I really enjoyed the lecture. The structure is excellent. I think I've clearly understood what real-time communication is through just this one lecture.

It wasn't simply about covering the Flink platform, but also content where I could get a glimpse of that senior developer's perspective.

gjsu540607534

Most developers are still stuck on Batch and CronJobs when it comes to data processing. However, in real-world production environments, data is generated continuously, and failing to process that flow immediately leads to latency, bottlenecks, and consistency issues. Having personally dealt with real-time recommendations, state synchronization, and event delay problems in high-traffic environments, I’ve often asked myself, "Is batch processing really the right approach for this?" This course begins with that very question. It explores how to use Apache Flink to perform computations the moment data flows, manage state securely, and produce accurate results based on Event Time—all from a practical perspective. Beyond simple theoretical explanations, you will experience how real-time stream processing systems are designed and operated through actual source code and architectures. For those who found real-time processing vague or were curious about the world beyond messaging, this course will provide a clear sense of direction.

jhong

지식공유자의 깜짝할인

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

Hello, developer born in '02!! Thank you for leaving such a positive review!! As you mentioned, I wanted to provide a perspective that allows you to see things from a broader viewpoint rather than just simple usage methods.

I'll continue to provide more beneficial lectures in the future. Thank you for your review, and have a great day!!

실습 중심

backend basics

백엔드이해하기

실시간

toy to portfolio

토이프로젝트

백엔드

ほとんどの開発者は、データ処理について語る際、依然としてバッチ（Batch）やCronJobにとどまっています。しかし、実際のサービス環境ではデータが絶え間なく生成されており、その流れを即座に処理できなければ、遅延・ボトルネック・整合性の問題へとつながります。私自身も大規模なトラフィック環境で、リアルタイム推薦、状態同期、イベント遅延といった問題に直面し、「これをバッチで処理するのが正解なのだろうか？」と何度も悩みました。この講義は、まさにその問いから始まります。Apache Flinkを活用し、データが流れる瞬間に演算を行い、状態を安全に管理し、Event Timeに基づいて正確な結果を導き出す方法を、実務の観点から紐解いていきます。単なる理論の説明ではなく、実際のソースコードや構造を通じて、リアルタイム・ストリーム処理システムがどのように設計・運用されているかを体験できます。リアルタイム処理が漠然としていた方、メッセージングのその先の領域が気になっていた方にとって、この講義は明確な指針となるはずです。

Hong

입문

초급

중급이상

자바

Java

도커

Docker

docker-compose

flink

NAVERの面接官が使用するリアルタイム超低遅延プラットフォーム Apache Flink