Syself Brings GPU Support to Hetzner Bare Metal Servers for AI and High- Performance Workloads

With this integration, Syself Autopilot users can now leverage powerful NVIDIA GPUs on Hetzner’s dedicated servers while maintaining the full automation and self-healing capabilities of Kubernetes. This unlocks a high-performance, yet budget-friendly alternative to traditional hyperscalers, giving businesses the power they need at a fraction of the cost.

Affordable AI & HPC with Hetzner’s GPU Servers

Hetzner has built a reputation as one of the most cost-effective hosting providers in the world, and its GPU-powered servers continue that tradition. With dedicated NVIDIA GPUs, organizations can now train AI models, run deep learning applications, and process large datasets without incurring the high costs of AWS, GCP, or Azure. This integration makes Hetzner a highly attractive choice for startups, research institutions, and enterprises looking to optimize both performance and cost.

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GPU acceleration is critical for modern workloads, but high cloud costs have kept it out of reach for many companies. With Syself Autopilot now supporting Hetzner’s bare metal GPU servers, we are making enterprise-grade AI infrastructure accessible and affordable—without compromising on performance or automation.

Sven Batista Steinbach

CEO at Syself

Seamless Kubernetes GPU Orchestration with Syself

By integrating Hetzner’s GPU servers into Syself Autopilot, users get a fully managed, Kubernetes-native approach to GPU orchestration:

• Out-of-the-box GPU Support – No manual configurations needed; Syself automatically provisions GPU-enabled Kubernetes clusters.
• Automated Scaling & Resource Management – Optimize GPU utilization dynamically, ensuring workloads scale efficiently.
• High-Performance Bare Metal – Get the full power of dedicated NVIDIA GPUs without virtualization overhead.
• Cost Savings up to 45% – Compared to hyperscalers, Hetzner’s GPU servers provide a dramatically lower total cost of ownership (TCO).
• Self-Healing & Automated Cluster Management – Ensure uptime and reliability with Syself’s autonomous Kubernetes platform.

Expanding Kubernetes for AI, ML, and HPC Workloads

The combination of Kubernetes and GPU support is a game-changer for AI-driven companies. Almost all AI workloads today run on Kubernetes, making it the de facto standard for AI infrastructure. With Syself’s integration of GPU acceleration on Hetzner Bare Metal, businesses can now train models, process data, and run AI inference—all within a single Kubernetes cluster hosted in European data centers.

By consolidating compute, storage, and GPU workloads into a unified Kubernetes environment, companies can:

• Run AI workloads and databases in the same cluster – No need for separate environments, reducing complexity and improving efficiency.
• Leverage GPU acceleration for deep learning and inference – Achieve high-speed model training and real-time inference without external services.
• Ensure high availability and automated failover – Syself Autopilot handles node restarts, workload rescheduling, and infrastructure self-healing.
• Run infrastructure entirely within Europe – Ensuring compliance with GDPR and national data sovereignty standards by running workloads on European infrastructure, managed by German companies.

With Syself Autopilot, organizations can deploy fully optimized Kubernetes AI infrastructure that combines compute, GPU acceleration, and database management into a single automated platform.

The combination of Kubernetes and GPU support is a game-changer for AI-driven companies. Almost all AI workloads today run on Kubernetes, making it the de facto standard for AI infrastructure. With Syself’s integration of GPU acceleration on Hetzner Bare Metal, businesses can now train models, process data, and run AI inference—all within a single Kubernetes cluster.

By consolidating compute, storage, and GPU workloads into a unified Kubernetes environment, companies can:

• Run AI workloads and databases in the same cluster – No need for separate environments, reducing complexity and improving efficiency.
• Leverage GPU acceleration for deep learning and inference – Achieve high-speed model training and real-time inference without external services.
• Ensure high availability and automated failover – Syself Autopilot handles node failures, workload rescheduling, and infrastructure self-healing.

With Syself Autopilot, organizations can deploy fully optimized Kubernetes AI infrastructure that combines compute, GPU acceleration, and database management into a single automated platform.

This integration is a major milestone for AI and high-performance computing on Kubernetes. Whether running AI inference, deep learning, or scientific simulations, organizations can now take advantage of affordable, high-performance GPU computing with Kubernetes automation.

Hetzner’s dedicated GPU servers, equipped with high-memory bandwidth and powerful NVIDIA GPUs, provide an optimal foundation for AI training, large-scale simulations, and scientific computing. These servers offer a cost-effective alternative for businesses looking to leverage GPU acceleration without the high costs of traditional cloud providers.

The Future of Cost-Effective and Compliant Kubernetes AI Infrastructure

Organizations leveraging AI and machine learning must also adhere to stringent security, compliance, and data sovereignty requirements. With Syself Autopilot running on Hetzner’s ISO 27001-certified data centers, businesses can ensure their AI workloads meet GDPR, ISO, and other industry regulations while maintaining complete control over their infrastructure.

By choosing European-based infrastructure and Kubernetes automation, enterprises benefit from:

• Full compliance with European data protection laws, ensuring AI data stays within trusted jurisdictions.
• Certified security standards, leveraging Hetzner’s ISO 27001 and SOC-compliant environments.
• Operational transparency and control, avoiding vendor lock-in with a 100% Kubernetes-native approach.

With Syself’s continued innovation, more cloud and bare metal providers will be supported in the future, further expanding the ecosystem of affordable AI infrastructure. Syself remains committed to helping businesses reduce complexity, optimize costs, and accelerate AI innovation with Kubernetes.

Get Started with Syself Autopilot on Hetzner GPU Servers

Syself Autopilot is now fully integrated with Hetzner GPU servers. Organizations looking to deploy GPU-powered Kubernetes clusters can get started today:

About Syself

Syself is a cloud-native automation company specializing in Kubernetes lifecycle management, self-healing infrastructure, and AI workload optimization. With deep expertise in Cluster API, Kubernetes, and high-performance infrastructure, Syself delivers cost-efficient, fully automated Kubernetes solutions.

Syself has been a key contributor to Cluster API Provider for Hetzner (CAPH) and played a pivotal role in the Sovereign Cloud Stack (SCS) initiative, a project funded by the German Federal Ministry for Economic Affairs and Climate Action (BMWK). As part of this effort, Syself developed a Kubernetes-as-a-Service (KaaS) solution to enhance digital sovereignty in Europe, ensuring secure, compliant, and scalable cloud-native infrastructure.

About Hetzner

Hetzner is a leading European hosting provider known for its high-performance and cost-effective infrastructure. With data centers in Germany, Finland, and the United States, Hetzner provides bare metal and cloud solutions that offer unbeatable price-to-performance ratios.

Their dedicated GPU servers are designed for AI, deep learning, and HPC applications, delivering top-tier performance at industry-leading affordability.