Abstract:

In the context of the ongoing pandemic, the need for remote collaboration between teachers and groups of students has become an important educational aspect. A possible solution is to move the entire activity to the Cloud, thus offering other advantages besides the much-needed interaction, such as disaster recovery and resource management. As cost savings are now more important than ever, one also needs to make the right choice between the Cloud providers where to deploy the educational environments. A platform focussed on multicloud deployment and collaboration can facilitate one to benefit from the advantages mentioned above, providing usage simplicity for teams of students and researchers that need to continue their activity during the lockdown period.

The result of our research is a multicloud deployment platform that helps users with their choices on the deployment of infrastructure and tools, even without possessing advanced technical knowledge. Thus, one can create multiple environments for test, development and production whenever he/she needs it. The paper discusses the educational advantages that a platform with such features can provide and the help it can represent for teachers, students, and researchers in the current world situation.

From a technical perspective, the means of deployment include technologies such as Docker, Kubernetes, Helm, and Terraform. The Cloud infrastructure is automatically deployed using Terraform scripts and the Kubernetes resources are deployed with Helm Charts. Helm Charts and Terraform are the source for automatic deployment and will be triggered when a user deploys the infrastructure from the web application. These methods are frequently used to create/delete/recreate environments and to move resources very fast on Cloud subscriptions; they are also supported by the most important Cloud providers.
The solution presented in this paper has the purpose to develop means for increasing the collaboration among the academic personnel such as teachers, researchers and students who face a tough period in which they have to learn, research and perform evaluations using online tools. As a result, the platform can ensure a strong work connection fulfills the objective of providing on-Cloud capabilities that may exceed a local laboratory environment. The paper describes an example that applies these ideas to the modelling field, by presenting the multicloud deployment of a generic modeling environment, alongside its model interpreters, used for Model Driven Engineering classes and the related research.

Keywords:

Cloud Computing, remote learning tools, learning under lockdown.