This paper investigates the computation time optimization of a software tool for critical infrastructure simulation. First, modifications to the input data processing module are presented to increase the efficiency of data retrieval and reduce processing time. Next, the effect of different data formats on computational time and memory load is analyzed. Tests showed that some formats provided significant improvements in data processing speed and reductions in data file size. The next step was the deployment of a software tool in the supercomputing infrastructure, which allowed the optimization of computation time through orchestration in Kubernetes. The modified architecture of the software tool allows efficient use of computing power from the computing center only for running simulations, while administrative tasks are performed on the user’s local device. This integration into the supercomputing infrastructure provides the ability to run the software tool on different devices with sufficient computing power as needed.