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TEN's blog on enterprise GPU infrastructure — GPU utilization, FinOps, AI networking, and data center power. Practical insights for teams running AI at scale.
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On-Prem vs Cloud GPU: How to Choose

On-Prem vs Cloud GPU: How to Choose

Build GPU infrastructure on-prem or rent it in the cloud? Compare the two on TCO, data security, scalability, and utilization — plus when a hybrid strategy makes the most sense.
Amanda's avatar
Sep 14, 2026
GPU & AI Ops
The GPU Utilization Trap: 95% Isn't Real

The GPU Utilization Trap: 95% Isn't Real

GPU utilization of 95% can still mean your GPUs are barely working. Here's why nvidia-smi's utilization metric doesn't reflect actual compute, what MFU really measures, and how to monitor GPU efficiency correctly.
Amanda's avatar
Sep 12, 2026
GPU & AI Ops
5 Real Reasons Your GPU Utilization Is Stuck at 5%

5 Real Reasons Your GPU Utilization Is Stuck at 5%

Average GPU utilization of just 5% isn't a GPU shortage problem. Here are the five real causes — idle allocation, monopolized cards, no scheduling — plus how to diagnose and fix each
Amanda's avatar
Sep 09, 2026
GPU & AI Ops
Kubernetes GPU Scheduling Explained

Kubernetes GPU Scheduling Explained

Why do GPU jobs sit pending when GPUs are still free? A clear look at how Kubernetes GPU scheduling works, the limits of the default scheduler, the fragmentation problem, and what efficient GPU placement requires.
Amanda's avatar
Sep 03, 2026
GPU & AI Ops
GPU Power Optimization: How to Control the 40% of AI Data Center Operating Costs That Go to Power

GPU Power Optimization: How to Control the 40% of AI Data Center Operating Costs That Go to Power

No matter how many GPUs you buy, there's no profitability without power control. — we break down AIPub's GPU power optimization strategy.
Amanda's avatar
Aug 11, 2026
GPU & AI Ops
On-Prem vs Cloud GPU: How to Choose

On-Prem vs Cloud GPU: How to Choose

Build GPU infrastructure on-prem or rent it in the cloud? Compare the two on TCO, data security, scalability, and utilization — plus when a hybrid strategy makes the most sense.
Amanda's avatar
Sep 14, 2026
GPU & AI Ops
The GPU Utilization Trap: 95% Isn't Real

The GPU Utilization Trap: 95% Isn't Real

GPU utilization of 95% can still mean your GPUs are barely working. Here's why nvidia-smi's utilization metric doesn't reflect actual compute, what MFU really measures, and how to monitor GPU efficiency correctly.
Amanda's avatar
Sep 12, 2026
GPU & AI Ops
5 Real Reasons Your GPU Utilization Is Stuck at 5%

5 Real Reasons Your GPU Utilization Is Stuck at 5%

Average GPU utilization of just 5% isn't a GPU shortage problem. Here are the five real causes — idle allocation, monopolized cards, no scheduling — plus how to diagnose and fix each
Amanda's avatar
Sep 09, 2026
GPU & AI Ops
Kubernetes GPU Scheduling Explained

Kubernetes GPU Scheduling Explained

Why do GPU jobs sit pending when GPUs are still free? A clear look at how Kubernetes GPU scheduling works, the limits of the default scheduler, the fragmentation problem, and what efficient GPU placement requires.
Amanda's avatar
Sep 03, 2026
GPU & AI Ops
GPU Power Optimization: How to Control the 40% of AI Data Center Operating Costs That Go to Power

GPU Power Optimization: How to Control the 40% of AI Data Center Operating Costs That Go to Power

No matter how many GPUs you buy, there's no profitability without power control. — we break down AIPub's GPU power optimization strategy.
Amanda's avatar
Aug 11, 2026
GPU & AI Ops
The Structural Limits of Time-Slicing: How Spatial Partitioning Solves the 30% GPU Utilization Problem

The Structural Limits of Time-Slicing: How Spatial Partitioning Solves the 30% GPU Utilization Problem

Low GPU utilization isn't caused by the structural limits of time-slicing. See how spatial partitioning fundamentally solves these problems.
Amanda's avatar
Aug 08, 2026
GPU & AI Ops
GPU Cluster Adoption Guide: 5 Essential Checks for Scalable AI Infrastructure

GPU Cluster Adoption Guide: 5 Essential Checks for Scalable AI Infrastructure

Thinking of building a GPU cluster? Check these 5 essential factors before scaling your AI infrastructure, from distributed training to scheduling and resource optimization.
Amanda's avatar
Aug 07, 2026
GPU & AI Ops
NVIDIA MIG: A Practical Guide to GPU Partitioning for Efficient AI Infrastructure

NVIDIA MIG: A Practical Guide to GPU Partitioning for Efficient AI Infrastructure

What is NVIDIA MIG? Learn how Multi-Instance GPU enables efficient GPU partitioning, improves utilization, and reduces AI infrastructure costs with real-world strategies.
Amanda's avatar
Aug 07, 2026
GPU & AI Ops
GPU Resource Optimization: 5 Essential Checks Before Building AI Infrastructure

GPU Resource Optimization: 5 Essential Checks Before Building AI Infrastructure

Before buying more GPUs, check your AI infrastructure. Learn 5 essential steps to optimize GPU resources and improve performance with smarter operations.
Amanda's avatar
Aug 05, 2026
GPU & AI Ops
Hybrid Multi-Cluster AI Infrastructure Management: A Unified Strategy

Hybrid Multi-Cluster AI Infrastructure Management: A Unified Strategy

Learn how to manage hybrid and multi-cluster AI infrastructure. Discover unified orchestration strategies to optimize GPU utilization and reduce operational complexity.
Amanda's avatar
Aug 04, 2026
GPU & AI Ops
AI Infrastructure Optimization: Why GPU Monitoring Is Essential

AI Infrastructure Optimization: Why GPU Monitoring Is Essential

Learn why GPU monitoring is critical for AI infrastructure. Discover how AI Pub enables real-time visibility, bottleneck detection, and cost optimization.
Amanda's avatar
Aug 04, 2026
GPU & AI Ops

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