Small and medium-sized Enterprises (SMEs) play a crucial role in the global economy by generating employment opportunities and fostering economic expansion. However, the allocation of cloud computing resources remains a significant challenge for small and mediumsized enterprises (SMEs). The primary objective of this qualitative study was to examine the challenges associated with the allocation of cloud computing resources in small and mediumsized enterprises (SMEs). The research encompassed a comprehensive examination of existing literature and the utilization of semi-structured interviews to gather data from small and medium-sized enterprise (SME) owners and managers. The study focused only on two developed nations, namely the United States of America and the United Kingdom, as well as two developing countries, namely India and Pakistan. The literature review identified many issues that have an influence on the allocation of cloud computing resources in small and medium-sized enterprises (SMEs). These challenges include financial constraints, organizational culture, availability of competent individuals, and advancements in technology. The insights obtained from conducting interviews with small and medium-sized enterprise (SME) owners and managers provided useful information on the current methodologies employed for assigning cloud computing resources, as well as the obstacles faced by SMEs in effectively distributing these resources. The study's findings indicate that the successful operation of small and medium enterprises (SMEs) heavily relies on the efficient allocation of cloud computing resources. Furthermore, addressing challenges in this area necessitates a purposeful and proactive strategy. The findings of this study offer valuable insights into the cloud computing resource allocation tactics employed by small and medium-sized enterprises (SMEs). As a result, policymakers, researchers, and SME owners and managers may utilize these insights to effectively implement successful strategies for allocating cloud computing resources.