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

Limitations of LLMs? We provide solutions to real-world problems using RAG trial-and-error and operational know-how experienced in the field in Silicon Valley.

You know AI agent frameworks, but is it difficult to understand the principles and apply them in practice? I will share everything from core principles to practical applications based on my direct experience in Silicon Valley.

Kotlin mastery via virtual payment server course.

It was created to solve the "overwhelming problem of not knowing where or how to start with Kubernetes." Based on hands-on experience operating financial infrastructure, it is designed to help you understand the actual build and operation flow rather than just simple theory. Through a learning process that covers the relationship with Docker, YAML, Pods, Deployments, and Services, learners will master Kubernetes not just as a "concept," but as a "usable skill."

This is a Redis course created with a current Kakao interviewer. It covers everything from data structure practice (String to Sorted Set) to Sentinel and Cluster configurations, helping you build design rationales that work in both interviews and real-world practice.

This course covers RPC communication techniques to maximize performance in large-scale MSA (Microservice Architecture) environments. Beyond simple gRPC practice, you will learn how to implement stable and efficient inter-service communication in real-world production environments where hundreds of microservices operate simultaneously. Based on Golang, the curriculum focuses on practical applications, including writing Protocol Buffers (proto) syntax, automated code generation and service implementation, the structure of gRPC and its advantages over traditional RPC, and performance optimization strategies. Designed to be easily understood even by non-majors or entry-level server developers, the course explains everything from the basic concepts of RPC to the internal workings of gRPC step-by-step, helping you build practical skills that can be applied immediately to real services.

Systematically learn the distributed NoSQL database Cassandra, from basic concepts to practical application. Develop high-volume data processing capabilities through practice-oriented theory and hands-on exercises, including data modeling, query optimization, and cluster configuration. Even without prior database experience, you can grow into a Cassandra expert based on the know-how of a current Silicon Valley developer.

When you find yourself constantly updating Swagger documentation, aligning API specs, and repeatedly communicating with the frontend, you start to wonder, "Why am I doing the same thing twice?" I also felt similar frustrations in my professional experience, which led me to use GraphQL extensively and develop an interest in data-centric design. This course goes beyond simple GraphQL syntax; it explores the real-world problems it was created to solve, along with practical considerations like Resolver structures, the N+1 problem, and Federation. I've structured this course to help you naturally learn how to reduce communication costs between developers and design more flexible API structures.

This course goes beyond simple CRUD-level database usage to help you acquire PostgreSQL skills necessary for the AI era from a practical perspective. Based on AI development experience in Silicon Valley, you will learn step-by-step how to design and utilize JSON, indexes, transactions, and even pgvector in real-world services, while mastering methods to solve complex data structures and performance issues.

The biggest challenges in operating batch systems that process millions of records are performance degradation and the difficulty of recovery in the event of a failure. These issues cannot be solved with simple loops or poor design. Based on my experience of reliably processing large-scale data in real-world service environments, this course covers the structure and operating principles of Spring Batch and provides design methods to achieve both performance and stability. Moving beyond simple functional descriptions, this course will help you develop fundamental data processing problem-solving skills through batch architectures that can be applied immediately in practice.

This course is for developers who want to find fundamental solutions in environments where response times slow down as traffic increases, thread pools are quickly exhausted, and bottlenecks worsen with more external API calls. It helps you look at problems from the perspective of changing the architecture itself, rather than simply scaling out servers. Through this course, you will first understand the limitations of the traditional Spring MVC "Thread per Request" model. You will examine at the code level why throughput doesn't increase even when CPU resources are available, and exactly how blocking I/O occupies system resources. Next, you will learn the concepts and standard specifications of Reactive Streams and master how to handle data streams using Reactor's Mono and Flux. Beyond simple usage, you will learn through hands-on practice how data flows start, how they are consumed, and how throughput is controlled. In particular, you will directly implement design patterns that prevent OOM (Out of Memory) or overloads using Back Pressure. Additionally, you will understand the event loop-based processing structure of Spring WebFlux and conduct comparative exercises on how Non-Blocking I/O operates during actual request processing. By placing MVC and WebFlux side-by-side to verify their structural differences, you will also establish criteria for when to choose Reactive. This goes beyond simply "learning asynchrony." You will learn how to handle more requests with fewer threads, how to maintain a stable flow in environments with high external API dependencies, and develop the design intuition to secure throughput in high-concurrency environments.

This course goes beyond simply teaching you how to use Docker as a tool; it approaches the subject from the perspective of solving the real-world dilemmas and problems encountered in professional practice. From unpredictable errors caused by differences between development and production environments, to configuration mistakes stemming from vague concepts of images and containers, and even the anxiety of "how much do I need to know to survive in the field"—this course explains it all based on firsthand experience operating financial infrastructure. Rather than just listing commands, it focuses on real-world cases: why certain structures are necessary, how to design images for easy maintenance, and how to handle containers for stable service operation. In particular, by prioritizing hands-on practice over theory, the course is designed to elevate students from simply "knowing how to use" Docker to "understanding it from an operational perspective" through visual comprehension and direct experience. This course provides practical standards and direction for those new to Docker, those who have used it but lack a clear conceptual grasp, and developers looking to take their infrastructure intuition to the next level.

This course focuses on solving the problem of getting stuck in interviews and practical work due to a lack of understanding of why certain structures and configurations are necessary, rather than just teaching how to configure NGINX. Based on experience evaluating numerous candidates as an interviewer for companies like Naver, Kakao, and Toss, I explain how to describe and utilize NGINX from the perspectives of performance, scalability, and operations through hands-on practice. The core of this course is to help you develop a mindset capable of tracing traffic flow and troubleshooting problems, rather than just memorizing configuration values.

This course was created to solve a common problem many people face while preparing for developer jobs: "I studied CS and data structures, but I get tongue-tied during interviews." While conducting actual interviews at companies like Naver, Kakao, and Toss, I noticed that most candidates have memorized concepts but cannot explain why those concepts are necessary or how they are applied in real-world situations. Rather than simple rote memorization, this course teaches you how to understand the interviewer's intent and provide more persuasive answers to the same questions. Whether it's the OSI 7 layers, data structures, or coding tests, we focus on why you need to know them, when they are used, and how to speak about them to receive a positive evaluation in an interview. This course is for those who want to become developers who can explain what they understand in their own words, rather than just giving the same answers as everyone else.

At some point in backend development, you start to have these concerns. It's that moment when services expand and traffic increases, and you begin to feel the limitations of simple REST communication and CRUD structures. I experienced these same issues in the field and went through much trial and error balancing performance and structural complexity. The solution I chose during that process was NATS. Its simple configuration based on a single binary, ultra-low latency performance in microseconds, and the fact that it provides essential features—from Pub/Sub to Queue Groups and JetStream—without being overkill made it a very practical choice for real-world service environments. This course is not just a list of NATS features. Based on the problems I faced in practice, I explain through code and workflows why I chose NATS in certain situations and how I designed the architecture. This course is designed to help everyone—from those new to messaging systems to backend developers preparing for employment and senior developers considering better architectures—understand distributed systems and grow to the next level.

This course breaks down microservice architecture and distributed environments not as a mere list of technologies, but through the "design perspective" required in actual practice and interviews. Starting from the differences between Monolithic and MSA, it covers gradual migration strategies, Modular Monoliths, Clean Architecture, and Hexagonal Architecture step-by-step, clearly explaining why each choice is necessary and the resulting trade-offs. Furthermore, through hands-on practice, you can directly verify the intent of the structures and learn about core issues inevitably encountered in distributed environments—such as data consistency, transactions, inter-service communication, and fault tolerance—through realistic scenarios. Based on the actual questions and perspectives of a Kakao interviewer, this course aims to go beyond simple knowledge acquisition and elevate your very way of thinking about distributed systems to the next level.

This course provides a step-by-step learning path, ranging from the fundamental usage of MySQL to advanced techniques required in real-world production environments. It covers a wide range of topics, including data modeling techniques based on various case studies and practical data, evaluating the effectiveness of Foreign Key designs, analyzing Google Calendar schema DDL, and modern DDL design principles. Through this course, you will gain an in-depth understanding of how to utilize MySQL as a core system component rather than just a simple database.

Learn the SAGA transaction management technique for maintaining data consistency in distributed environments through a hands-on approach. You will configure three microservices using Spring Boot and Docker, and implement both Orchestration and Choreography patterns using Kafka and MySQL. Through this course, you will master core concepts applicable to real-world scenarios, including the operational principles of distributed transactions, designing compensating transactions, and handling fault recovery.

Learn the process of building essential Observability in a Microservices Architecture (MSA) environment, from the basics to practical application. You will master standardized data collection using OpenTelemetry, trace storage and search via Grafana Tempo, and visualization using TraceQL through step-by-step hands-on exercises. You will learn how to track service flows, identify bottlenecks, and analyze the root causes of failures through distributed tracing.

Learn the process of building data pipelines using Apache Airflow, from the basics to practical application. Understand the core concepts and architecture of Airflow, and master advanced design patterns frequently used in the field—such as dynamic DAGs, parallel processing, distributed processing, and custom operators—through hands-on practice. Configure a practice environment using Python and Docker to develop the practical skills needed to design and operate real-world workflows.

At some point in backend development, you start to have these concerns. It's that moment when services expand and traffic increases, and you begin to feel the limitations of simple REST communication and CRUD structures. I experienced these same issues in the field and went through much trial and error balancing performance and structural complexity. The solution I chose during that process was NATS. Its simple configuration based on a single binary, ultra-low latency performance in microseconds, and the fact that it provides essential features—from Pub/Sub to Queue Groups and JetStream—without being overkill made it a very practical choice for real-world service environments. This course is not just a list of NATS features. Based on the problems I faced in practice, I explain through code and workflows why I chose NATS in certain situations and how I designed the architecture. This course is designed to help everyone—from those new to messaging systems to backend developers preparing for employment and senior developers considering better architectures—understand distributed systems and grow to the next level.

Pass the Information Processing Engineer practical exam in one go! We pinpoint only the core code and theory for you. Master past exam questions perfectly! Open the door to passing with our systematic lectures. 🏆 2024 Inflearn Rookie Award 🏆 2025 Students' Pick Award

Have you ever wondered "how" the many Java libraries and frameworks you use provide this functionality? In this course, learn how to manipulate various codes or objects provided by Java and take your Java skills to the next level.

This course is designed to prepare you for the Information Processing Engineer practical exam solely through solving previous exam questions. Instead of unnecessary theories or vast amounts of content, it focuses on past exam questions that are repeatedly featured, allowing you to connect your learning directly to passing the exam. You can quickly grasp core points and question patterns by reflecting on the latest trends, and even learn tips for writing answers through the problem-solving process. This lecture is optimized for examinees aiming to pass efficiently in a short period of time.

This contains everything you need to truly get started with Kubernetes (☸). 🧭 Through this course, you can begin your journey with the easiest way to understand the structure of Kubernetes. 🥇

This course goes beyond simply teaching you how to use Docker as a tool; it approaches the subject from the perspective of solving the real-world dilemmas and problems encountered in professional practice. From unpredictable errors caused by differences between development and production environments, to configuration mistakes stemming from vague concepts of images and containers, and even the anxiety of "how much do I need to know to survive in the field"—this course explains it all based on firsthand experience operating financial infrastructure. Rather than just listing commands, it focuses on real-world cases: why certain structures are necessary, how to design images for easy maintenance, and how to handle containers for stable service operation. In particular, by prioritizing hands-on practice over theory, the course is designed to elevate students from simply "knowing how to use" Docker to "understanding it from an operational perspective" through visual comprehension and direct experience. This course provides practical standards and direction for those new to Docker, those who have used it but lack a clear conceptual grasp, and developers looking to take their infrastructure intuition to the next level.

It was created to solve the "overwhelming problem of not knowing where or how to start with Kubernetes." Based on hands-on experience operating financial infrastructure, it is designed to help you understand the actual build and operation flow rather than just simple theory. Through a learning process that covers the relationship with Docker, YAML, Pods, Deployments, and Services, learners will master Kubernetes not just as a "concept," but as a "usable skill."

You will learn about the overall DevOps process, including domain purchasing, deploying Spring Boot production servers using EKS, Docker basics, Kubernetes basics, AWS basics, CI/CD automation via GitHub Actions, ArgoCD, and Prometheus/Grafana.

Copilot used by working developers in the industry! From Copilot tips to unit testing and API integration testing, do it all with Vibe Coding! Leap forward as a 10x faster director with real-world industry know-how.

Learn the SAGA transaction management technique for maintaining data consistency in distributed environments through a hands-on approach. You will configure three microservices using Spring Boot and Docker, and implement both Orchestration and Choreography patterns using Kafka and MySQL. Through this course, you will master core concepts applicable to real-world scenarios, including the operational principles of distributed transactions, designing compensating transactions, and handling fault recovery.

If you are a student or developer who is using or studying the Java programming language, you will learn various methods of testing your applications that you must know.

We will teach you how to obtain certified Kubernetes certifications such as Certified Kubernetes Administrator (CKA), Kubernetes Certified Application Developer (CKAD), and Certified Kubernetes Security Specialist (CKS).

This course is a practical-focused learning program for JWT-based token authentication and security enhancement techniques that are essential in modern web service environments. Using Spring Boot 3, Spring Security 6, and React, you'll implement secure login systems and cover comprehensive security practices including XSS·CSRF countermeasures, HTTPS implementation, token reissuance and revocation strategies, and secure secret key management. Additionally, you'll practice real service-level environment configuration through AWS build·deployment and performance optimization using Redis, and the complete project source code provided in the course can be directly applied to real-world work.

Through this lecture, you can learn about the characteristics and background of the Kotlin language, grammar and operation principles, usage examples, and things to be careful of when using Java and Kotlin together.

Experience the power of Type Safe SQL with jOOQ!

Channel Talk interviewers will directly analyze the difference between failing and passing answers to the same question and help you prepare for actual follow-up questions.

An AI system that grades and reviews your code in just 5 seconds—imagination becomes reality. This course is an all-in-one project curriculum for creating a **'GitHub PR Auto-Analysis and Grading Bot'** using Spring AI. When a student submits an assignment (Pull Request), the server detects it, and the AI analyzes the code changes (Diff). The grading results are then stored in a database, feedback is automatically posted as a GitHub comment, and the student can check their results on a dedicated dashboard. From backend to AI integration and frontend (Vaadin), all with just Java! This is the ultimate introductory guide for any developer who wants to build their own AI service from A to Z.

This course was created based on my personal experience passing the very first revised Information Processing Engineer practical exam, which had a pass rate of only 5.34%. The Information Processing Engineer practical exam can no longer be prepared for through simple memorization alone. In particular, the ability to read the execution flow of C, Java, Python, and SQL code to track results, as well as the ability to accurately distinguish short-answer concepts and write them as answers, has become crucial. This course is structured to help even beginners who are new to programming follow along step-by-step, covering everything from creating variable tables to tracking C, Java, Python, and SQL code, core practical terminology, and written exam subjects 1 through 5. Rather than being a video-centered course, this is a text-based course designed for fast reading and repeated review. It makes it easy to look up necessary parts again and focuses on practicing how to derive answers at the testing center by following the code and explanations directly. The 1st update covers the practical programming sections: C, Java, Python, and SQL. The 2nd update will organize core terms and concepts required for the short-answer practical questions and provide a "Stepper Simulator" to practice code tracking directly. The 3rd update will sequentially expand to cover written exam subjects 1 through 5. The Stepper Simulator is designed so that you don't just stop at reading explanations; you can understand how variable values change as the code executes line by line by following along yourself. If you have any questions while taking the course, please leave them in the Q&A. I will respond as quickly as possible to ensure your learning doesn't get stuck.

Real-time data processing is now essential, not optional! Learn to handle real-time streaming smartly with Apache Flink. Batch? Streaming? Even complex concepts can be understood easily and quickly. Hands-on practice configuration where you'll get the hang of it by directly working with Kafka and DB integration! In a world driven by data, start first with Flink.

This is a Redis course created with a current Kakao interviewer. It covers everything from data structure practice (String to Sorted Set) to Sentinel and Cluster configurations, helping you build design rationales that work in both interviews and real-world practice.