Abstract
The deployment of composite applications and services in distributed or compute cloud environments is still a challenging task that is a key source of operational cost and risk. Current approaches to composite deployments can be categorized as workflow based and model based. In the workflow based approach, deployers create end-to-end workflows to automate application deployment, while in the model based approach architects design detailed “desired state” models and validate they meet all requirements and constraints. Today, there is no formally understood relationship and mapping between “desired state” models and deployment workflows, posing a challenge and limitation on architects and deployers. In this paper we propose a new model based approach to bridge the gap between deployment models and workflows. Our approach supports separation of concerns where basic automation building blocks (such as scripts and workflows) can be developed independently of the resource model and with no knowledge of it. Therefore, the method enables deployers to continue to leverage useful libraries of automation building blocks, while enjoying the benefits of a sound resource model, used for validation and constraint satisfaction. We propose algorithms and implementation to generate end-to-end workflows for input “desired state” resource models, based on given libraries of automation building blocks. Our approach has been incorporated into IBM's leading deployment modeling platform [15] and is in active use by customers in a large range of applications.
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