CloudNativeSim: a toolkit for modeling and simulation of cloud-native applications
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arXiv
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| Autores principales: | , , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| _version_ | 1866909980411559936 |
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| author | Wu, Jingfeng Xu, Minxian He, Yiyuan Ye, Kejiang Xu, Chengzhong |
| author_facet | Wu, Jingfeng Xu, Minxian He, Yiyuan Ye, Kejiang Xu, Chengzhong |
| contents | Cloud-native applications are increasingly becoming popular in modern software design. Employing a microservice-based architecture into these applications is a prevalent strategy that enhances system availability and flexibility. However, cloud-native applications also introduce new challenges, such as frequent inter-service communication and the complexity of managing heterogeneous codebases and hardware, resulting in unpredictable complexity and dynamism. Furthermore, as applications scale, only limited research teams or enterprises possess the resources for large-scale deployment and testing, which impedes progress in the cloud-native domain. To address these challenges, we propose CloudNativeSim, a simulator for cloud-native applications with a microservice-based architecture. CloudNativeSim offers several key benefits: (i) comprehensive and dynamic modeling for cloud-native applications, (ii) an extended simulation framework with new policy interfaces for scheduling cloud-native applications, and (iii) support for customized application scenarios and user feedback based on Quality of Service (QoS) metrics. CloudNativeSim can be easily deployed on standard computers to manage a high volume of requests and services. Its performance was validated through a case study, demonstrating higher than 94.5% accuracy in terms of response time. The study further highlights the feasibility of CloudNativeSim by illustrating the effects of various scaling policies. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_05093 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | CloudNativeSim: a toolkit for modeling and simulation of cloud-native applications Wu, Jingfeng Xu, Minxian He, Yiyuan Ye, Kejiang Xu, Chengzhong Distributed, Parallel, and Cluster Computing Cloud-native applications are increasingly becoming popular in modern software design. Employing a microservice-based architecture into these applications is a prevalent strategy that enhances system availability and flexibility. However, cloud-native applications also introduce new challenges, such as frequent inter-service communication and the complexity of managing heterogeneous codebases and hardware, resulting in unpredictable complexity and dynamism. Furthermore, as applications scale, only limited research teams or enterprises possess the resources for large-scale deployment and testing, which impedes progress in the cloud-native domain. To address these challenges, we propose CloudNativeSim, a simulator for cloud-native applications with a microservice-based architecture. CloudNativeSim offers several key benefits: (i) comprehensive and dynamic modeling for cloud-native applications, (ii) an extended simulation framework with new policy interfaces for scheduling cloud-native applications, and (iii) support for customized application scenarios and user feedback based on Quality of Service (QoS) metrics. CloudNativeSim can be easily deployed on standard computers to manage a high volume of requests and services. Its performance was validated through a case study, demonstrating higher than 94.5% accuracy in terms of response time. The study further highlights the feasibility of CloudNativeSim by illustrating the effects of various scaling policies. |
| title | CloudNativeSim: a toolkit for modeling and simulation of cloud-native applications |
| topic | Distributed, Parallel, and Cluster Computing |
| url | https://arxiv.org/abs/2409.05093 |