Saving checkpoints too frequently slows training, while too sparse a schedule makes rollbacks costly; a common practice is to trigger on both a time interval (e.g., every 30 minutes) and a step interval, and to write to disk only from the main process to avoid multi-GPU concurrent write conflicts.