In the field of cloud computing, Infrastructure as a Service (IaaS) provides virtualized on-demand computing resources on a pay-per-use model. IaaS Cloud differ from traditional mutualized infrastructures in that the resources can be dynamically claimed and released, and the real hardware infrastructure is unknown to its users. These properties drastically changes the way resource pro-visioning and job scheduling can be addressed by the user because i) the large number of jobs and resources to handle becomes rapidly overwhelming for human operators, and ii) the real performances of the platform should be inferred from observations to make robust scheduling decisions. In order to optimize the resources usage by the client, we advocate the need for brokers on the client-side. This article presents our work based on Schlouder, a broker of IaaS cloud resources able to provision and schedule independent jobs or static work-flows according to strategies chosen by the client. Further, we advocate that simulation can be a precious auxiliary to help the user to choose between provi-sioning strategies. Schlouder brings a unique feature which is to predict through simulation the makespan and cost of executions under various strategies. The contribution of this work is twofold. First, it presents the broker, available as an open source project, in which new provisioning strategies can be plugged in by third parties. The effectiveness of the tool is demonstrated through experiments involving actual applications and platforms. Second, we show that simulation produces accurate predictions making this feature a helpful means for the user to choose the appropriate strategy.