Introduction to SUSE AI|SUSE AI architecture
Applies to SUSE AI 1.0

3 SUSE AI architecture

SUSE AI building blocks
Linux operating system

The underlying operating system with the optional NVIDIA driver installed. We prefer SUSE Linux Enterprise Server (https://documentation.suse.com/sles). If you require an immutable operating system, SLE Micro is the recommended alternative.

Kubernetes cluster

Kubernetes cluster managed by SUSE Rancher Prime ensuring container and application lifecycle management. We recommend using the SUSE Rancher Prime: RKE2 (https://documentation.suse.com/cloudnative/rke2/) distribution.

NVIDIA GPU Operator

Utilizes the NVIDIA GPU computing power and capabilities for processing AI-related tasks.

SUSE Security (https://www.suse.com/solutions/security/)

For security and compliance.

SUSE Observability (https://www.suse.com/solutions/observability/)

Provides advanced performance and data monitoring.

SUSE Storage (https://www.suse.com/products/rancher/storage/)

Enterprise-grade storage solution.

SUSE Virtualization (https://www.suse.com/products/rancher/virtualization/)

For virtualized workloads.

SUSE Multi-Linux Manager (https://www.suse.com/products/multi-linux-manager/)

For managing multiple Linux distributions.

SUSE Application Collection (https://www.suse.com/products/rancher/application-collection)

As a source of Helm charts and container images for the AI Library applications.

AI Library applications. Following is a list of AI applications that you can find in the SUSE Application Collection. For a complete and up-to-date list, refer to https://apps.rancher.io/stacks/suse-ai.

cert-manager (https://cert-manager.io/)

An extensible X.509 certificate controller for Kubernetes workloads.

OpenSearch (https://opensearch.org/)

A search and analytics suite for analyzing and visualizing search data.

Milvus (https://milvus.io)

A vector database built for generative AI applications with minimal performance loss.

Ollama (https://ollama.com)

A platform that simplifies the installation and management of large language models (LLM) on local devices.

Open WebUI (https://openwebui.com)

An extensible Web user interface for the Ollama LLM runner.

vLLM (https://github.com/vllm-project/vllm

A high-performance inference and serving engine for large language models (LLMs).

mcpo (https://github.com/open-webui/mcpo)

The MCP-to-OpenAPI proxy server provided by Open WebUI.

PyTorch (https://pytorch.org/)

An open source machine learning framework.

MLflow (https://mlflow.org)

An open source platform to manage the machine learning lifecycle, including experimentation, reproducibility, deployment and a central model registry.

An image showing a basic structure of SUSE AI
Figure 3.1: Basic schema of SUSE AI