To realize a chaotic system in digital world always leads a dynamical degradation of chaotic characteristics. Digital chaotic systems are increasingly utilized in modern cloud computing security architectures and big data analytics frameworks where precision degradation in large-scale, distributed, and heterogeneous environments can severely affect reliability. This paper focuses on the effects of fluctuations on digital chaotic systems and dynamical degradation related issues of those systems. A scheme based on hybrid structure is proposed for the solution to chaos degradation, in which the continuous chaotic system provides intrinsic random fluctuation. Further, the relationship between scaling of intrinsic randomness and chaos with different structure is studied. Symbolic dynamics is applied to rigorously prove that a class of digital systems is chaotic in the presence of fluctuations and to show that scaling behavior of fluctuations determines topological structure of chaos. Specifically, there are two critical fluctuation amplitudes at which topological structure of chaos essentially changes. Moreover, simulation studies are conducted to verify the theoretical results and further compare the effects of different random fluctuations on chaos degradation. These findings contribute to chaos-preserving mechanism designs applicable to precision-sensitive large-scale computing scenarios.