B. Purahong, J. Sithiyopasakul, P. Sithiyopasakul, A. Lasakul, C. Benjangkaprasert
{"title":"基于容器编排工具比较的自动化资源管理系统","authors":"B. Purahong, J. Sithiyopasakul, P. Sithiyopasakul, A. Lasakul, C. Benjangkaprasert","doi":"10.12720/jait.14.3.501-509","DOIUrl":null,"url":null,"abstract":"—The goal of this article is to study and analyze the container orchestration technology Kubernetes, Docker Swarm, and Apache Mesos by performing performance evaluations and inspecting how many requests and responses the server can handle. Due to the fact that managing information system resources is a challenge in terms of performance, usability, reliability, and the cost of information resources. Some orchestration tools cannot automatically allocate resources depending on the scope of the information system resource management. This leads to allocating resources more than the needs of system requirements, resulting in excessive costs. Therefore, this article proposed testing the system by measuring its effectiveness using a structured process by examining measurement variables such as the number of requests per second, number of responses to requests, and resource extension period using all three-orchestration technology. From the testing and analysis of all three variables as mentioned, it is possible to know the efficiency of the Kubernetes technology in such a similar environment and compared it with other orchestration tools like Docker Swarm and Apache Mesos orchestrator. For Kubernetes, Docker Swarm, and Apache Mesos, the mean value of its handling average request per minute is 30,677.25/min, 33,688.67/min, and 29,682.6/min, respectively. Swarm performed better in aspects of handling requests per minute by 9.35% of the difference when compared to Kubernetes and by 12.64% when compared to Apache Mesos. However, there are several things which should be taken into consideration because each orchestration tool has its own strong and weak points. The testing experiment could display a piece of information on the dashboard for visualization and analytic purposes and there is an elaboration at the end of when to use which container orchestration tool to suit the business proposes the most .","PeriodicalId":0,"journal":{"name":"","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Automated Resource Management System Based upon Container Orchestration Tools Comparison\",\"authors\":\"B. Purahong, J. Sithiyopasakul, P. Sithiyopasakul, A. Lasakul, C. Benjangkaprasert\",\"doi\":\"10.12720/jait.14.3.501-509\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"—The goal of this article is to study and analyze the container orchestration technology Kubernetes, Docker Swarm, and Apache Mesos by performing performance evaluations and inspecting how many requests and responses the server can handle. Due to the fact that managing information system resources is a challenge in terms of performance, usability, reliability, and the cost of information resources. Some orchestration tools cannot automatically allocate resources depending on the scope of the information system resource management. This leads to allocating resources more than the needs of system requirements, resulting in excessive costs. Therefore, this article proposed testing the system by measuring its effectiveness using a structured process by examining measurement variables such as the number of requests per second, number of responses to requests, and resource extension period using all three-orchestration technology. From the testing and analysis of all three variables as mentioned, it is possible to know the efficiency of the Kubernetes technology in such a similar environment and compared it with other orchestration tools like Docker Swarm and Apache Mesos orchestrator. For Kubernetes, Docker Swarm, and Apache Mesos, the mean value of its handling average request per minute is 30,677.25/min, 33,688.67/min, and 29,682.6/min, respectively. Swarm performed better in aspects of handling requests per minute by 9.35% of the difference when compared to Kubernetes and by 12.64% when compared to Apache Mesos. However, there are several things which should be taken into consideration because each orchestration tool has its own strong and weak points. 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Automated Resource Management System Based upon Container Orchestration Tools Comparison
—The goal of this article is to study and analyze the container orchestration technology Kubernetes, Docker Swarm, and Apache Mesos by performing performance evaluations and inspecting how many requests and responses the server can handle. Due to the fact that managing information system resources is a challenge in terms of performance, usability, reliability, and the cost of information resources. Some orchestration tools cannot automatically allocate resources depending on the scope of the information system resource management. This leads to allocating resources more than the needs of system requirements, resulting in excessive costs. Therefore, this article proposed testing the system by measuring its effectiveness using a structured process by examining measurement variables such as the number of requests per second, number of responses to requests, and resource extension period using all three-orchestration technology. From the testing and analysis of all three variables as mentioned, it is possible to know the efficiency of the Kubernetes technology in such a similar environment and compared it with other orchestration tools like Docker Swarm and Apache Mesos orchestrator. For Kubernetes, Docker Swarm, and Apache Mesos, the mean value of its handling average request per minute is 30,677.25/min, 33,688.67/min, and 29,682.6/min, respectively. Swarm performed better in aspects of handling requests per minute by 9.35% of the difference when compared to Kubernetes and by 12.64% when compared to Apache Mesos. However, there are several things which should be taken into consideration because each orchestration tool has its own strong and weak points. The testing experiment could display a piece of information on the dashboard for visualization and analytic purposes and there is an elaboration at the end of when to use which container orchestration tool to suit the business proposes the most .