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Know exactly where your GPU dollars go. The Cost Explorer gives you full visibility into spend across teams, clusters, GPU types, and workload classes — with built-in forecasting, waste detection, and optimization recommendations to help you get more out of every GPU-hour. Navigate to Cost Explorer in the Chamber dashboard sidebar to get started.

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At a Glance

Cost Explorer is built to answer the questions every GPU infrastructure team asks:
  • How much are we spending? Total and per-team GPU costs with trend analysis
  • Where is the money going? Breakdown by team, user, cluster, GPU type, and workload class
  • What will we spend next? Month-end forecasts with confidence intervals
  • What are we wasting? Idle capacity, failed workload costs, and underutilized resources
  • How do we optimize? Actionable recommendations for spot instances, rightsizing, and failure reduction

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Key Metrics

Four headline numbers are displayed at the top of every Cost Explorer view:
MetricDescription
Total SpendGPU cost from completed workloads in the selected time range
Month to DateCumulative GPU spend so far this calendar month
Projected Month-EndWhere you’ll land by end of month, based on current trajectory
Trend vs. PriorPercentage change comparing the recent period to the prior period

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Filtering and Grouping

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Filters

Slice your data by any combination of:
  • Team — One or more teams
  • Cluster — Specific capacity pools
  • GPU Type — Hardware type (A100, H100, etc.)
  • Workload Class — Type of workload (training, inference, interactive, etc.)
Filters apply across every chart, metric, and table on the page. Active filters appear as removable pills below the filter bar.

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Grouping

Change how the spend chart and cost breakdown are organized:
  • Team / User / Cluster / GPU Type / Workload Class
Switch grouping at any time to see costs from a completely different angle.

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Time Range

Pick from presets or define your own window:
  • Last 7 / 30 / 90 days
  • This month / Last month
  • Custom range with a calendar picker
Filters and time range are saved in the URL — bookmark or share a specific cost view with your team.

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Spend Over Time

A time-series chart shows how your spend trends across the selected period:
  • Granularity — Toggle between daily, weekly, or monthly aggregation
  • Stacked series — Top contributors are shown individually; smaller ones grouped as “Other”
  • Forecast overlay — Project costs forward with a shaded 95% confidence band

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Forecasting

Turn on the forecast overlay to see where spend is heading:
  • Uses linear regression fitted to your daily historical data
  • Shows a projected line with upper and lower confidence bounds
  • Defaults to an end-of-month projection, but you can pick any date up to 365 days ahead
  • Trend detection automatically classifies your spend as increasing (over 10% growth), decreasing (over 10% decline), or stable

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Capacity Utilization

This section compares what you’re paying for (provisioned GPU capacity) against what’s actually being used by workloads:
MetricDescription
Total Capacity CostCost of all provisioned GPUs across selected clusters
Used CostCost attributable to completed workloads
Wasted CostIdle capacity — provisioned but sitting unused
Utilization %Percentage of provisioned capacity actively used
Utilization is color-coded so you can spot problems at a glance:
  • Green (70%+) — Healthy
  • Orange (40-70%) — Worth reviewing
  • Red (under 40%) — Significant optimization opportunity
Capacity metrics come from cluster telemetry. Team and Workload Class filters only affect the “Used Cost” number, since provisioned capacity isn’t tied to specific workloads.

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Cost Breakdown

A donut chart shows the proportional distribution of spend by your selected dimension. Items contributing less than 1% are grouped as “Other” — hover to expand the full list.

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Cost Events Table

Dig into the details with a full table of individual cost events:
ColumnDescription
DateWhen the cost was incurred
TeamTeam name
UserWho submitted the workload
ClusterCapacity pool
GPU TypeHardware type
Workload ClassType of workload
HoursGPU instance-hours consumed
RateHourly rate for this GPU type
CostTotal cost for this event

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Pagination and Export

  • Navigate results with cursor-based pagination
  • Set your page size: 10, 25, 50, or 100 rows
  • Export to CSV to pull data into spreadsheets or external tools (up to 100K rows)

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GPU Rate Configuration

Cost calculations rely on per-GPU-type hourly rates. Org Admins can set these up:
  1. Click the settings icon in the Cost Explorer header
  2. Set the hourly rate for each GPU type in your organization
  3. Rates apply retroactively to all cost calculations

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Waste Analysis

Chamber automatically surfaces wasted GPU spend from three sources:
Waste CategoryDescription
Failed WorkloadsGPU time consumed by workloads that ultimately failed
Preempted WorkloadsGPU time from workloads preempted before completion
Short Runtime, High CostWorkloads under 5 minutes that cost more than $1 — often a sign of misconfiguration

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Optimization Recommendations

Chamber analyzes your usage patterns and surfaces actionable next steps:

Spot Instance Savings

Identifies workloads that could run on spot or preemptible instances, with estimated monthly savings.

Failure Reduction

Flags teams or GPU types with failure rates above 20% and calculates the cost impact.