Distributed Environment essentials you must know, as told by a Kakao interviewer

The limitations of LLMs? I’ll share practical solutions to real-world problems based on RAG trial and error and operational know-how from working in Silicon Valley.

You know about AI agent frameworks, but understanding how they work and applying them in practice can be difficult, right? Drawing on firsthand experience from Silicon Valley, we’ll guide you from the core principles to practical applications.

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 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.

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.

Build a scalable real-time event streaming order processing system using Spring Boot 3.x + Kotlin, establishing a Kafka cluster, and leveraging PostgreSQL CDC, Debezium Connect, and Apache Avro schemas.

Kotlin mastery via virtual payment server course.

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.

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.

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.

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.

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 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.

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.

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 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.

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.

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.

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.

Learn the process of converting an existing legacy monolithic system to a microservice architecture through hands-on training. You will also receive code reviews from knowledge sharers up to two times!

Through the 25 patterns of OODP, you will learn various ways to design software in an object-oriented manner.

In this lecture, you will learn how to use OpenTracing to perform distributed tracing across various applications.

Along with reading, writing, and arithmetic, computational thinking is an essential skill that everyone living in the AI era must possess. Simply put, computational thinking can be defined as thinking like a programmer or a computer scientist. This course replicates an actual one-semester university lecture and covers essential content for those new to programming or beginners planning to major in computer science. Additionally, through this course, non-computer science majors or those with a humanities background can develop the ability to communicate easily with professional programmers. Even in an era where learning prompts for "AI vibe coding" is necessary, computational thinking allows you to develop the ability to instruct AI more accurately and effectively.

This is a course where you can learn UML and object-oriented design even without programming experience. Concepts are explained through everyday examples (cafes, libraries, shopping malls), and you'll learn 9 types of UML diagrams step by step. You'll develop design skills that can be immediately applied in practice using theory and PlantUML.

In the software system design course taught by Silicon Valley engineers, you will learn the design principles and architectural patterns of large-scale systems and how to build stable and scalable software solutions. In addition, you will cover performance optimization and fault response strategies through practical cases.

I have created a 'Kubernetes Introduction/Practice' course that is easy for non-majors to understand and can be applied immediately in the field!

Along with reading, writing, and arithmetic, computational thinking is an essential skill that everyone living in the AI era must possess. Simply put, computational thinking can be defined as thinking like a programmer or a computer scientist. This course replicates an actual full-semester university lecture and covers essential content for those new to programming or beginners planning to major in computer science. Furthermore, through this course, non-computer science majors or those with a background in the humanities can develop the ability to communicate easily with professional programmers. Even in an age where learning prompts for "AI vibe coding" is necessary, computational thinking will help you develop the ability to instruct AI more accurately and effectively.

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.

Preparing for a coding interview? You've come to the right place! We've put together a session to dive deep into those JavaScript concepts that are usually hard to understand or remain confusing no matter how many times you hear them :) Are you ready to capture the interviewer's heart?

This is a full-stack restaurant map tutorial that allows you to learn everything from front-end, back-end, Kakao Map API usage, and deployment all at once while creating a restaurant map of your favorite YouTuber.

Through this course, you can acquire the concepts and practices of Information Strategic Planning.

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.

In many programming languages, including Javascript, asynchronous operations are one of the most difficult and complex elements of software. You can discard primitive asynchronous programming such as setTimeout and setInterval and easily handle complex asynchronous operations through RxJS.

This course is a series of courses on functional programming and JavaScript ES6+, covering a variety of application cases.

You can learn design patterns to implement flexible and scalable object-oriented programming. Learn various patterns that can be used in the real world and apply them to your projects and code refactoring.