 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Comprehensive Experimentation Framework for Energy-Efficient Design of Cloud-Native Applications Werner, Sebastian Borges, Maria C. Wolf, Karl Tai, Stefan Software Engineering Distributed, Parallel, and Cluster Computing Current approaches to designing energy-efficient applications typically rely on measuring individual components using readily available local metrics, like CPU utilization. However, these metrics fall short when applied to cloud-native applications, which operate within the multi-tenant, shared environments of distributed cloud providers. Assessing and optimizing the energy efficiency of cloud-native applications requires consideration of the complex, layered nature of modern cloud stacks. To address this need, we present a comprehensive, automated, and extensible experimentation framework that enables developers to measure energy efficiency across all relevant layers of a cloud-based application and evaluate associated quality trade-offs. Our framework integrates a suite of service quality and sustainability metrics, providing compatibility with any Kubernetes-based application. We demonstrate the feasibility and effectiveness of this approach through initial experimental results, comparing architectural design alternatives for a widely used open-source cloud-native application. |
| title | A Comprehensive Experimentation Framework for Energy-Efficient Design of Cloud-Native Applications |
| topic | Software Engineering Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2503.08641 |