Infrastructure is critical for the effi cient operation of Local Digital Twins (LDTs) by supporting both governance commitments and technical needs. Effective data fl ows, whether real-time, continuous, batch, or event-driven, require the right infrastructure to meet specifi c demands such as low latency, bandwidth, reliability, and data processing location. Successful infrastructure enables actionable insights from raw sensor data. Choosing the right infrastructure involves tailoring it to the specifi c data fl ow type. Real-time scenarios require low-latency networks and edge processing, while batch processing can leverage scheduled uploads and centralized servers. Adopting edge, cloud, or hybrid architectures impacts factors like latency, resilience, and compliance. The correct architecture ensures effi cient fl ow and supports governance goals. This unit teaches stakeholders to design infrastructure aligned with governance and fl ow needs, focusing on real-time, continuous, batch, and event-based data fl ows. Participants explore processing architectures like edge, cloud, and hybrid models, considering cost and regulatory compliance. Activities guide them in mapping fl ow scenarios to network strategies, encompassing redundancy and resilience in design planning.