Cortex Dashboard
Cortex spend comes from agents, direct inference, SQL functions, search, and coding tools - all billed from one credit pool. This dashboard shows where it's going, who's driving it, and how it's performing, in one page.
Page Overview
At the top, two summary cards:
- Total Cortex Spend - total credits consumed across all Cortex products in the selected period
- Daily Average - average credits burned per day
Use the date range selectors (top right) to adjust the view.
Spend Over Time
A stacked bar chart showing daily Cortex spend:
- Switch the breakdown between Product, Agent, User, or Role to drill into who or what is driving spend
- The dashed line marks the 30-day average, so spikes are easy to spot at a glance
- The Aggregated bars below the chart summarize total credits and % share per product for the selected period
Model Performance & True Cost
Two tables break down cost and latency per model:
| Table | Description |
|---|---|
| Spend per model | Queries, the token/compute credit split, token credits, compute credits, and total credits per model |
| Model latency | P50, P95, and P99 response latency per model and function, sortable by percentile |
Use this to tell whether a cost or performance issue comes from model selection, prompt complexity, or infrastructure latency, rather than just seeing an aggregate cost go up.
How to Use This Page
- Spot spend spikes on the Spend Over Time chart, then switch to Agent or User to trace the spike to its source
- Compare model efficiency using the token/compute split - a low token share means a model is compute-bound rather than token-bound
- Diagnose slow responses by sorting Model Latency by P95 or P99 instead of only looking at aggregate cost