Terraform Deployment Guide

A portfolio-focused course on deploying a React frontend and Spring Boot backend directly to the AWS cloud! This course is helpful for those who want to quickly deploy frontend and backend projects for their portfolio. You will gain the necessary knowledge for deployment through short-term, step-by-step practice, covering everything from server configuration to Docker, domain connection, Nginx, and HTTPS application!

This covers the process of creating AWS resources based on AWS InfraArchitecture using Terraform modules.

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

"Enter the world of Cloud Infrastructure Automation!" Terraform, an infrastructure automation tool, is used to provision and manage resources in a cloud environment. Now, you too can define and automate your cloud infrastructure as code to quickly and consistently configure an infrastructure environment!

This course is designed for developers, DevOps engineers, cloud engineers, and IT professionals who want to master advanced Kubernetes concepts used in real-world production environments. Throughout the course, students will engage in hands-on projects and real-world deployment scenarios, learning how to build secure, scalable, and production-ready Kubernetes infrastructure. Rather than focusing solely on theory, this course emphasizes practical implementation, troubleshooting, and best practices utilized by modern DevOps teams. One of the biggest challenges students face when learning Kubernetes is understanding how all components interact within large-scale environments. Many learners struggle with topics such as RBAC permissions, persistent storage, namespaces, network policies, StatefulSets, Kustomize, and secure cloud deployments. This course addresses these issues step-by-step through clear explanations, guided labs, and examples that mirror actual production environments. Students will learn step-by-step how to organize Kubernetes resources, secure workloads, manage application configurations, deploy stateful applications like MongoDB, and automate multi-environment deployments using Kustomize. Additionally, the course covers how to deploy applications to Google Kubernetes Engine (GKE) and configure Ingress, TLS certificates, monitoring, and scaling strategies. By the end of this course, students will have the confidence to design, secure, deploy, and manage advanced Kubernetes environments used in professional DevOps and cloud engineering workflows.

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

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.

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.

Deploy a Spring Boot SNS app to local Kubernetes, and automate deployments with GitHub Actions and Argo CD. Identify the causes of failures through metrics, logs, and traces, and review them based on AI analysis results.

This course is Part 3 of the Full-Stack course series, designed to help you thoroughly master the latest server technologies and Docker. To enable you to genuinely incorporate Docker into your tech stack, the course meticulously tests Docker’s various options, covers related technologies such as Linux that you need to understand for Docker, and is structured so that you can even build complex real-world services.

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.

You can quickly experience the process of deploying a sample e-commerce service to AWS and continuously improving it into a robust and efficient environment.

This course is designed to help you quickly learn server deployment methods using Nginx, Docker, and Spring Boot through hands-on practice. Learn Blue-Green deployment, a frequently used technique in the industry, faster than anyone else!

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.

This is a practical, hands-on course where you will learn the principles of AI Agents—going beyond simple chatbots that just answer questions to systems that can perceive situations, make judgments, and control actual systems. The curriculum is structured to provide a step-by-step understanding, starting from the differences between AI Agents and chatbots to the core Agent Loop structure: Sense-Think-Act, state management, planning, and feedback loops. Moving beyond theory, you will set up Windows and Linux development environments and gain hands-on experience with the basic structure of Kubernetes and kubectl commands. Following this, you will implement a process where an AI Agent detects server issues, analyzes the causes, and automatically resolves errors. Finally, by directly analyzing the Python code and internal logic of the Agent controlling Kubernetes, you will understand how AI Agents connect to and operate within real-world systems. From developers new to AI Agents to those who want to design Multi-Agents that control actual systems, this course allows you to learn both the principles and the practical implementation process of Agents.

With v0, cursor AI, and various LLMs, from PRD to AI product recommendations! Complete your Next.js shopping mall through a practical project.

Learn cloud infrastructure automation technology using AWS and Terraform, and practice efficient infrastructure management and deployment. Manage AWS resources as code through Terraform, and learn how to deploy consistent infrastructure across various environments.

In this course, we will practice step-by-step how to use React and FastAPI to implement social features such as real-time voting, comments, and likes, as well as how to monetize by integrating payment systems (Kakao Pay, Toss Pay, etc.).

You can learn about IAM, the foundation of AWS Zero Trust, from the most basic elements to the most detailed specifics. Through this, you can learn which parts may actually be vulnerable and where you need to pay more attention.