KTWIN: A Serverless Kubernetes-based Digital Twin Platform
Alexandre Gustavo Wermann, Juliano Araujo Wickboldt
TL;DR
KTWIN addresses the need for an open, vendor-neutral, edge-to-cloud Digital Twin platform by integrating a Kubernetes-based Serverless architecture with an extended DTDL modeling layer and a Kubernetes Operator. The approach automates DT component provisioning, event routing, and data storage using Cloud Native tools (Knative, RabbitMQ, Redis, ScyllaDB) across control and application planes. Key contributions include the extended DTDL-based CRDs, the KTWIN Operator, and a New York City Smart City use case that demonstrates scalable performance and meaningful cost savings (roughly 60-80% vs over-provisioned). The work has practical impact by enabling flexible, scalable, and interoperable DT deployments with reduced operational overhead in edge-to-cloud environments, while remaining open for future enhancements and broader DT scenarios.
Abstract
Digital Twins (DTs) systems are virtual representations of physical assets allowing organizations to gain insights and improve existing processes. In practice, DTs require proper modeling, coherent development and seamless deployment along cloud and edge landscapes relying on established patterns to reduce operational costs. In this work, we propose KTWIN a Kubernetes-based Serverless Platform for Digital Twins. KTWIN was developed using the state-of-the-art open-source Cloud Native tools, allowing DT operators to easily define models through open standards and configure details of the underlying services and infrastructure. The experiments carried out with the developed prototype show that KTWIN can provide a higher level of abstraction to model and deploy a Digital Twin use case without compromising the solution scalability. The tests performed also show cost savings ranging between 60% and 80% compared to overprovisioned scenarios.