IRILL - Research and Innovation on Free Software Cloud Computing is a major trend in distributed computing environments enabling software virtualization on configurable runtime platforms. Configuration and customization choices arise due to the heterogeneous and scalable aspect of the cloud computing paradigm. The wide range of cloud solutions and the lack of knowledge in this domain is a real problem for companies when facing the cloud solution choice. Indeed, the selection of a cloud among others as well as the selection of required tools and/or libraries in this cloud remains challenging due to the amount of providers and their intrinsic variability. Feature Models (FM) originating from Software Product Lines (SPL) approach is one way to handle this variability and then manage and create configurations in the cloud, while ontologies are used to model the various semantics of cloud systems. We propose a model-driven approach based on FMs and ontologies. We use extended FMs to represent cloud providers variability and their resources dimensions, combined with ontologies that capture cloud computing knowledge. We define a mapping between ontologies and FMs to bridge the gap between the application configuration and cloud platforms’ offer.