Due to the higher level of automation than traditional agricultural systems, Controlled Environment Agriculture (CEA) applications generally achieve better yields and quality crops at the expenses of higher energy consumption. Digital Twin (DT) is considered a technology with the potential to bring CEA to new levels of productivity and sustainability. In this context, a monitoring Digital Twin (mDT) has been developed to provide services for the monitoring of the different subsystems of CEA facilities. By integrating open-source software tools, an architecture was built able to: i) gather different types of data collected from a CEA facility; ii) store the collected data and calculate relevant features from them; iii) locally and remotely display the assessed data. The implemented mDT has the potential to generate a database of CEA data that in future may be utilized by predictive and prescriptive algorithms to suggest actions able to improve the productivity and sustainability of the process.