Cloud computing became a popular IT and business trend in recent years, due to its scalability, reliability, ease of access and low costs. The demand for cloud services has led to a steep increase in number and size of data centres around the world with more hardware dense, large-scale data centres being build. A modern data centre has become a very complex system with a multitude of interconnected hardware resources that is hard to manage in an autonomic and cost-effective manner. This thesis presents novel techniques, models and software for estimating the impact of data centre planning decisions on Total Cost of Ownership. The use of a Discrete Event Simulation (DES) framework as a decision support tool is proposed for understanding operational efficiencies and the financial implications of different cloud resource management techniques and different hardware components. Based on a detailed assessment of the current state of cloud simulation tools, resource management techniques and cost models available for data centre management, an on-the-fly compilation of simulation models for large-scale cloud data centres has been proposed and delivered. This enables an automated approach for extracting all required simulation modelling parameters from existing data centre monitoring tools, improving speed and usability of the simulation approach. A unique integration approach between a production grade cloud optimisation framework and an offline simulation analysis framework, enables direct simulation of cloud resource management policies allowing for experimentation of different “what-if” scenarios using existing production tooling. An improved set of cost models were developed alongside the simulation framework which are capable of calculating costs based on time series data produced by the simulation framework. Thus, taking into account resource management policy effects and enabling a more granular overview of costs when compared to traditional TCO calculation approaches. The simulation framework implementation was validated using real case study data. In addition, the practical use of the proposed cloud data centre decision support approach is demonstrated through presentation of an extended case example, estimating and planning for the impact of a data centre hardware upgrade and resultant system performance and costs.