What makes a source–channel communication system optimal? It is shown that in order to achieve an optimal cost–distortion tradeoff, the source and the channel have to be matched in a probabilistic sense. The match (or lack of it) involves the source distribution, the distortion measure, the channel conditional distribution, and the channel input cost func- tion. Closed-form necessary and sufficient expressions relating the above entities are given. This generalizes both the separa- tion-based approach as well as the two well-known examples of optimal uncoded communication. The condition of probabilistic matching is extended to certain nonergodic and multiuser scenarios. This leads to a result on op- timal single-source broadcast communication.