Current Data Center (DC) simulators focus more on resource management and deployment of applications, including the new virtualization technologies that can be used to simplify the deployment and improve resource efficiency. While this is an important perspective for the Development and Operations (DevOps) engineers, DC operators on the other hand have different priorities, especially the infrastructure challenges such as cooling and power consumption, and how changes in the workload will impact the energy efficiency of a DC. A DC simulator, which can consider the environmental impact, and evaluate the different sustainability metrics, can lead to more energy efficient and sustainable DCs in the future. Hence the main target of this research is to study the different sustainability metrics and their input parameters to determine the minimum number of commonly reused inputs that are expected to evaluate the maximum number of sustainability metrics, which consequently helps in designing more energy efficient and green DCs. This can be done by selecting the commonly reused set of inputs and metrics, and researching the parameters that are essential to assess and evaluate the sustainability metrics of a DC. It requires a detailed study and profound elaboration and analysis of the set of metrics and inputs including their interrelationships, and experimenting how changes in the DC parameters are reflected in the metrics. There are many metrics classifications available to evaluate the different key performance indicators. A collective and integrated classification of these sustainability metrics is provided in [VSR+17]. The paper classifies the metrics into 9 categories, starting with the energy efficiency metrics down to the financial metrics, and it gives the mathematical equations required for calculating the different sustainability metric.