The increasing use of modern edge computing solutions in production is creating new opportunities for collecting and processing internal machine data. This data provides information on the load on a machine tool during operation. Using the technical expertise of component manufacturers, specific loads on individual components can be derived. This knowledge provides valuable insights for machine and component manufacturers to analyze the usage behavior of machine operators and use it for sustainable product development. Additionally, this information can be used to implement new business models, creating financial incentives for sustainable usage through load-oriented payment models. As a result, new potentials for users in efficient design and optimization of manufacturing processes arise. Data and service ecosystems play a crucial role in this context by establishing the technical framework that enables sovereign data exchange and the deployment of expert knowledge in the form of digital services. Therefore, this paper demonstrates a concept and the potential for sustainable machining based on digital services for two central components of a machine tool, the spindle and the feed axis.