Designing Large-Scale Data Processing Patterns Based on Data Workflow Management with Toss Developers

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 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 explores microservice architecture and distributed environments not as a simple list of technologies, but from a 'design perspective' required in actual work and interviews. Starting from the differences between monolithic and MSA, it progressively covers incremental migration strategies, modular monoliths, clean architecture and hexagonal architecture, clearly explaining why each choice is necessary and the trade-offs involved. Through hands-on practice, you can directly verify the intent of the structure and learn about core issues 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 go beyond simple knowledge acquisition and elevate your way of thinking about distributed systems to the next level.

This course covers how to set up multi-module projects from scratch using Kotlin and Spring Boot. It proceeds with a hands-on approach, covering everything from the basic concepts of modularization to Gradle configuration, managing dependencies between modules, and actual application development. If you are a beginner or intermediate developer looking to learn the fundamentals and practical application of multi-modules, please refer to this course.

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.

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.

Kotlin mastery via virtual payment server course.

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.

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 covers RPC communication techniques that maximize performance in large-scale MSA (Microservice Architecture) environments. Going beyond simple gRPC practice, you'll learn how to implement stable and efficient inter-service communication in real production environments where hundreds of microservices operate simultaneously. Based on Golang, the course covers Protocol Buffers (proto) syntax writing, automatic code generation and service implementation, gRPC structure and advantages over existing RPC, and performance optimization strategies with a practical focus. To ensure easy understanding for non-majors and server development beginners, the course provides step-by-step explanations from RPC concepts to gRPC's internal operating principles, enabling you to develop practical skills that can be immediately applied to real services.

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

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.

Develop a scalable real-time WebSocket chat server capable of handling high traffic by building a 3-instance cluster with Spring Boot 3.x and Kotlin, utilizing Redis Pub/Sub for distributed messaging and Nginx as a load balancer.

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.

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.

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.

How will you handle exploding traffic? Learn how to build resilient and flexibly scalable architectures through practical EDA (Event-Driven Architecture) design patterns using Kafka, Spring, CDC, and Temporal. A Kakao developer shares real-world experience with clear, easy-to-follow explanations that even non-majors can understand. A practice-oriented course covering everything from real-time data flow and event processing to microservice integration!

Learn how to design and handle large-scale data architectures that process hundreds of billions of records using only pure SQL and core MySQL features, alongside a Toss developer who handles hundreds of billions of financial traffic transactions and a developer who started as a non-major and is now developing platforms in Pangyo.

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.

This course is a master class that systematically covers the fundamental principles and practical applications of MongoDB. Starting with core MongoDB concepts, you will systematically learn essential topics for practical work, such as database design, CRUD operations, indexing, aggregation pipelines, performance optimization, transactions, and security. It explains topics step-by-step so even beginners can understand, and you can deeply learn the working principles of MongoDB through exercises and examples. This is the best introductory and practical course for developers who want to build strong MongoDB skills for practical work.

Uncover true value in the age of data! 📊 Designing applications focused on data has now become essential. Develop the insight and skills your company wants with the latest trends and practical case studies. Start now with efficient data processing and design secrets! Your next step, leap into the data-driven world!

This is a code-lab-oriented course where you will directly build big data or distributed processing system clusters (HDFS, Zookeeper, Spark, Zeppelin) that guarantee High Availability.

How is processing big data different from processing data with Pandas? Let's learn about Spark, an essential framework for big data processing.

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.

With the advent of the AI era, building data pipelines has become a core competency that determines a company's competitiveness. Learn how to build efficient data pipelines using Airflow, the most widely used tool, directly from a Silicon Valley expert (formerly Head of the Data Team at Udemy, currently a professor in the Data Masters program at San Jose State University) with practical experience and extensive lecturing experience.

Redis is a fast and scalable open-source database. This technology is used to maximize performance in real-time applications, games, social media platforms, and more. However, to truly understand the power of Redis and use it effectively, you need a deep understanding. Now is your chance to learn Redis in a professional way. "Redis with Silicon Valley Engineers" covers a wide range of topics, from the core concepts of Redis to advanced features. This course is designed for everyone, from beginners who are new to Redis to advanced users.

If you work with data, SQL is a fundamental skill you must know. In this course, we will learn SQL from a data analysis perspective, focusing on hands-on practice. The practice will be conducted in Google Colab using DuckDB.

Build a local LLM with RAG-based Q&A system in just 2 hours of practice using Docker + ollama + R2R framework. (Applicable for internal/in-house Q&A systems, personal portfolios, AI-enhanced work productivity, and even commercial services)

Regardless of the field! This is a lecture that covers the core fundamentals that developers must know in practice in an easy + code-oriented way. I highly recommend this lecture to all junior developers and job seekers who want to grow.

It covers basic data concepts, useful R functions and packages, and data analysis exercises, to allow anyone to perform big data analysis using R programming.

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.

I have created an introductory and practical Docker course that is easy for non-majors to understand and can be applied immediately in the real world!

This is a special lecture that can lay the theoretical foundation to simultaneously prepare for the Microsoft AZ-900 certification, and as the latest content reflecting the scope of questions as of May 2025, by providing content related to core data concepts, Azure's relational data, Azure's non-relational data, and Azure's analytical workloads in a form combining theory and practice, it can be utilized as a meaningful educational opportunity to not only obtain the certification but also take the first step towards becoming a data professional.

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.

I have created an introductory CI/CD course that is easy to understand even for non-majors and can be applied immediately in practice!

Through this lecture, you can systematically learn core concepts such as the types and characteristics of volumes, commands for creating and managing volumes, methods for connecting containers and volumes, strategies for ensuring data persistence, and precautions when using volumes.

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.

We introduce methods for planners and marketers without data analysis experience or technical skills to try data analysis at the most basic level, complete with various examples. Built on years of hands-on practice with over 2,000 participants in more than 100 companies and public institutions, the content is designed around the most practical analysis methods for data non-experts.

This course takes you from the fundamentals to advanced, real-world container workflows using Docker and Kubernetes. You will start by learning containers from the ground up, understanding how Docker works and why it is widely used in modern DevOps environments. You’ll run Docker, Docker Compose, and Kubernetes locally to improve software development, testing, and deployment workflows.

SSIS, SSAS, MachineLearning, BI, ETL. You can learn important technologies that cannot be found in domestic books, YouTube, lectures, blogs, and academies. I also recommend it to those who are interested in employment at domestic large companies, American large companies, and American state funding agencies.