Abstract—Cloud computing has become the rapidly growing area in industry today with the advancements in the field of science and technology. There are cloud service providers who provide large scale computing infrastructures as services in a supple manner which the users can scale up or down based on the requirements. In present day scenario of the network cascaded with task consummation, and the aspect of heterogeneity along with platform divergence, dynamic load balancing plays a vital role in optimizing the performance of the server in the cloud computing environment. Developing a proficient load balancing algorithm and efficient usage of resources is the ultimate goal for the lead of optimized performance in a cloud network. Taking these factors into consideration, the proposed system applies Firefly Load balancing algorithm for the cloud in a partitioned cloud environment to balance the load across the variety of partitions. The central idea of the proposed work is to prepare the nodes capable to conceive the arriving load and attract the workload after analyzing various parameters that characterize the load and the node. A balance factor is calculated, which probabilistically defines the extent of balancing that ensues. Fuzzy logic is applied in accretion, to resolve the time uncertainties following the initial stage of load balancing. By applying this logic it is observed that, a better performance is achieved in terms of computational time, load arrived, task migration and the cost incurred.