Jingfeng Wu, Minxian Xu, Yiyuan He, Kejiang Ye, Chengzhong Xu
{"title":"CloudNativeSim: a toolkit for modeling and simulation of cloud-native applications","authors":"Jingfeng Wu, Minxian Xu, Yiyuan He, Kejiang Ye, Chengzhong Xu","doi":"arxiv-2409.05093","DOIUrl":null,"url":null,"abstract":"Cloud-native applications are increasingly becoming popular in modern\nsoftware design. Employing a microservice-based architecture into these\napplications is a prevalent strategy that enhances system availability and\nflexibility. However, cloud-native applications also introduce new challenges,\nsuch as frequent inter-service communication and the complexity of managing\nheterogeneous codebases and hardware, resulting in unpredictable complexity and\ndynamism. Furthermore, as applications scale, only limited research teams or\nenterprises possess the resources for large-scale deployment and testing, which\nimpedes progress in the cloud-native domain. To address these challenges, we\npropose CloudNativeSim, a simulator for cloud-native applications with a\nmicroservice-based architecture. CloudNativeSim offers several key benefits:\n(i) comprehensive and dynamic modeling for cloud-native applications, (ii) an\nextended simulation framework with new policy interfaces for scheduling\ncloud-native applications, and (iii) support for customized application\nscenarios and user feedback based on Quality of Service (QoS) metrics.\nCloudNativeSim can be easily deployed on standard computers to manage a high\nvolume of requests and services. Its performance was validated through a case\nstudy, demonstrating higher than 94.5% accuracy in terms of response time. The\nstudy further highlights the feasibility of CloudNativeSim by illustrating the\neffects of various scaling policies.","PeriodicalId":501422,"journal":{"name":"arXiv - CS - Distributed, Parallel, and Cluster Computing","volume":"14 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Distributed, Parallel, and Cluster Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.05093","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
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.