Cloud computing refers to a parallel and distributed architecture which consists of provisioned and interconnected, powerfully and virtually provisioned computer systems. According to SLAs (Service Level Agreements) created through client-provider interaction, these systems function as a single, cohesive computing resource. Effectiveness in cloud-based settings is crucial for modern enterprises looking to lower energy consumption, limit resource utilization, improve workload management, and decrease response time. Time Management is essential for maximizing the distribution of load and cutting down on completion times in the cloud. Balancing load within a server pool helps distribute incoming server requests effectively, aiming to make the use of energy minimal while maximizing system functioning. Despite several load balancing methods proposed in recent years, many fail to produce the desired results. This paper put forwards a hybrid optimization solution that unifies the ACO and SA algorithms to manageload in the cloud. The ACO and SA algorithms have been compared with the suggested approach, which is implemented in MATLAB, with respect to resource usage, response duration, and use of energy.