GPU Cost Monitoring: Track Utilization and Attribute AI Spend
Blog post from Cast AI
GPU utilization in Kubernetes clusters is notably low, averaging just 5%, with costs compounding due to idle GPUs, such as AWS's H100 GPU costing about $8,850 per month when not in use. The Cast AI 2026 State of Kubernetes Optimization Report highlights the challenges faced by teams, who often provision GPUs for peak demand without scaling down afterward, resulting in substantial financial waste. NVIDIA's Data Center GPU Manager (DCGM) serves as the primary tool for tracking GPU usage, providing metrics that can be integrated into Prometheus for monitoring and analysis. Effective cost management involves distinguishing between requests-based and usage-based attribution models, allowing teams to align GPU usage with actual needs and financial accountability. Implementing strategies like detecting idle GPUs, right-sizing requests, and setting budget constraints can lead to significant cost savings, emphasizing the importance of visibility in managing GPU resources efficiently.
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