The growing use of the Internet of Things (IoT) has led to widespread adoption of Cloud and Edge computing technologies to better manage and analyze the huge amount of data generated by IoT devices. The combination of Cloud and Edge computing paradigms attempts to avoid their pitfalls while offering the best of both worlds: Cloud scalability and computing closer to the Edge where data is typically generated. However, placing microservices in such highly heterogeneous environments while meeting Quality of Service (QoS) constraints is a challenging task due to the geo-distribution of nodes and the varying heterogeneous computational resources. In this work, we propose an approach for scheduling microservices applications across the Cloud-to-Edge continuum to minimize QoS violations on the response times of these applications. Our approach has been evaluated on the iFogSim simulator and compared with some of its built-in scheduling strategies.