Modern component-based software engineering environments allow deployment of cloud applications on various computing infrastructures, such as Edge-to-Cloud infrastructures. The heterogeneous nature of such computing resources results in variable Quality of Service (QoS). Therefore, the deployment decision can seriously affect the application’s overall performance. This study presents an approach for automated deployment of cloud applications in the Edge-to-Cloud computing continuum that considers non-functional requirements (NFRs). In addition, the authors explore multiple methods for selection of optimal cloud infrastructure, such as IaaS. The paper presents an experimental evaluation performed using a cloud application for storing data under different workloads. For the purposes of the experimental evaluation, a Kubernetes cluster composed of 44 computing nodes was used. The cluster nodes were geographically distributed computing infrastructures hosted by several service providers. The proposed approach allows a reliable selection of infrastructures, which satisfy high QoS requirements for cloud applications, from heterogeneous Edge-to-Cloud computing environments.