Track GPU Usage → Generate Cost Reports → Schedule Reviews

intermediate30 minPublished Mar 31, 2026
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Monitor GPU utilization across your AI infrastructure, automatically generate detailed cost reports, and schedule regular optimization reviews with stakeholders.

Workflow Steps

1

Prometheus

Collect GPU and cost metrics

Deploy Prometheus with GPU exporters (nvidia-smi exporter) and cloud billing exporters to collect real-time GPU utilization, memory usage, and cost data. Configure scraping intervals of 15 seconds for GPU metrics and hourly for cost data.

2

Grafana

Build cost optimization dashboards

Create dashboards showing GPU utilization vs. cost, idle resource identification, and cost trends over time. Add panels for cost per model training run, efficiency ratios, and resource waste indicators with threshold-based color coding.

3

Grafana

Generate and distribute automated reports

Set up Grafana's reporting feature to automatically generate weekly PDF reports with key cost metrics, efficiency recommendations, and utilization trends. Configure email distribution to engineering leads and finance stakeholders.

Workflow Flow

Step 1

Prometheus

Collect GPU and cost metrics

Step 2

Grafana

Build cost optimization dashboards

Step 3

Grafana

Generate and distribute automated reports

Why This Works

Prometheus provides granular, real-time metrics while Grafana transforms complex data into actionable insights and automated reports, essential for managing expensive GPU resources efficiently.

Best For

Engineering teams running AI workloads who need to track GPU costs and optimize infrastructure spending with regular stakeholder reporting

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