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 modifying Swagger documents, aligning API specs, and communicating back and forth with the frontend, you start to wonder, "Why am I doing the same thing twice?" I felt that same frustration in the field, which led me to dive deep into GraphQL and develop an interest in data-driven design. This course isn't just about simple GraphQL syntax; it covers why it emerged to solve real-world service problems, along with practical considerations like Resolver structures, the N+1 problem, and Federation. I have designed this course to help you naturally learn how to reduce communication costs between developers and design a more flexible API structure.

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."

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 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.

You may have felt frustrated using Redis without being able to explain why it should be designed that way or why certain patterns emerged. Through my experience in both practical development and as an interviewer, I have treated Redis not just as a simple cache, but as a core component that determines service stability and scalability. This course is not about memorizing commands; instead, I will share my experiences on which structures to choose in real traffic environments and their trade-offs, helping you establish the criteria to explain these concepts confidently in both interviews and practical work.

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.

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.

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.