Songjie Wang, R. Neupane, Ashish Pandey, Xiyao Cheng, P. Calyam
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Our learning platform features scalability, flexibility, and extend ability in providing Cloud and DevOps concepts knowledge and hands-on skills. We detail our “application-inspired learning” methodology that is based on integration of real-world application use cases in four learning modules that include laboratory exercises and self-study activities using realistic cloud/HPC-based application testbeds. We describe the learning modules that allow students to gain skills in using latest technologies (e.g., containerization, cluster and edge computing, data pipeline automation) to implement relevant security, monitoring, and adaptation mechanisms. Lastly, we evaluate our platform via a knowledge growth study survey with instructors and students.","PeriodicalId":227669,"journal":{"name":"2021 IEEE 28th International Conference on High Performance Computing, Data and Analytics Workshop (HiPCW)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Online Learning Platform for Application-Inspired Cloud and DevOps Curriculum\",\"authors\":\"Songjie Wang, R. Neupane, Ashish Pandey, Xiyao Cheng, P. Calyam\",\"doi\":\"10.1109/HiPCW54834.2021.00012\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Cloud-hosted services are being increasingly used in hosting business applications due to cost effectiveness, scalability, and ease of deployment. To facilitate rapid development, change and release process of cloud-hosted applications, the area of Development and Operations (DevOps) is fast evolving. It is necessary to train the future generation of application development professionals such that they are knowledgeable in the continuous integration and continuous delivery automation. In this paper, we present the design and development of our “Mizzou Cloud DevOps platform”, an online platform to learn cutting-edge Cloud and DevOps tools/technologies using open/public cloud infrastructures for wide adoption amongst instructors/students. Our learning platform features scalability, flexibility, and extend ability in providing Cloud and DevOps concepts knowledge and hands-on skills. We detail our “application-inspired learning” methodology that is based on integration of real-world application use cases in four learning modules that include laboratory exercises and self-study activities using realistic cloud/HPC-based application testbeds. We describe the learning modules that allow students to gain skills in using latest technologies (e.g., containerization, cluster and edge computing, data pipeline automation) to implement relevant security, monitoring, and adaptation mechanisms. 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Online Learning Platform for Application-Inspired Cloud and DevOps Curriculum
Cloud-hosted services are being increasingly used in hosting business applications due to cost effectiveness, scalability, and ease of deployment. To facilitate rapid development, change and release process of cloud-hosted applications, the area of Development and Operations (DevOps) is fast evolving. It is necessary to train the future generation of application development professionals such that they are knowledgeable in the continuous integration and continuous delivery automation. In this paper, we present the design and development of our “Mizzou Cloud DevOps platform”, an online platform to learn cutting-edge Cloud and DevOps tools/technologies using open/public cloud infrastructures for wide adoption amongst instructors/students. Our learning platform features scalability, flexibility, and extend ability in providing Cloud and DevOps concepts knowledge and hands-on skills. We detail our “application-inspired learning” methodology that is based on integration of real-world application use cases in four learning modules that include laboratory exercises and self-study activities using realistic cloud/HPC-based application testbeds. We describe the learning modules that allow students to gain skills in using latest technologies (e.g., containerization, cluster and edge computing, data pipeline automation) to implement relevant security, monitoring, and adaptation mechanisms. Lastly, we evaluate our platform via a knowledge growth study survey with instructors and students.