In this talk, I would like to share the successful experience our team is having implementing Kafka within a complex data architecture. Although I have the blessing of leading a team of incredibly talented Engineers, none of us had the experience of working with Kafka in the scale we face at Mimecast, where hundreds of microservices generate millions of events per second to communicate asynchronously to achieve different goals. The talk will explain how Kafka is helping us to decouple Microservices and make data available for teams and services that were not in communication before. I will highlight the challenges we encountered and how we overcame them, like having one Kafka Cluster per region going across to our double data center architecture and still avoiding a split-brain scenario, serving thousands of producers and consumers, explaining in plain language the main Kafka components and how they are used to solve problems. I would like to share how Kafka is allowing our Data Scientists to explore the data since we are able to replay the input data as many times we need, discovering new features and more importantly, been able to reproduce exactly the same scenario over and over. Last but not least, the talk will emphasize the fact, like in our case, newcomers do not have to pay a steep learning curve to make the intimidating Kafka Platform part of their solution, the documentation is fantastic, the community is amazing and examples could be found all over the internet.