About Me
Overview of backend, platform, and DevOps experience, plus the technical areas I am focused on now.
Me
Author
Backend, Platform & DevOps Engineer
I've spent most of my career building backends and platform infrastructure with Python and Node.js. My work has ranged from public-sector B2G/B2B SaaS platforms to real-time high-availability notification systems and multi-cloud SRE monitoring — all across Azure, Naver Cloud Platform (NCP), and on-premise hybrid environments. I designed and operated these systems myself, and I got good at keeping them running.
Early on, shipping features was the whole job. At some point, though, the question shifted: "How fast does this system come back when something breaks?" That question stuck with me. Since then, I've been obsessed with HA architecture, observability, and building solid incident response workflows.
I've built CI/CD pipelines on NCP DevTools (Source Commit/Build/Deploy) and GitHub Actions, operated real-time anomaly detection with Prometheus, Grafana, and Alertmanager, and put together search (OpenSearch), caching (Redis), async processing (Celery), and ETL pipelines. The through-line has always been the same: availability and performance, at the same time.
When we migrated a public SaaS product to NCP-based microservices, I handled the CSAP, K-PaaS, and national security certifications directly. That meant addressing security requirements at the architecture level, not just checking boxes. On the performance side, I improved our notification pipeline to cut the error rate by 75% while scaling the system to handle 5x the load. Standardizing our monitoring brought MTTR down by 30%.
More recently, I've been expanding from my backend and infrastructure roots into data engineering pipelines, AI/LLMOps, and Infrastructure as Code.
What I'm focused on right now
I'm deepening the skills I already use in production while systematically learning new areas.
DevOps & GitOps
Data engineering
Backend (going deeper)
Infrastructure & databases
Observability
Frontend (expanding toward full-stack)
AI / ML & LLMOps
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Experiences
Career timeline focused on platform engineering, reliability, and AI development.
Skills
Technical stack grouped by infrastructure, backend, observability, and modern web/AI.
Project 1
This repository manages various open-source services required for home server operations by containerizing them. It is designed to allow anyone from beginners to experts to easily build a personal cloud environment, featuring volume mount settings for data persistence, network isolation for inter-service communication, and security management via environment variables.
Project 2
This repository contains declarative configurations for running various microservices required for home server operations within a Kubernetes environment. It features systematic service isolation by Namespace, data management via Persistent Volumes (PV), and Ingress setups for external access, designed to apply modern infrastructure operation methodologies to a home server context.
Project 3
This repository is a Blueprint designed to maximize project productivity. It includes a standardized directory structure, configuration files for maintaining Code Conventions, and automated workflows. This allows developers to reduce time spent on infrastructure setup and focus on implementing core Business Logic.