Apache Flink, a real-time ultra-low-latency platform used by Naver interviewers

Most developers still think in terms of Batch and CronJob when discussing data processing. However, in real-world service environments, data is generated continuously, and failing to process that flow immediately leads to delays, bottlenecks, and data consistency issues. I have also repeatedly faced the question, “Is batch processing really the right approach?” while dealing firsthand with real-time recommendations, state synchronization, and event delays in high-traffic environments. This course starts from that very question. It explores, from a practical perspective, how to use Apache Flink to perform computations as data flows in, manage state safely, and produce accurate results based on Event Time. Rather than simply explaining theory, it allows you to experience how real-time stream processing systems are designed and operated through actual source code and architectures. For those who have found real-time processing vague or wondered what lies beyond messaging, this course will provide a clear direction.