To handle large peak loads resource over provisioning is the simple solution but due to the high cost and limited resource capacity at edge nodes over provisioning of resources is unsuitable. The study aims to provide the insights of the Docker containers in various computational environments and potential benefits of the proposed hybrid approach using genetic and falcon optimization algorithms. The proposed system increases the performance with limited resources, less hardware and meta-heuristic optimization algorithm used for balancing the load. Experimental simulation using java cloudsim shows availability of resources for execution of the task and performance analysis for dynamic load balancing using performance parameters like average waiting time, process time, latency, execution time and throughput. The simulation execution validates the proposed hybrid meta-heuristic algorithm on computational storage architecture using resource-based approach. It gives improvement in the throughput around 37–39% appx and reduced latency by 0.04421, 0.3690 ms appx also execution time reduced by 29% appx over optimization algorithms used for scheduling in the cloud environment.