Nguyen Van Tuan AnhFull-stack · DevOps · CloudI build cloud-native platforms and operational automation on AWS and Kubernetes — from application architecture to CI/CD and observability.
Profile & experience
Explore each foundation
01 · Focus
Da Nang, Viet Nam
Focused on full-stack applications, cloud-native platforms, and delivery workflows that are observable, controlled, and scalable. I approach each project end to end, from application architecture to deployment and operations.
02 · Education
2023–2027 · Bachelor of Information Technology
Pursuing a degree in Information Technology at the Vietnam–Korea University of Information and Communication Technology, The University of Da Nang.
03 · Experience
June–September 2025
Developed backend architecture, automated the CI/CD workflow, and deployed the application on AWS EC2.
04 · Cloud & leadership
April–August 2026 · VKU Skills Club 2024–2025
Designed AWS infrastructure and Kubernetes platforms with Terraform, GitHub Actions, Argo CD, observability, and canary deployments. Served as Vice Head of VKU Skills Club from 2024 to 2025.
How I work
A platform earns its keep on the worst day, not the best one. So I build for the worst day: every deploy reversible, every failure visible, every fix leaving a trace someone else can follow.
A system you cannot see is a system you cannot run. Metrics, traces, and logs come first — optimisation comes after the graph proves it is needed.
Infrastructure as code, pinned versions, declarative environments. If it only works on one machine, it does not work yet.
Novelty belongs in the product, not in the deployment path. The pipeline should be the least surprising part of the day.
Writing the service is half the job. Alert routing, runbooks, rollbacks, and the on-call story are the other half.
Focus areas
Track 01 · Cloud platform
Designing and running Kubernetes platforms on AWS: network layout, identity boundaries, autoscaling, and the guardrails that keep a cluster boring.
Working stack
AWSEKSTerraformIAM/IRSAVPCKMSChoose a path
Selected work
Developed and evaluated EfficientNetV2, ConvNeXt, and ResNet50 for authentic/AI image classification at approximately 98.6% F1; combined local inference, Gemini multimodal analysis, Grad-CAM, a Next.js dashboard, and a Chrome Extension.
There's more
Coursework, experiments, and small tools — updated regularly.
Beyond the résumé
Nguyen Van Tuan AnhCloud / DevOps · Full-stackDa Nang, Viet NamMilestones · 2024—2026
Vietnam–Korea University of Information and Communication Technology
Vietnam–Korea University of Information and Communication Technology
Vietnam–Korea University of Information and Communication Technology
National-level award · Grab
xbrain
KOICA CIAT · WFK Korea · Vietnam
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