Requirements#

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

The following are the common requirements for running the getting started tutorials.

A single-node NVIDIA GPU cluster on a Linux host with cluster-admin permissions.
A least 300 GB of free disk space.
Two NVIDIA GPUs, B200 80B, A100 80 GB, or H100 80 GB, and no other workloads running on them:
- One GPU for machine learning model fine-tuning.
- One GPU for a meta/llama-3.1-8b-instruct NIM microservice for inference.

Software Requirements

Choose one of the following options to set up a demo cluster with the NeMo microservices platform.

Minikube

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

Minikube version 1.33 or later.
Docker 27 or later.
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"
```

The minikube cluster setup 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.

Kubernetes

Kubernetes cluster.
Docker 27 or later.
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"
```