Become an AI Infrastructure Engineer with real Kubernetes and real GPUs
Run GPU clusters that don't melt down. Kubernetes, GPU Operator, MIG, MPS, observability.
About this path
AI Infrastructure Engineers run the GPU clusters that everyone else's models depend on. The role lives at the intersection of Kubernetes platform engineering and GPU-specific operations, and almost no online course teaches it through real clusters. This path does. Every module is a lab on a live, isolated Kubernetes environment with real GPU scheduling, real GPU operator components, and real triage scenarios that break the way they break in production.
Skills you'll put on a resume
- Schedule GPU workloads on Kubernetes with the right resource requests, limits, and priority classes
- Install and triage the NVIDIA GPU Operator end-to-end, attributing every component's role
- Share single GPUs across workloads with CUDA streams, MPS, and MIG, and know when each fits
- Implement the four-stage cost-audit pipeline (measure → classify → price → recommend) for GPU fleets
- Profile PyTorch training with Nsight Systems and the built-in profiler to find real bottlenecks
- Pass the NVIDIA-Certified Associate AI Infrastructure & Operations exam
For
Platform engineers, SREs, and DevOps engineers responsible for running GPU workloads in production. Comfortable with Linux and Kubernetes basics; new to GPU-specific operations.
Prerequisites
- Comfortable with Linux command line and basic shell scripting
- Kubernetes basics (Pods, Deployments, Services), equivalent of CKA prep
- Familiarity with containers (Docker / containerd)
Guides & articles
Deep-dive reading that pairs with this course
NCA-AIIO Complete Guide 2026 — NVIDIA AI Infrastructure & Operations
Master the NVIDIA Certified Associate - AI Infrastructure and Operations (NCA-AIIO) certification. Exam domains, study plan, career impact, and preparation strategies for data center and IT infrastructure professionals.
ReadNCA-AIIO Exam Domains: Complete Breakdown of All 3 Domains (2026)
Every NCA-AIIO exam domain explained topic by topic: Essential AI Knowledge (38%), AI Infrastructure (40%), and AI Operations (22%), with the DGX, NVLink, InfiniBand, DCGM, and MIG concepts NVIDIA tests.
ReadHow to Pass NCA-AIIO on Your First Attempt (2026 Strategy)
A first-attempt strategy for the NVIDIA NCA-AIIO AI Infrastructure & Operations exam: where candidates lose points, how to prep for a fast 50-question associate exam, and the final-week protocol.
ReadNCA-AIIO Study Plan: 4-Week Preparation Schedule (2026)
A complete 4-week study schedule for the NVIDIA NCA-AIIO AI Infrastructure & Operations exam: weekly goals across all three domains, hands-on GPU labs, and a practice-exam cadence that peaks on exam day.
ReadNVIDIA NCA-AIIO Cheat Sheet 2026: Key Concepts & Decision Rules
Fast-review reference for the NVIDIA NCA-AIIO exam: the software stack, NVLink vs InfiniBand, DGX vs HGX, training vs inference, DCGM and MIG, and the facts a 50-question associate exam tests.
ReadNCP-AII Complete Guide 2026: NVIDIA AI Infrastructure Certification
Master the NVIDIA Certified Professional - AI Infrastructure (NCP-AII) certification. Exam domains, DGX bring-up and cluster validation skills, salary data, and a preparation path for data center engineers building GPU clusters.
ReadHow to Pass NCP-AII on Your First Attempt (2026 Strategy)
A first-attempt strategy for the NVIDIA NCP-AII AI Infrastructure exam: where candidates lose points across bring-up and validation, how to prepare without DGX hardware, and how to run the final week.
ReadNCP-AII Exam Domains: Complete Breakdown of All 5 Domains (2026)
Every NCP-AII exam domain explained topic by topic: cluster test and verification with HPL and NCCL, DGX bring-up sequencing, Base Command Manager control plane, Xid troubleshooting, and MIG/DPU physical layer management.
ReadNCP-AII Study Plan: 6-Week Preparation Schedule (2026)
A complete 6-week study schedule for the NVIDIA NCP-AII AI Infrastructure exam: weekly goals across bring-up, validation, and control plane, hands-on GPU lab work, and a practice-exam cadence that peaks on exam day.
ReadNVIDIA NCP-AII Cheat Sheet 2026: Key Concepts & Commands
Fast-review reference for the NVIDIA NCP-AII exam: deployment sequence, validation toolchain, Xid error table, DCGM diagnostic levels, MIG vs vGPU comparison, and the BCM control-plane map.
ReadNCP-AIO Complete Guide 2026: NVIDIA AI Operations Certification
Master the NVIDIA Certified Professional - AI Operations (NCP-AIO/NCP-AIOL) certification. New lab-based exam format, all four domains, Slurm and Kubernetes operations skills, salary data, and a preparation path for GPU cluster operators.
ReadHow to Pass NCP-AIO on Your First Attempt (2026 Strategy)
A first-attempt strategy for the lab-based NVIDIA NCP-AIO exam: time budgeting across 30 questions and 3 live labs, the terminal fluency bar, where candidates lose points, and the final-week protocol.
ReadNCP-AIO Exam Domains: Complete Breakdown of All 4 Domains (2026)
Every NCP-AIO exam domain explained topic by topic: BCM and Mission Control installation, Slurm and Run:ai administration, training and Triton/NIM inference workloads, and the GPU troubleshooting decision tree.
ReadNCP-AIO Study Plan: 6-Week Preparation Schedule (2026)
A complete 6-week study schedule for the lab-based NVIDIA NCP-AIO exam: weekly goals across installation, administration, workloads, and troubleshooting, daily hands-on GPU reps, and a practice cadence that peaks on exam day.
ReadNVIDIA NCP-AIO Cheat Sheet 2026: Key Concepts & Commands
Fast-review reference for the lab-based NVIDIA NCP-AIO exam: Slurm admin command table, Run:ai quota model, Triton serving features, the five-layer troubleshooting tree, Xid/ECC quick table, and MIG geometry rules.
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