In this study, we use the respective advantages of the tabu search (TS) and the cloud computing technologies to develop a cloud-based decision support system (DSS) for cell formation (CF) problem. To further verify the feasibility and effectiveness of the developed system, an example taken from the literature is adopted for illustrational purpose. Moreover, a set of test problems with various sizes drawn from the literature are used to test the performance of the proposed system. Corresponding results are compared to several well-known algorithms previously published. The results indicate that the proposed cloud computing CF DSS improves the best results found in the literature for 50% of the test problems. Moreover, with the assistance of our developed system, the CF practitioners in the production departments can interact with the systems without knowing the details of algorithms and can get the best machine cells and part families with maximize grouping efficacy wherever and whenever they may need it. These show that the proposed CF DSS should thus be useful to both practitioners and researchers.