Top 5 Reasons to Choose SUSE for Your Generative AI Projects in 2025

Generative AI is moving fast. Your infrastructure should too

2025 is shaping up to be a pivotal year for generative AI. Organizations across industries are no longer just experimenting—they’re scaling production-grade AI systems to power everything from automated customer interactions to knowledge management, content generation, and decision support.

But with this momentum comes complexity. From managing massive compute requirements and ensuring data privacy, to avoiding vendor lock-in and navigating skills gaps—enterprise teams face a growing set of technical and strategic decisions.

At SUSE, we work with IT and AI leaders across finance, healthcare, manufacturing, and the public sector. What we’ve learned is simple: the infrastructure you choose today will define the flexibility, security, and success of your generative AI journey tomorrow.

Here are five reasons SUSE AI stands out as the platform of choice for GenAI in 2025

1. A Secure and Proven Linux Foundation for AI Workloads

Generative AI workloads are resource-intensive and demand consistency at scale. They also require a secure operating environment that can support everything from training and fine-tuning large language models (LLMs) to deploying inference at the edge.

SUSE Linux Enterprise Server (SLES) is designed to meet these needs. With performance optimizations for GPUs, real-time processing capabilities, and enterprise-grade reliability, it offers a rock-solid foundation trusted by the most security-conscious industries.

Enterprises using SLES benefit from features like FIPS certification, extended lifecycle support, and hardened images—enabling compliance across regulated environments such as healthcare (HIPAA), finance (PCI DSS), and government (FedRAMP-ready).

2. Simplifying Kubernetes for AI with Rancher

Containers and Kubernetes are now standard for AI workloads—but managing them effectively can be a challenge.

Recognized by Forrester and Gartner as a leader, Rancher Prime is a comprehensive, open infrastructure platform designed to drive enterprise cloud-native transformation. It provides the tools needed to manage and secure every application workload with real-time observability and robust security measures across all clusters. This platform allows organizations to deploy, run, and manage containerized workloads across diverse environments, from data centers to hybrid clouds and the edge.

By combining operational simplicity with enterprise-grade security, Rancher Prime ensures that your generative AI stack remains consistent, scalable, and production-ready—no matter where you deploy.

3. Data Privacy by Design: On-Premise and Hybrid Flexibility

For many enterprises, data privacy isn’t optional—it’s essential. Cloud-native AI services are convenient, but they raise real concerns around control, compliance, and sovereignty.

SUSE Security extends this foundation by providing zero-trust container security—enabling continuous scanning throughout the container lifecycle, removing roadblocks, and embedding policies from the start to maximize developer agility. Its integrated, zero-trust security model gives enterprises the confidence to deploy and operate AI applications securely, even when leveraging diverse open-source components.

SUSE also gives you the flexibility to deploy GenAI where it makes the most sense—whether that’s fully on-premise, in a hybrid cloud, or at the edge.

• Keep sensitive data in-house for fine-tuning and inference
• Deploy in air-gapped environments with full network isolation
• Maintain full control over data flows, access policies, and retention

Organizations in regulated industries, or those dealing with proprietary IP, benefit from SUSE’s privacy-first approach—empowering them to innovate with AI without compromising trust.

4. Open Source at the Core—No Vendor Lock-In

One of the biggest risks in fast-moving AI adoption is getting locked into a closed ecosystem that limits innovation down the road.

SUSE offers an open, interoperable foundation that integrates seamlessly with leading AI frameworks and platforms. You have the freedom to:

• Run open-source LLMs (like LLaMA, Mistral, or Falcon)
• Integrate with Hugging Face, LangChain, and ONNX
• Orchestrate workloads across EKS, AKS, OpenShift, and beyond

With SUSE, your architecture remains flexible—and your roadmap stays yours.

5. AI at Scale—From Data Center to Edge

Generative AI is no longer confined to high-performance data centers. From smart factories to branch offices and field operations, enterprises are embedding intelligence directly at the edge.

SUSE enables this with lightweight, scalable components:

• K3s: A production-ready, lightweight Kubernetes distribution perfect for edge inference
• Rancher Fleet: Scalable cluster management across thousands of locations
• SUSE Security: Run-time container security to protect models and workloads from external threats

As generative AI becomes more distributed, SUSE ensures performance, security, and manageability aren’t sacrificed in the process.

Final Thoughts: Building a GenAI Strategy That Lasts

The landscape of generative AI is evolving fast—and that’s not going to change. But the infrastructure decisions you make now will determine whether your AI capabilities grow with your organization or become a constraint.
At SUSE, we believe in enabling organizations to build responsibly, deploy securely, and scale flexibly. We help enterprises architect AI platforms that align with their compliance requirements, data privacy strategies, and innovation goals.

Choosing SUSE means choosing:

• An enterprise-ready Linux platform
• Kubernetes made for operational simplicity
• Full ownership of your data and models
• An open ecosystem that evolves with your needs
• Scalable AI infrastructure from core to edge

Learn more how SUSE can help you operationalize you AI workloads.  Visit https://www.suse.com/products/ai/