This systematic literature review explores current trends and methodologies in DRA in cloud computing. In this regard, we looked into the following studies that help to figure out the future directions of the effectiveness of the resource management in cloud computing environments. We conducted a study on major academic databases for studies that focus on optimization algorithms, reinforcement learning techniques, scheduling strategies, and hybrid approaches published over the past half decade. We performed an appraisal on its methodology, effectiveness, and contribution. Our findings show, and underline challenge areas, that there has been significant progress in adaptive resource management of cloud infrastructure, but there still are areas that need to be improved, such as the machine learning complex model and hybrid approaches. Therefore, we here propose an innovative strategy for resource allocation in the cloud environment that incorporates new technologies, including real-time monitoring, predictive analytics, and self-healing. Therefore, the recommendations aim at the improvement of efficiency, scalability, and resiliency of the cloud resource management system, and hence are proposed to bring a holistic approach for future resource allocation strategies.