Usage → Warehouse

The Warehouse page helps you monitor and analyze Snowflake warehouse credit consumption, how query time is spent (execution, compilation, queuing, provisioning), and which warehouses drive the most cost and activity.

Overview

This page gives you:

Credit usage over time — Total and per-warehouse credit usage with configurable date range and granularity
Query time distribution — Where total query time goes: execution, compilation, provisioning, queuing, and other
Credits used by warehouse — A table of each warehouse with query counts and credits for the last 24 hours, 7 days, and 30 days, plus export and per-warehouse actions

Use it to spot high-cost warehouses, optimize query and warehouse sizing, and see if time is lost to queuing or compilation.

Top Warehouses by Credit Usage

This section shows credit usage trends across warehouses.

Page controls

Control	Description
Date Range	Time window for the charts (e.g. Last 30 Days).
Granularity	How to bucket time (e.g. Day).
Show only Revefi Auto-Managed Warehouses	When checked, limits the list and charts to warehouses that Revefi auto-manages.

Charts

Total Credits Used — One chart with aggregate daily (or chosen granularity) credit usage across all warehouses. Use it to see overall spend and peaks.
Per-warehouse charts — A separate bar chart for each warehouse showing credits used over the selected date range. Use these to see which warehouses contribute most and how their usage varies over time.

Query Time Distribution

This section breaks down total query time over the last 30 days so you can see where time is spent.

Total Query time — Sum of all components (e.g. shown in hours).
Total Query Execution Time — Time queries spend actually running. Usually the largest share (e.g. ~55%). High values can mean heavy or inefficient queries.
Total Query Compilation Time — Time spent compiling queries before execution (e.g. ~36%). High values can point to complex queries or frequent schema changes.
Total Warehouse Provisioning Time — Time spent starting or scaling warehouses (e.g. ~1%). Typically small unless you scale often.
Total Queued Time — Time queries wait in queue before running (e.g. ~8%). High values can mean undersized warehouses or concurrency limits.
Others — Remaining query-related time (e.g. minimal).

Use this to decide whether to optimize queries (execution/compilation), resize warehouses (queuing), or change scaling (provisioning).

Credits Used by Warehouse

A table of all warehouses with usage and cost metrics.

Columns

Column	Description
Last 24h query count	Number of queries in the last 24 hours.
Last 24h Credits Used	Credits consumed in the last 24 hours.
Last 7d query count	Number of queries in the last 7 days.
Last 7d Credits Used	Credits consumed in the last 7 days.
Last 30d query count	Number of queries in the last 30 days.
Last 30d Credits Used	Credits consumed in the last 30 days.

Use cases

Cost control — Use “Top Warehouses by Credit Usage” and “Credits Used by Warehouse” to find the biggest consumers and adjust size or schedule.
Performance tuning — Use “Query Time Distribution” to see if time is lost in execution, compilation, or queuing, then target optimizations (queries, warehouse size, concurrency).
Revefi-managed focus — Turn on “Show only Revefi Auto-Managed Warehouses” to review credit and usage trends for auto-managed warehouses only.