With the rapidly growing popularity of cloud services, the cloud computing faces critical challenges to orchestrate the deployment and operation of cloud applications on heterogenous cloud platforms. Cloud applications are built on a platform model that abstracts away underlying platform-specific details, so that their orchestration can benefit from the abstract view and flexibility of the underlying platform configuration. However, considerable efforts are still required to properly manage complicated cloud applications. This paper proposes a model-driven approach to cloud application orchestration which promotes the concerns of distinct roles for cloud system provisioning and operation. By establishing a set of capabilities as modeling constructs, our approach allows TOSCA-based application topology itself and its orchestration needs to be specified in a way to provide a more targeted support for different needs and concerns of application developers and operators. With novel orchestration features like application topology description, platform capability modeling, and role-awareness for cloud application orchestration, it can significantly reduce the complexity of application orchestration in diverse cloud environments. To show the feasibility and effectiveness of our proposal for cloud application orchestration, we present a proof-of-concept orchestration system implementation and evaluate its deployment and orchestration results in a Kubernetes cluster.

With a rapid growth of cloud service offerings, application developers face a critical challenge to adequately orchestrate their applications on diverse cloud platforms. A desirable orchestration solution should ensure that the applications are deployed, configured, and operated in an appropriate way to the given situation. This paper proposes a model-driven orchestration approach that specifies particular tasks depending on the roles of involved individuals. By keeping the concerns of applications developers and operators separated, our proposed scheme allows them to better focus on what are expected from themselves to achieve the overall orchestration goal. To show the feasibility and effectiveness of the proposal, we present a proof-of-concept system implementation and demonstrate its orchestration operations on Kubernetes platform.