Programmatic advertising is a core pillar in the business model for companies such as Alibaba, Amazon, Google, and many others. An important ingredient of programmatic advertising is auto-bidding in large-scale auctions, which makes this workshop highly relevant and exciting. A Demand Side Platform is a particular business model for programmatic advertising, and its goal is to optimally spend an advertising budget. The optimization is challenging due to an underlying high-dimensional, nonlinear, time-varying, dynamic, and stochastic plant. In this talk we introduce the optimization problem and demonstrate how techniques from control engineering can be used to analyze and solve the problem. The problem is decomposed into lower-dimensional sub problems and one of these problems is solved with the help of an adaptive feedback control system. We discuss challenges and opportunities, and we demonstrate a principled approach towards feedback control in online advertising. While the content is based on previously published work; the goal is for the audience to leave with an appreciation of the many open, interesting, and challenging feedback control problems available in programmatic advertising.