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

If you’ve found it difficult to explain what’s happening under the hood while using AI and embeddings, this course may be the answer. Drawing on the experience of a practicing AI developer in Silicon Valley, it helps you understand the principles of AI through code by implementing everything from embeddings and Word2Vec to automatic differentiation and transformers yourself.

If you’ve ever had trouble determining whether the quality of responses declined after changing a prompt or model while building a service using an LLM, this course may be the solution. You’ll learn how to create your own evaluation criteria and automatically identify responses that have changed.

When Redis alone can no longer guarantee performance, what options do we have?? There is Valkey, which is 100% compatible with Redis and applies IO-based tuning. Through this course, let’s explore how Valkey guarantees 1M++ TPS and learn about the data structures suited to different traffic patterns and feature implementations.

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.

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.

A Redis course created with a current Kakao interviewer. From hands-on practice with data structures ranging from String to Sorted Set to Sentinel and cluster configuration, you’ll build design rationale that holds up in interviews and real-world work.

This course goes beyond basic CRUD-level database usage, helping you develop the PostgreSQL skills needed in the AI era from a practical, real-world perspective. Drawing on AI development experience in Silicon Valley, you’ll gradually learn how to design and use JSON, indexes, transactions, and pgvector in actual services, while gaining the skills to solve complex data structure and performance problems.

It was created to solve the problem of “not knowing where or how to start with Kubernetes.” Based on hands-on experience gained from operating financial infrastructure, it is structured to help learners understand Kubernetes by following the actual process of building and operating it, rather than focusing on theory alone. Through a learning progression covering its relationship with Docker, YAML, Pods, Deployments, and Services, learners will internalize Kubernetes not as a “concept,” but as a “usable technology.”

This course goes beyond teaching Docker as merely a set of tools and approaches it from the perspective of solving the concerns and problems you will actually encounter in the field. It explains, based on firsthand experience operating financial infrastructure in the industry, everything from unpredictable errors caused by differences between development and production environments, and configuration mistakes stemming from vague concepts of images and containers, to the anxiety of wondering, “How much do I need to know for this to be useful in practice?” Rather than simply listing commands, the course focuses on real-world examples to explain why this structure is necessary, how to design images for easier maintenance, and how to manage containers to operate services reliably. In particular, it places greater emphasis on hands-on practice than theory, with the goal of helping students understand Docker visually and master it through practice—not merely reaching the level of “knowing how to use Docker,” but understanding it from an operational perspective. This course provides practical standards and direction for those encountering Docker for the first time, those who have used it but have not yet organized their understanding of the concepts, and developers who want to take their infrastructure skills to the next level.

Learn how to build data pipelines with Apache Airflow, from the basics to real-world applications. Understand Airflow’s core concepts and architecture, and practice advanced design patterns frequently used in the field, including dynamic DAGs, parallel processing, distributed processing, and Custom Operators. Set up a hands-on environment with Python and Docker, design and operate real-world workflows, and develop practical skills for production use.

How can you withstand skyrocketing traffic? Learn how to build a resilient and flexibly scalable architecture through practical design patterns based on EDA (Event-Driven Architecture) using Kafka, Spring, CDC, and Temporal. Explained clearly and simply—even for non-majors—alongside the real-world experience of a Kakao developer. A hands-on course covering everything from real-time data flows and event processing to microservice integration!

Kotlin mastery via virtual payment server course.

Learn how to design and process large-scale data architectures capable of handling hundreds of billions of records, using only pure SQL and MySQL’s core features, alongside a Toss developer who handles hundreds of billions of financial transactions and a developer who started without a computer science background and now works on platform development in Pangyo.

As you work in backend development, you eventually find yourself facing a certain concern. As services multiply and traffic increases, there comes a point when simple REST communication and a CRUD-only structure begin to show their limitations. I experienced the same problem in practice and went through many trials and errors trying to balance performance with structural complexity. The solution I chose in that process was NATS. Its simple, single-binary-based setup, ultra-low-latency performance measured in microseconds, and practical feature set—from Pub/Sub and Queue Groups to JetStream—made it a highly realistic choice for actual service environments. This course is not about listing NATS’s features. Based on the problems I encountered in practice, it explains through code and workflows when and why I chose NATS and how I designed the architecture. From those new to messaging systems, to backend developers preparing for employment, and senior developers considering better architectures, this course will help everyone understand distributed systems and grow to the next level.

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.

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

This course is a master class that teaches Kotlin's 🌺 Coroutine, covering everything from theoretical foundations to practical application in a standard manner. It systematically covers core principles and structure, the necessity of asynchronous programming, Coroutine builders and scopes, exception handling, channels, Flow, and other key features frequently used in practice, step by step. Each concept is explained with hands-on examples, making it easy for beginners to understand and immediately apply them. This is the best introductory and practical course for developers who want to build strong Coroutine skills for real-world use.

This course explores microservice architecture and distributed environments not as a simple list of technologies, but from the “design perspective” required in real-world practice and technical interviews. Starting with the differences between monolithic architectures and MSA, it systematically covers gradual migration strategies, modular monoliths, clean architecture, and hexagonal architecture, clearly explaining why each choice is necessary and the trade-offs that come with it. Through hands-on exercises, you can directly verify the intentions behind each structure and learn about the core challenges inevitably encountered in distributed environments—such as data consistency, transactions, inter-service communication, and failure handling—through realistic scenarios. Based on actual questions and perspectives from Kakao interviewers, this course aims to do more than impart knowledge: it seeks to elevate your way of thinking about distributed systems to the next level.

This course covers RPC communication techniques for maximizing performance in large-scale MSA (Microservice Architecture) environments. Going beyond simple gRPC practice, you will learn how to implement stable and efficient service-to-service communication in real-world production environments where hundreds of microservices operate simultaneously. Based on Golang, the course takes a practical, hands-on approach to writing Protocol Buffers (proto) syntax, generating code automatically and implementing services, understanding gRPC’s architecture and advantages over traditional RPC, and applying performance optimization strategies. To ensure that even non-majors and beginners in server development can easily follow along, it explains everything step by step—from the concept of RPC to gRPC’s internal operating principles—helping you develop practical skills that can be applied directly to real-world services.

Learn the process of building essential observability in a microservices architecture (MSA) environment, from the basics to hands-on practice. Through step-by-step exercises, you will learn standardized data collection using OpenTelemetry, trace storage and search with Grafana Tempo, and visualization using TraceQL. You will also learn how to trace service flows through distributed tracing, identify bottlenecks, and analyze the causes of failures.