Microservices have emerged as a preferred architectural style for developing scalable and resilient applications, especially within cloud environments. This approach offers significant advantages over traditional monolithic architectures, such as enhanced scalability, flexibility, and fault isolation. However, these benefits come with substantial operational costs. Running microservices on cloud platforms incurs high expenses due to the need for extensive monitoring, complex service management, and dynamic resource allocation. Industry solutions have primarily focused on monitoring and management, leaving a gap in comprehensive strategies for cost reduction through optimization and resource management. This study aims to identify and analyze the primary cost drivers of running microservices and assess their individual impacts. By providing a detailed analysis, this research enhances the understanding of cost factors, aiding in the cost management and optimization of cloud-based microservices. This knowledge helps businesses make informed decisions to minimize expenses while maximizing the benefits of cloud adoption. Key cost drivers identified include virtualization mechanisms, scaling solutions, microservice architectures, and API designs. Microservices vary significantly in terms of performance and resource consumption depending on their design and architecture. However, by following certain best practices, it is possible to reduce the overall running costs of microservices by minimizing resource consumption.