COF-C03 Practice Question: Snowflake AI Data Cloud Features and Architecture
A Snowflake administrator is configuring a new virtual warehouse for a data science team. The team requires the ability to run multiple concurrent queries without queuing, and they want to minimize credit consumption during idle periods. The administrator needs to configure the warehouse with appropriate settings. Which two actions should the administrator take? (Choose two.)
⚠ Common exam trap
The trap here is focusing on auto-resume or result caching, which are helpful but do not directly solve the concurrency and idle cost requirements.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Enable multi-cluster warehouse with auto-scaling.
To handle multiple concurrent queries without queuing, enabling multi-cluster warehouse with auto-scaling allows Snowflake to add clusters dynamically as needed. To minimize credit consumption during idle periods, setting a short auto-suspend period ensures the warehouse stops when not in use. Together, these settings provide both concurrency and cost efficiency. Other options either do not address the requirements or could hinder performance.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Enable multi-cluster warehouse with auto-scaling.
Why this is correct
Multi-cluster warehouses with auto-scaling automatically add clusters when queries are queued and remove them when they are no longer needed. This allows multiple concurrent queries to run without queuing, as additional clusters provide more compute resources. It also helps minimize credit consumption because clusters are only added when required. This setting directly addresses the need for concurrency without queuing while controlling costs.
- ✗
Configure the warehouse to use a smaller size to reduce credits.
Why it's wrong here
Using a smaller warehouse reduces credits per hour but may not provide enough compute resources to handle multiple concurrent queries without queuing. In fact, a smaller warehouse could lead to more queuing because it has fewer resources. The requirement is to avoid queuing, so scaling up or using multi-cluster is more appropriate. A smaller size might reduce cost but at the expense of performance and concurrency.
- ✗
Set the warehouse to auto-resume when a query is submitted.
Why it's wrong here
Auto-resume is typically enabled by default and ensures that the warehouse starts automatically when a query is submitted. While this is necessary for the warehouse to function after being suspended, it does not directly address the requirements of minimizing idle credit consumption or handling concurrency. Auto-resume is a complementary setting but not one of the two key actions to meet the stated goals.
- ✓
Set the warehouse to auto-suspend after a short period of inactivity.
Why this is correct
Auto-suspend automatically suspends the warehouse after a specified period of inactivity, which stops credit consumption when no queries are running. This directly addresses the requirement to minimize credit consumption during idle periods. A short auto-suspend period (e.g., 60 seconds) ensures that the warehouse does not remain running unnecessarily. This is a standard best practice for cost optimization.
- ✗
Enable the query result cache to avoid re-execution.
Why it's wrong here
The query result cache can improve performance for repeated queries, but it does not address concurrency or idle credit consumption. It only helps when identical queries are run again. The scenario focuses on concurrent queries and minimizing idle costs, so the result cache is not relevant. It is a useful feature but not one of the two actions needed here.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Snowflake exam blueprint
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