Cloud providers are constantly seeking to become more cost effective, where a common strategy is to consolidate multiple applications in physical machines using virtualization techniques. This consolidation, however, may result in performance related problems such as resource interference. Moreover, if the workload is composed of multi‐tier applications, an increasingly popular method of application development, especially for web and mobile, in which tiers need to communicate through the network, we have another possible source of performance degradation, which we refer as network affinity. In order to reduce the effects of such problems, placement techniques are used to better distribute the applications in the physical machines. Several of these placement techniques consider resource interference or network affinity in order to decide the best placement, however, none of them apply both criteria at the same time. In our previous work, we identified that a combined approach could result in better solutions for this problem and proposed a set of placement policies that explore this tradeoff. In this paper, we propose placement algorithms based on these policies and evaluate the proposed solutions for different workload scenarios using a visual simulation tool we developed called CIAPA. CIAPA introduces a performance degradation model, a cost function, and heuristics to find a placement with the minimum cost for a specific workload of multi‐tier applications. In our preliminary experiments, we compared the solution generated by CIAPA with other placement strategies from related work, and have verified that, for the tested scenarios, it delivers placement decisions with better cost and, consequently, improved performance. We observed a reduction in response time of 10% when compared to interference strategies and up to 18% when considering only affinity strategies.