To deploy a distributed application on the cloud, cost, resource and communication constraints have to be considered to select the most suitable Virtual Machines (VMs), from private and public cloud providers. This process becomes very complex in large scale scenarios and, as this problem is NP-Hard, its automation must take scalability into consideration. In this work, we propose a heuristic able to calculate initial placements for distributed component-based applications on possibly multiple clouds with the objective of minimizing VM renting costs while satisfying applications' resource and communication constraints. We evaluate the heuristic performance and determine its limitations by comparing it to other placement approaches, namely exact algorithms and meta-heuristics. We show that the proposed heuristic is able to compute a good solution much faster than them.