NVIDIA k8s lab on a gaming laptop — new article
The guide takes you from WSL2 and Docker through Kind (K8s) and the NVIDIA GPU Operator. In the final step, you run a small LLM on the NVIDIA GPU (Ollama with a 3B model) to confirm the full stack works for real AI workloads.
Why I Built This Lab#
If you work in an industry that is moving toward AI workloads, knowing the NVIDIA AI infrastructure stack helps. That is why I decided to study it.
Earlier in my career, I was a Red Hat Certified Instructor (RHCI), a Red Hat Certified Examiner (RHCX), and a Microsoft Certified Trainer (MCT). From that work, I learned one thing: the best way to learn a vendor’s technology is to study for and pass the certification exam.
The Associate exam — NVIDIA-Certified Associate: AI Infrastructure and Operations (NCA-AIIO) — is not a hands-on lab. It is a timed multiple-choice test about how the parts fit together. You can pass it using slides and documentation alone, but…
The Role of This Lab#
This lab is supplemental exam preparation, not a replacement. You still need the official study guide, documentation, and practice questions. What the lab adds is hands-on practice with NVIDIA tools — without access to expensive data-center hardware. An old gaming laptop is enough.