The world is data, and everyone uses it, but building a production ready system at scale comes with its own challenges. The main ones are how to stream the data quickly enough, how to make the right decision and use it until it's relevant, and how to return to the decisioning model. During the talk, I'll share my own experience in: • Which language is more appropriate for each microservice composing the system, enterprise favorite Java or data scientists’ pick Python? • What type of transport to choose? • Where should each component be deployed? • Where and how much data should be stored to balance costs and ML training? I will share design considerations and potential problems and solutions I have found along the way, describing a real-world production scenario. I will demo event streaming with Apache Kafka and decision making with a TensorFlow ML model.

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Anton is а Senior Software Engineer at Experian, with more than 15 years of experience in software development. In the last 5 years, he has participated in the design and development of several projects like the one in the talk, where he also used Python and Go alongside Java. He is a Stack Overflow enthusiast with moderation privileges. He likes to spend his free time with his family and in the mountains.