The widespread adoption of cloud technology has been hindered by its high costs, which often serve as a barrier preventing many organizations from considering its implementation. Existing solutions in the market tend to be constrained by specific infrastructure types, limiting their effectiveness. This master thesis aims to address this challenge by presenting a novel approach to reduce the cost of cloud computing. Our contribution involves the development of a linear model that computes a suitable combination of commitments for a given cloud usage. Through rigorous experimentation, our results demonstrate the efficacy of our model in effectively reducing costs for cloud users. A significant advantage of our approach is its ability to be applied on-the-fly to any type of infrastructure, providing flexibility for cloud cost optimization. This research brings valuable insights and practical solutions to the industry, enabling organizations to leverage cloud technology while minimizing their financial burden.