As virtualization platforms or cloud computing have become more of a commodity, many more organizations have been utilizing them. Many organizations and technologies have emerged to fulfill those cloud needs. Cloud vendors provide similar services, but the differences can have significant impact on specific applications. Selecting the right provider is difficult and confusing because of the number of options. It can be difficult to determine which application characteristics will impact the choice of implementation. There has not been a concise process to select which cloud vendor and characteristics are best suited for the application requirements and organization requirements. This thesis provides a model that identifies crucial application characteristics, organization requirements and also characteristics of a cloud. The model is used to analyze the interaction of the application with multiple cloud platforms and select the best option based on a suitability score. Case studies utilize this model to test three applications against three cloud implementations to identify the best fit cloud implementation. The model is further validated by a small group of peers through a survey. The studies show that the model is useful in identifying and comparing cloud implementations with regard to application requirements.

Cloud technology requires a virtualized ubiquitous and scalable environment with shared resources. The general problem in cloud adoption is the absence of standardization across organizations. A standardized approach remained elusive since the inception of the Cloud First mandate. The purpose of this study was to explore leader-initiated change management (LICM) practices in cloud adoption within organizations. The theoretical framework included the classical theories of Kurt Lewin's organization change management, leader-member exchange, intentional change, and appreciative inquiry. A multiple case study design approach facilitated the exploration of LICM-value added practices to identify standardization in cloud adoption practices. Data collection included semistructured interviews from 8 high-level cloud adopters chosen from a resource pool of change management experts including a government chief information officer, academic college professor, military commander, and industry chief executive officer. Each interviewee represented an organization type providing perspectives on strategies for cloud adoption. Secondary data gathering included universal cloud standards and guidance from collaborative professional working groups. Emergent themes were identified after completing Yin's 5 stages of data analysis: LICM approaches for cloud decision-making, change management strategies, leader empowerment in action planning with progressive metrics, and successful learning outcomes in corporate universities. LICM strategies foster cooperative relationships and positive social change. Standardized cloud adoption practices also contribute to positive social change in reducing the environmental footprint through organizational efficiency.