A distinctive component of cloud-based applications is the elasticity control. This component facilitates the adaptation necessary for an application to maintain service quality in the presence of fluctuating demand. Elasticity control achieves this adaptation at runtime by managing the expansion and contraction of resource capacity in response to demand. How to design the rules of elasticity control is a central challenge when deploying cloud-based software. Many application providers express the need to manage the large fluctuations in demand associated with planned events, like marketing events. Existing reactive and predictive elasticity control strategies can be ineffective in managing the surges in workload associated with such planned events. This report will introduce a novel control strategy that integrates expert knowledge about planned events, along with runtime measurements and trend prediction from recent history. We will evaluate how well this strategy can maintain quality of service as planned events alter the load. The initial results presented in this paper are promising and suggest that making an elasticity controller aware of upcoming events is an effective strategy for dealing with event-associated surges in workload.