Through the use of a comparative analytical methodology, this study investigates the optimization of performance in hybrid cloud computing. Performance metrics, mistake rates, and resistance to attacks from the outside are the three significant features that are investigated in this research. A number of metrics, such as the number of affected blocks, training time, validation time, and testing time, are measured and compared throughout the course of the study, which makes use of both conventional and proposed methods. The technique that has been developed has the objective of enhancing the efficiency and dependability of hybrid cloud environments by determining the most effective strategies for the distribution of workloads, the allocation of resources, and the implementation of security measures. The purpose of this abstract is to provide a succinct outline of the study scope, techniques, and projected contributions to the subject of hybrid cloud computing optimization.