ADA-C01 Question 387
Single answerMonitor accounts and usageA Snowflake administrator is asked to identify why compute costs spiked during the last 7 days in a production account. Leadership wants a quick analysis that shows which warehouses consumed the most credits and whether warehouse sizing or idle time likely contributed to the increase. The administrator needs a solution that can be queried directly in SQL without building custom ETL pipelines. Which approach should the administrator take?
- A
Query the ACCOUNT_USAGE.WAREHOUSE_METERING_HISTORY view to analyze credits consumed by warehouse over time, and join it with warehouse configuration metadata to correlate spikes with warehouse size and usage patterns.
- B
Query the INFORMATION_SCHEMA.QUERY_HISTORY table function only, because it contains all billed credit information for each warehouse and is the authoritative source for warehouse idle cost analysis.
- C
Query the ORGANIZATION_USAGE views from within the account, because they provide the most detailed warehouse-level metering data for any Snowflake edition and do not require organization-level access.
- D
Use ACCESS_HISTORY to determine warehouse credit consumption, since it records all object access and can be aggregated to calculate billed compute credits by warehouse.
Show answer and explanation
Correct answer: A
Explanation
For account-level monitoring of warehouse compute usage, Snowflake administrators should use the SNOWFLAKE database ACCOUNT_USAGE schema, especially WAREHOUSE_METERING_HISTORY, which records credits used by warehouses over time. This is the most appropriate source for identifying which warehouses contributed to a cost spike during a defined period. To deepen the analysis, administrators often combine metering data with query patterns from QUERY_HISTORY and operational events from warehouse-related history views to determine whether costs were driven by warehouse size, concurrency, long-running workloads, or periods of inactivity. INFORMATION_SCHEMA table functions are useful for near-real-time operational analysis, but they are not the primary source for billed warehouse metering. ORGANIZATION_USAGE is intended for centralized monitoring across multiple accounts from an organization context, not as the default account-level solution. ACCESS_HISTORY supports auditing and governance, not warehouse billing analysis. These practices are consistent with Snowflake documentation on Account Usage views and monitoring credit consumption.
- A. Correct.
Correct. ACCOUNT_USAGE.WAREHOUSE_METERING_HISTORY is the appropriate account-level source for analyzing warehouse credit consumption over time. It supports direct SQL analysis of warehouse metering and is commonly used to identify which warehouses drove compute cost increases. To assess likely causes such as oversized warehouses or low utilization, the administrator can correlate metering history with warehouse metadata and other usage views such as QUERY_HISTORY or WAREHOUSE_EVENTS_HISTORY as needed. This aligns with Snowflake best practice for monitoring account usage using the SNOWFLAKE database shared views.
- B. Incorrect.
Incorrect. QUERY_HISTORY is useful for analyzing query execution patterns, durations, and the warehouse used, but it is not the authoritative source for billed warehouse credits. It does not directly provide complete warehouse metering or reliably isolate idle time costs. A candidate might choose this option because query history is often used in performance troubleshooting, but warehouse cost analysis should begin with WAREHOUSE_METERING_HISTORY.
- C. Incorrect.
Incorrect. ORGANIZATION_USAGE views are intended for organization-level monitoring across accounts and generally require organization account access. They are not the standard answer when an administrator needs to investigate usage within a single account using account-level views. Also, availability depends on organization setup and privileges, so this is not the best direct approach for the stated requirement.
- D. Incorrect.
Incorrect. ACCESS_HISTORY captures data access lineage and governance-related information about which objects were accessed, not compute billing metrics. While it is valuable for auditing and impact analysis, it cannot be used as the primary source to calculate warehouse credit consumption. This distractor targets the common misconception that any historical usage view can be repurposed for cost monitoring.