Nowadays many companies become data rich and intensive. They have millions of users generating billions of interactions and events per day. These massive streams of complex events can be processed and reacted upon to e.g. offer new products, next best actions, communicate to users or detect frauds, and quicker we can do it, the higher value we can generate. Our presentation will be based on our recent experience in building a real-time data analytics platform for telco events. This platform has been jointly built by GetInData and Kcell - the leading telco in Kazakhstan - in just a few months and it currently runs in production at the scale of 10M subscribers and 160K events per second on a still small cluster. It's used as a backbone for personalized marketing campaigns, detecting frauds, cross-sell & up-sell by following the behavior of millions of users in real-time and reacting to it instantly. We will share how we build such platform using current best of breed open-source projects like Flink, Kafka, and Nifi. We won't skimp on the details how we designed and optimized our Flink applications for high load and performance. We will also describe challenges that we faced during development and try to provide some tips what one should pay attention to when developing similar solutions, not only for telco, but also for banks, e-commerce, IoT and other industries.