Cloud Native Platform Engineer · Open Source Engineer · Adjunct Professor

I am a Cloud Native Platform Engineer with 20+ years of IT experience, focused on Kubernetes, Platform Engineering, AI/Data Platform, DevOps, and Cloud Native Infrastructure.

I design and build reliable, developer-friendly platforms that reduce operational complexity and enable engineers to focus on delivering products.

My engineering approach emphasizes a continuous loop of problem definition → design → implementation → validation → incident analysis → regression testing → automation → documentation.

I actively apply this approach to open-source projects focused on Kubernetes and Cloud Native infrastructure.

🇰🇷 한국어: README.ko.md

• Kubernetes & Platform Engineering
• Internal Developer Platform (IDP)
• AI & Data Platform
• GPU Infrastructure
• Cloud Native & DevOps
• GitOps & CI/CD
• Infrastructure as Code & Automation
• Observability & Service Mesh
• IAM / SSO
• Storage & Infrastructure Troubleshooting
• AI-assisted Engineering
• Open Source Engineering

Kubernetes Internal Developer Platform (IDP)

HA Kubernetes, GitOps, Keycloak SSO/RBAC, Cilium, Istio Ambient, Observability, Security, IDP Portal, and automated cluster/SSO validation in one platform.

Apple Silicon MLOps Platform

An experimental MLOps environment combining Kubernetes-based ML services with host-side GPU/MLX compute on Apple Silicon.

Local K-PaaS Installation & Development Environment

Automation for installing, learning, and validating K-PaaS in local environments.

Kubernetes NFS Quota Automation

A Go-based project for automating filesystem quota management and integrating quotas with Kubernetes PVs.

Kubernetes-Ready Vagrant Images

Automated Kubernetes node images covering OS tuning, filesystem configuration, and multi-architecture environments.

OSS is not only about writing code. It is about building a system that can be installed, operated, verified, evolved, and trusted.

I believe the value of an open-source project is not measured only by lines of code or commit counts.

It is about the complete engineering loop:

• Define the problem clearly
• Make it work in a real environment
• Record failures and incidents
• Analyze root causes
• Turn lessons into regression tests
• Automate repeatable operations
• Document the project so others can use it

I actively use AI-assisted engineering tools such as Claude Code for development, testing, troubleshooting, documentation, and open-source maintenance.

I am particularly interested not simply in AI-generated code, but in how AI can be integrated into the engineering loop while improving both quality and productivity.

• Adjunct Professor at Tech University of Korea — Software Frameworks
• 10+ years of Open Source / Cloud Native community activities
• 30+ technical talks and seminars
• Open Source community leadership

• GitHub: https://github.com/dasomel
• Engineering & OSS: https://cne.io.kr
• LinkedIn: https://www.linkedin.com/in/%EA%B8%B0%ED%95%98-%EC%9D%B4-ba909924
• OSS Engineering Portfolio: https://cne.io.kr/ko/posts/oss-engineering-portfolio-standard/

Cloud Native Platform Engineering · Kubernetes · Platform Engineering · AI Platform · Data Platform · DevOps · Open Source Engineering