Modeling Different Deployment Variants of a Composite Application in a Single Declarative Deployment Model

Author:

Stötzner MilesORCID,Becker SteffenORCID,Breitenbücher UweORCID,Képes KálmánORCID,Leymann FrankORCID

Abstract

For automating the deployment of composite applications, typically, declarative deployment models are used. Depending on the context, the deployment of an application has to fulfill different requirements, such as costs and elasticity. As a consequence, one and the same application, i.e., its components, and their dependencies, often need to be deployed in different variants. If each different variant of a deployment is described using an individual deployment model, it quickly results in a large number of models, which are error prone to maintain. Deployment technologies, such as Terraform or Ansible, support conditional components and dependencies which allow modeling different deployment variants of a composite application in a single deployment model. However, there are deployment technologies, such as TOSCA and Docker Compose, which do not support such conditional elements. To address this, we extend the Essential Deployment Metamodel (EDMM) by conditional components and dependencies. EDMM is a declarative deployment model which can be mapped to several deployment technologies including Terraform, Ansible, TOSCA, and Docker Compose. Preprocessing such an extended model, i.e., conditional elements are evaluated and either preserved or removed, generates an EDMM conform model. As a result, conditional elements can be integrated on top of existing deployment technologies that are unaware of such concepts. We evaluate this by implementing a preprocessor for TOSCA, called OpenTOSCA Vintner, which employs the open-source TOSCA orchestrators xOpera and Unfurl to execute the generated TOSCA conform models.

Funder

Federal Ministry for Economic Affairs and Energy

Publisher

MDPI AG

Subject

Computational Mathematics,Computational Theory and Mathematics,Numerical Analysis,Theoretical Computer Science

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