Abstract
For the deployment of applications, various deployment technologies, such as Kubernetes and Terraform, are available to automate the deployment of applications. However, to use these technologies, developers must acquire specialized knowledge about these deployment technologies to create, maintain, and understand deployment models, for example, configuration files created with Kubernetes. In this work, we present and demonstrate the Deployment Model Abstraction Framework (DeMAF), a tool that enables transforming technology-specific deployment models into technology-agnostic deployment models that are modeled based on the Essential Deployment Metamodel (EDMM). The resulting technology-agnostic EDMM deployment models express deployments only by using the general modeling concepts that are supported by the 13 most prominent technologies. Therefore, the target audience for this demonstration includes developers and architects, who will be shown that such transformations can be automated and that the resulting EDMM models can be understood without knowledge of the original deployment technology. We evaluate the general practical feasibility of the approach by a case study that demonstrates a scenario based on the T2-Project and the technologies Terraform, Kubernetes, and Helm.
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Notes
- 1.
Implementation of the T2-Project on GitHub: https://github.com/t2-project.
- 2.
Helm: https://helm.sh/.
- 3.
Terraform: https://www.terraform.io/.
- 4.
Deployment model for the T2-Project on GitHub: https://github.com/Well5a/kube.
- 5.
EDMM in YAML Specification: https://github.com/UST-EDMM/spec-yaml.
- 6.
GitHub organization with the DeMAF prototype: https://github.com/UST-DeMAF.
- 7.
Zenodo repository with evaluation results: https://doi.org/10.5281/zenodo.6824223.
- 8.
References
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Weller, M., Breitenbücher, U., Speth, S., Becker, S. (2023). The Deployment Model Abstraction Framework. In: Sales, T.P., Proper, H.A., Guizzardi, G., Montali, M., Maggi, F.M., Fonseca, C.M. (eds) Enterprise Design, Operations, and Computing. EDOC 2022 Workshops . EDOC 2022. Lecture Notes in Business Information Processing, vol 466. Springer, Cham. https://doi.org/10.1007/978-3-031-26886-1_19
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DOI: https://doi.org/10.1007/978-3-031-26886-1_19
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