About

About This Blog

I’m learning AI infrastructure by building real systems—sharing projects, experiments, and lessons across Linux, Kubernetes, GPU clusters, and HPC environments.

RiverRocket is my personal space where I explore and build AI infrastructure systems—from Linux-based environments to GPU clusters, Kubernetes, and HPC workloads.
I started this journey with a simple goal: to understand how real-world AI systems are designed, deployed, and optimized beyond theory. Instead of only reading or watching tutorials, I focus on building, breaking, and improving actual systems.

What I’m Working On

Right now, I’m focused on developing hands-on experience with:

• Linux system administration and performance tuning.
• Kubernetes for container orchestration.
• GPU-based computing for AI workloads.
• HPC systems and job schedulers like Slurm.
• Infrastructure automation and observability.

Each project I take on is an opportunity to learn something practical—whether it’s setting up a cluster, optimizing performance, or debugging issues that only appear in real environments.