The AARI Systems Lab is not a simulation. It's a production-grade facility where students operate the same enterprise hardware found in Fortune 500 data centers, racking servers, configuring networks, deploying AI models, and maintaining real uptime.
Energy → Silicon → Infrastructure → Models → Applications → Quantum
AI Infrastructure Physics. One arc, one doctrine, every layer taught from the ground up
AARI's enterprise systems curriculum is built on Red Hat's open source ecosystem, the same stack used by the world's largest organizations to run critical infrastructure at scale.
Students don't learn about OpenShift. They deploy on it. They don't read about OpenStack. They configure it. This is the Red Hat difference: real tools, real environments, real skills.
Enterprise Kubernetes platform for container orchestration at scale
Private cloud infrastructure for managing compute, storage, and networking
Red Hat Enterprise Linux, the OS of enterprise infrastructure
Automation and configuration management at enterprise scale
AI doesn't only live in the data center. AARI teaches the full spectrum, from a Raspberry Pi at the edge to a GPU cluster in the cloud.
Edge AI Platform
Students deploy real AI inference at the edge using NVIDIA Jetson devices, the same hardware used in autonomous vehicles, smart cameras, and industrial robotics. This is where AI meets the physical world.
IoT & Embedded Computing
Raspberry Pi teaches students the fundamentals of embedded computing, IoT integration, and low-power systems design. It's the training ground where Linux administration, networking, and hardware interface all meet.
Cloud is a layer on top of metal. AARI students learn the metal first.
Students physically install and cable enterprise servers. No click-to-deploy here. You understand every component before you virtualize anything.
VLANs, switching, routing, and firewall configuration on real equipment. Security is built in from layer one, not bolted on at the end.
SAN, NAS, NVMe, and object storage, understanding how data lives, moves, and persists across enterprise infrastructure at scale.
Most programs teach Models → Applications. We teach Energy → Chips → Infrastructure → Models. Applications are the capstone, not the foundation.
Power systems, UPS, PDUs, PUE efficiency, data center power architecture
CPU, GPU, TPU, FPGA, accelerated compute, hardware architecture, NVIDIA CUDA
Bare metal, virtualization, containers, Kubernetes, OpenShift, networking, security
ML training, fine-tuning, inference optimization, MLOps, model registry and deployment
Real AI products, robotics, automation, the capstone, not the starting point
Quantum computing foundations using NVIDIA CUDA-Q, the frontier of compute where classical and quantum meet
The robot isn't the goal. It's proof the pipeline works. Our students don't just use AI tools. They understand and build every layer of the systems that power them.
Contact us to learn more about the AARI Systems Lab, partnership opportunities, or equipment donations.