Cloud computing is widely being used by researchers’ academia and industry for its abundant opportunities. Different technologies such as Internet of Things, Edge Computing, and Fog Computing are gradually integrating with the cloud platform due to its scalability and availability. The number of cloud users is also increasing exponentially. The requests generated from wide range of users are random. Executions of request and providing the quality of service are one of the promising issues in cloud environment. Optimization of response time and commutation cost is the major concern in cloud environment. Researchers have proposed many heuristics, meta-heuristic approaches for solving the load balancing issues in cloud platform. In this paper, authors have proposed a hybrid approach for load balancing in cloud computing using genetic algorithm with gravitational search algorithm. Simulations are carried out using cloud Sim Simulator and comparisons are made with other competitive approaches to evaluate the performance of the system. It is observed that the hybrid approach outperforms in various measures.