The Earthquake Agency of Tianjin Municipality realized a seismic data transmission network by constructing a digital seismological observation network. The seismic waveform data is real-time stored in the AWS data server, and users can call the data from the AWS server by a man-machine interface system. Therefore, the seismic system operation generates load in the server hardware and software, thus affecting the system overall efficiency. In this study, we use a Python-based algorithm of time series to predict the disk capacity of the AWS server and estimate the load rate of the storage server, thus avoiding the occurrence of system paralysis because of storage capacity depletion. The real-time data of stations can also be monitored by the algorithm, and variation curves of station data can be accordingly generated.