Avesha, SUSE AI Blueprint Simplifies GPU Orchestration and Enterprise Security

Avesha, a leader in dynamic AI infrastructure orchestration, and SUSE, a global leader in secure open source solutions, today announced a joint AI infrastructure blueprint that combines Avesha’s Elastic GPU Service (EGS) with SUSE AI. This integrated solution provides enterprises with a production-grade AI stack that is both powerful and intuitive, enabling scalable, self-service AI across teams and projects.

The blueprint lets enterprises deploy, manage, and monitor AI workloads across hybrid cloud environments with zero friction. It includes a modern self-service portal, dynamic GPU resource allocation, and comprehensive workload observability—delivering AI infrastructure that is as easy to use as it is powerful.

Blueprint Overview: The AI Stack for Modern Enterprises

• Avesha’s Elastic GPU Service (EGS)
• Dynamic GPU orchestration across clusters and clouds
• Reallocating unused GPU
• Elastic bursting for rapid access to cloud GPUs from on-prem environments
• Preemption and priority-aware scheduling for mission-critical workloads
• Unified observability for usage, cost, and performance
• Project/team isolation and governance for GPU initiatives

SUSE AI

• Built on SUSE Rancher Prime for GPU-aware Kubernetes management
• GenAI & MLOps integrations (eg Ollama, MLFlow, Pytorch, etc)
• Full-stack security with SUSE Security runtime protection
• Impactful insights into AI workloads with AI Observability
• GitOps-driven deployment pipelines
• Enterprise-ready, hardened, and FIPS-compliant

Together, Avesha and SUSE deliver true self-service AI—empowering data scientists, ML engineers, and platform teams to collaborate and launch GPU-powered projects with ease.

Solving Enterprise Challenges in AI Infrastructure

• Enterprises need to scale, secure, and govern AI—without runaway costs or complexity.
• The Avesha–SUSE blueprint addresses these needs by:
• Eliminating underutilized GPU resources through real-time orchestration
• Enabling project- and team-level isolation with precise resource controls
• Providing a no-code self-service interface to spin up GPU workloads
• Simplifying AI model deployment across on-prem and cloud environments
• Securing every layer with zero-trust container runtime protection Project/team isolation and governance for GPU initiatives

Ready for Deployment Today

The Avesha + SUSE AI blueprint is available immediately through both companies and their partner ecosystems. Target industries include finance, healthcare, manufacturing, government, and telco, where GPU-intensive AI workloads and robust governance are mission-critical.