Real-time Ultra-low Latency Apache Flink Explained by a Naver Interviewer
Hong
Most developers still remain stuck with Batch and CronJob when talking about data processing. However, in real service environments, data is constantly being generated, and if you can't process that flow immediately, it leads to delays, bottlenecks, and consistency issues. I too have directly experienced real-time recommendation, state synchronization, and event delay problems in high-traffic environments, and have countless times wondered, "Is it right to handle this with batch processing?" This course starts from exactly that question. Using Apache Flink, it explains from a practical perspective how to compute data the moment it flows, safely manage state, and produce accurate results based on Event Time. Rather than simple theoretical explanations, you can experience how real-time stream processing systems are designed and operated through actual source code and architecture. For those who found real-time processing vague, or were curious about the world beyond messaging, this course will provide clear direction.
Basic
Java, Docker, docker-compose






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