In recent years, worldwide, with the development of technology, a huge amount of data is collected in Electronic Health Records (EHRs). Although vast progress has been made with the use of artificial intelligence in various areas of health domain and for specific problems, it is a fact that to date there is no holistic approach to a patient’s state of health using these technologies. Digital Twin refers to a complete physical and functional description of an item, product, or system, which includes pretty much all the information that could be useful in all—current and next—life cycle phases. This paper presents a platform that, using state of the art technologies such as Microservice Architecture (MSA), containerization (Docker), orchestration (Kubernetes) and Machine Learning Operations (MLOps), whereas it is inspired by Leonardo DaVinci’s Vitruvian man, building the Digital Twin of Patient platform. To achieve that, the platform’s architecture is designed with multiple clusters of Docker containers and Kubernetes orchestration. Specific parts or organs of the human body, are represented by clusters called “digital_twin_components”—DTCs. The set of those DTCs structure the “patient_digital_twin” cluster in which appropriate pipelines define and monitor in real time the “best” possible construction of the patient’s digital twin.