Study of fluctuation in genetic algorithm has been a sub-objective in genetic algorithm implementations. The reliability of genetic algorithm may vary based on implementation case, hence it is necessary to investigate its performance pattern for each implementation case. The purpose of this study is to observe the reliability of genetic algorithm in our previously simulated network optimization in a data centre. Previous researchers found fluctuation as random occurrence, mainly within small population. This paper's fluctuation observation revolves around our recent optimization of data centre's network. Our findings agree with the nature of genetic algorithm and other researches, where it is found that the fluctuation of fitness values in our case happened randomly in general, but it had higher probability with small population size. However, regardless of fluctuations that in average occurred during early stage of population generation, the near-optimal solutions with near maximum fitness values were able to be generated. This fact has proven the robustness of genetic algorithm itself.