SOL-C01 Exam Dumps | You have a Snowflake virtual warehouse named 'COMPUTE that is experiencing performance issues during

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Snowflake.SOL-C01.v2026-01-13.q155
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Question 124/155

You have a Snowflake virtual warehouse named 'COMPUTE that is experiencing performance issues during peak hours. The workload consists of a mix of complex analytical queries and high- volume data loading operations. To optimize performance, you want to implement resource monitoring and auto- scaling. Which of the following strategies would be MOST effective?

A. Increase the size of 'COMPUTE_WH' to a larger T-shirt size (e.g., from Medium to Large).

B. Create a resource monitor that triggers notifications when the warehouse's credit consumption exceeds a certain threshold.

C. Enable auto-suspend on "COMPUTE_WH' to minimize costs during idle periods.

D. Create separate virtual warehouses for analytical queries and data loading, configure auto-scaling on each warehouse, and use resource monitors to control credit consumption.

E. Implement workload management rules to prioritize analytical queries over data loading operations.

Correct Answer: D

Option D provides the most effective solution. Separating workloads onto dedicated warehouses allows for independent scaling and optimization. Auto-scaling ensures that each warehouse can adjust its resources dynamically to meet the demands of its specific workload. Resource monitors help control costs and prevent runaway credit consumption. While increasing warehouse size (A) might improve performance, it's not as targeted as workload separation. Resource monitors and auto-suspend (B and C) are helpful but don't address the core issue of workload contention.
Workload management rules (E) can help prioritize, but don't scale resources dynamically.

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