  Industry 4.0 is changing fundamentally data collection, its storage and
analysis in industrial processes, enabling novel application such as flexible
manufacturing of highly customized products. Real-time control of these
processes, however, has not yet realized its full potential in using the
collected data to drive further development. Indeed, typical industrial control
systems are tailored to the plant they need to control, making reuse and
adaptation a challenge. In the past, the need to solve plant specific problems
overshadowed the benefits of physically isolating a control system from its
plant. We believe that modern virtualization techniques, specifically
application containers, present a unique opportunity to decouple control from
plants. This separation permits us to fully realize the potential for highly
distributed, and transferable industrial processes even with real-time
constraints arising from time-critical sub-processes. In this paper, we explore
the challenges and opportunities of shifting industrial control software from
dedicated hardware to bare-metal servers or (edge) cloud computing platforms
using off-the-shelf technology. We present a migration architecture and show,
using a specifically developed orchestration tool, that containerized
applications can run on shared resources without compromising scheduled
execution within given time constraints. Through latency and computational
performance experiments we explore limits of three system setups and summarize
lessons learned.
