Requirements#

The following requirements are specific to setting up the entire NeMo microservices platform on a minikube cluster for running the Beginner Tutorials.

Depending on your environment, what combination of the NeMo microservices you want to deploy, and the scale of your AI workload, you should adjust the requirements accordingly.

System Requirements

A single-node NVIDIA GPU cluster on a Linux host and cluster-admin level permissions.
At least 200 GB of free disk space.
At least two NVIDIA GPUs, A100 80 GB or H100 80 GB, and no other workloads running on them:
- One GPU for machine learning model customization, training, or fine-tuning.
- One GPU for inference.

Software Requirements

minikube
NVIDIA Container Toolkit v1.16.2 or higher. Refer to the Installing the NVIDIA Container Toolkit.
NVIDIA GPU Driver 560.35.03 or higher. Refer to Driver Installation Guide.
Kubernetes CLI, kubectl. Refer to Install and Set Up kubectl on Linux in the Kubernetes documentation.
Helm CLI, helm. Refer to the Helm documentation.
Hugging Face CLI. Refer to the Hugging Face Hub CLI user guide and the Hugging Face Hub installation guide. If you aren’t using a virtual environment or a root user, make sure that you add the $HOME/.local/bin directory to your PATH environment variable.
```
export PATH="$HOME/.local/bin:$PATH"
```

Requirements for the Minikube Cluster

NVIDIA developed and tested this tutorial using minikube and meeting the following prerequisites.

minikube version 1.33 or later.
Docker 27 or later.

This tutorial uses the following minikube features:

minikube ingress.
Standard storage class using host path volumes provided by the default storage provisioner.

The host file system for the host path volumes must support file locking. During customization with NeMo Customizer, NeMo Operator starts an entity handler pod that runs the Hugging Face CLI. The CLI requires a file system, such as EXT4, that supports file locking.