💰
FinOps

GPU Cost Attribution & Optimization

idle GPU cost per team cluster efficiency power draw

How Graphite achieves this
Graphite metric paths natively encode team and project tags, gpu.team.{name}.project.{name}.utilization, no complex label taxonomy required
Graphite's integral() and sumSeries() functions compute total GPU-hours consumed per team per billing period, directly reportable to finance
Idle GPU alert: Graphite threshold fires when utilisation stays below 10% for >15 minutes during business hours, reclaim spend automatically
Cost modelling: divideSeries(cost_per_hour, tokens_per_hour) produces a live cost-per-token metric visualised in the same Graphite dashboard
MetricFire includes pre-built Grafana dashboards for GPU FinOps. Per-team cost attribution, idle GPU tracking, cluster efficiency, and spend trends, ready on day one with no dashboard configuration needed
Graphite metrics collected
gpu.{id}.utilization_pct gpu.{id}.power_watts cost.team.{name}.gpu_hours cost.project.{name}.gpu_hours cluster.allocated_gpus cluster.idle_gpus cost.per_token
Self-hosted pain solved
Legacy monitoring stacks lack standard cost attribution taxonomy → Graphite path conventions encode cost dimensions natively
Ops teams can't produce GPU spend reports for engineering managers → Graphite summaries are directly exportable
Idle GPU detection requires complex query logic in legacy stacks → Graphite threshold alerts on utilisation paths are simple and reliable
Graphite value: Engineering leaders get the per-team GPU spend dashboard that finance has always wanted and self-hosted stacks have never been able to produce reliably, built on Graphite's hierarchical metric path model and visualised in MetricFire-hosted Grafana dashboards your finance team can actually bookmark.

GPU Monitoring Use Cases
Explore other use cases

MetricFire's Hosted Graphite covers every GPU workload. See how it fits your team's specific challenge.