Recent research in cloud usage patterns focuses on understanding and modeling how users and organizations consume cloud resources over time to improve efficiency, scalability, and cost management. Studies analyze workload characteristics, access frequency, and scaling trends to identify recurring patterns that influence resource provisioning and pricing strategies. Machine learning and statistical models are often employed to predict demand fluctuations, optimize scheduling, and enhance auto-scaling mechanisms. By uncovering usage trends across diverse cloud environments and applications, these research efforts enable more intelligent resource allocation, better energy management, and improved Quality of Service in dynamic multi-tenant cloud infrastructures.