From Kubernetes to Microservices, CI/CD, and Service Mesh in Three Hours

This course is a comprehensive program that covers everything you need to know to utilize generative AI in practical work settings, from the basic principles of LLM (Large Language Models) to RAG (Retrieval-Augmented Generation), and even the latest technologies like AI Agent and MCP (Modular Command Protocol). It is structured to naturally teach you how generative AI understands, searches, judges information, and extends into AI Agents that take action, following the flow of technological development.

We will summarize the core theories spanning from Machine Learning and Deep Learning to Generative AI in one go. And by implementing various Generative AI applications with easy Python code, you can take your first step as an AI developer.

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

Introducing a DevOps course based on hands-on case studies experienced directly on the front lines of Silicon Valley. This course goes beyond mere theory and covers CI/CD-related tools in a K8S environment that can be applied immediately in real-world engineering fields.

Through this course, you can systematically learn core concepts such as an overview of Docker Events, practical use case 1: monitoring and alerts, practical use case 2: CI/CD pipeline automation, practical use case 3: security and auditing, and Docker Events filtering.

This course is Part 3 of the Full Stack lecture series, designed to help you solidly master the latest server technologies and Docker. The course is structured to enable you to practically incorporate Docker into your tech stack by meticulously testing Docker's various options, learning related technologies such as Linux that are necessary for understanding Docker, and building actual complex services.

Learn from the beginning how to set up a development environment that even an ordinary office worker can easily understand. It is practice-oriented and focuses on students learning various development tools such as Vim, VS Code, Git, Docker, and remote development. You can learn how to build an efficient development environment by learning step-by-step from the basic usage of each development tool to advanced functions.

Learn about Race Condition, a representative concurrency problem. Practice by comparing single server environments and distributed environments that cause concurrency issues. Understand transaction boundaries and isolation levels. Learn the differences between optimistic locking, pessimistic locking, and distributed locking.

This is a DevOps course based on practical experience in Silicon Valley. It goes beyond theory to cover content that can be applied immediately in the field. You will learn how to develop using Generative AI (Vibe Coding), set up CI/CD tools in a Kubernetes environment, and implement strategies to keep operating costs at $0. We will cover configuring a production environment without additional costs by running DB, Redis, S3, and batch jobs inside Kubernetes, and you will master building automated pipelines using GitHub Webhooks and Jenkins through hands-on projects.

Learn the process of building data pipelines using Apache Airflow from basics to practical application. Understand Airflow's core concepts and architecture, and master advanced design patterns frequently used in practice such as dynamic DAGs, parallel processing, distributed processing, and Custom Operators through hands-on exercises. Set up a practice environment with Python and Docker, and develop practical skills to design and operate real workflows.

Instead of long and boring theories, you can learn them one by one through short practical exercises, and as you flesh them out one by one, you will soon be able to experience the overall architecture composition.

Packed with LLM Fine-Tuning Know-how, learned from Silicon Valley LLM Project Practitioners.

I want to launch a side project as a real service and study Kubernetes, but managed services from AWS/GCP (EKS, GKE, etc.) are too expensive. On the other hand, running it only on a local computer makes it difficult to experience network configurations or actual deployment environments. We will utilize the "Always Free" tier of Oracle Cloud (OCI), which offers the most powerful free benefits among existing public clouds. By installing the lightweight yet powerful k3s, we will build a Linux server and Kubernetes environment capable of hosting actual services from scratch—all at zero cost. After taking this course, you will gain a general understanding of cloud networking and possess your own Kubernetes cluster infrastructure where you can deploy and operate your applications for free.

A solo IT startup founder and solo entrepreneur's experience distilled into an honest, straightforward, intuitive, and deep React + Spring Boot course (Docker, AWS, GitHub Actions) I just unified everything into this one course.

Let's implement a web service modeled after Pinterest's unique card-type layout design using Django, Python's representative web framework.

Learn the basic, essential, and practical knowledge of Kafka that software developers need to know. We will integrate Kafka using Spring Boot and conduct hands-on exercises for sending and receiving messages tailored to various real-world scenarios.

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.

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.

What is DevSecOps? Configure a CI build environment and an environment that automatically performs SAST checks during build

This is a 'Practical Linux Troubleshooting Course' where you analyze and solve problems together with generative AI, based on a Docker practice environment that reproduces 5 representative failures that occur in actual Linux operating environments. Even those who were overwhelmed about where to start examining problems can learn the problem-solving approach and thought process of field engineers through AI guidance.

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)

⚓ Kubernetes CKA Certification! 🙇‍♀️Are you still hesitating? 🚢Board the Ilpro-ho! We will guide you through the optimal route.