1. A method comprising: using one or more processors to perform the following: collecting and analyzing historic resource utilization data relating to a plurality of computing devices, the historic resource utilization data representing a load placed on a set of finite resources over a predefined period of time, wherein irrelevant data from the historic resource utilization data is identified and eliminated; generating an exponential growth model for each computing device based on analysis of the historic resource utilization data; generating a linear growth model for a particular computing device by adjusting the exponential growth model into the linear growth model when a defined criterion which pertains to the exponential growth model is met, wherein the defined criterion includes when the historic resource utilization data generates a slope of the exponential growth model that exceeds a threshold scale factor of a slope of an end of a most recent portion of the historic resource utilization data in the exponential growth model; creating a resource utilization forecast for each computing device from the exponential growth model or the linear growth model; receiving an assignment of a threshold value for the resource utilization forecast of each computing device; identifying an earliest forecasted date the threshold value is exceeded for the particular computing device based on the resource utilization forecast and the threshold value of each computing device; and sorting a number of resource utilization forecasts by the identified date for each of the number of resource utilization forecasts, wherein the number of resource utilization forecasts includes linear and exponential growth models.