Internet of Things (IoT) systems are distributed collections of embedded systems that are connected over the Internet or similar networks. A key property of IoT systems is the need for high reliability throughout their lifespan under physical constraints, e.g., material properties, and natural degradation of system components. Simulation and digital twin approaches can quantify statistical assurances at design time and runtime respectively to verify reliability of IoT systems. However, existing approaches lack integration through a multi-paradigm modeling approach for seamless design time and runtime reliability verification, sole use of mature standards and protocols for interoperability and easy extension, and state-of-the-art statistical model checking (SMC) techniques for sound and efficient reliability verification. Consequently, we propose a service-oriented digital twin architecture and implement the architecture in a production-grade, interoperable, and radically distributed scale out process engine that integrates both design and runtime verification in a single model. We demonstrate our architecture and implementation for four IoT systems and report statistical reliability assurances through sound and efficient SMC.