Why is digitalization becoming one of the main assets for wind power energy? Wind farms today boast higher capacity factors, indicating that they are producing more energy relative to their installed capacity. Improved design, coupled with advancements in predictive analytics and control systems, have optimized the performance of wind turbines, making them more reliable and productive. The interest in renewable energy and, particularly, in wind power accelerated dramatically as the war in Ukraine took place. For the first time in history the investment in renewables was the primary response to an energy crisis. The increase in wind power capacity involves some new challenges. Older wind turbines are more prone to failure due to aging and at the same time this must be predicted as accurately as possible for the newer ones, based on data collected in real-time in the field. Predictive maintenance can save a lot of time and money by having the right number of spare parts in stock in the right location. Applying DevOps principles to Big Data predictive analytics can help optimize the use of resources and workflows. This produces major improvements to the spare part recommendation based on IoT data. This presentation illustrates how DevOps practices and related Open-Source tools help build an efficient software infrastructure where wind turbines lifetime predictions and spare part stock recommendations are delivered regularly to service engineers.