With its rapid development, cloud computing has been increasingly adopted by scientists for large-scale scientific computation. Compared to the traditional computing platforms such as cluster and supercomputer, cloud computing is more elastic in the support of real-time computation and more powerful in the management of large-scale datasets. This paper presents our experience on designing and implementing seismic source inversion on both cluster (specifically, MPI-based) and cloud computing (specifically, Amazon EC2 and Microsoft Windows Azure). Our experiment shows that applying cloud computing to seismic source inversion is feasible and has its advantages. In addition, we notice that both cluster and Amazon EC2 have obviously better performance than Windows Azure. Cloud computing is suited for real-time processing scientific applications but it (especially Azure) does not work well for tightly-coupled applications.