Cloud Service deployment automation is a crucial component of the Cloud Computing concept, because it enables us to create new instances of a service with minimal cost and effort. Cloud service instances consist of many platform and infrastructure components as well as application components, which all need to be deployed and configured. Manually deploying new instances hinders development, it increases the cost of onboarding new customers, and operating large installations becomes impractical and error prone. Deployment automation has long been a practice among software engineers, but solutions like installers, scripts, Chef or Puppet are not suited for the diverse Cloud environments. For this reason, higher-level model-based approaches, like Amazon CloudFormation, Openstack Heat and TOSCA, have emerged. They allow automating a wide variety of services and components, and encourage reusing modelling artifacts. However, these modelling languages are complex and lack tool-support. In practice, their reusability is also limited, because the models are often tightly coupled and monolithic. For these reasons, the model-based deployment approaches have not found wide spread adoption yet, especially in the enterprise segment. Therefore, we propose a different approach to model-based deployment automation: We focus on a specific application domain and define a domain specific language (DSL) for this domain. Then we provide a smart interpreter that translates the high level DSL into an executable service deployment model.