In recent years, computing workloads have shifted from the cloud to the fog and edge, as IoT devices are becoming powerful enough to run containerized services. While the fog and edge computing can increase energy efficiency, reduce network traffic and provide better end user experience, the scale and volatility of the fog and edge also present new problems for service scheduling. In the edge, there are orders of magnitude more devices than in cloud data centers, and conditions are often less stable. Additionally, unlike in data centers, the network topology of the edge often changes, requiring a real-time approach to scheduling. In this demonstration, an implementation of a highly scalable orchestrator named “Swirly” is presented. The challenge of fog service scheduling is illustrated by using this implementation to organize software services in near real-time and on-demand in a virtual representation of a real-world industry park. Performance indicators are presented to show that this solution can scale up to 300.000 edge nodes.