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…

Question

Options

• AIncrease the size of 'COMPUTE_WH' to a larger T-shirt size (e.g., from Medium to Large).
• BCreate a resource monitor that triggers notifications when the warehouse's credit consumption
• CEnable auto-suspend on "COMPUTE_WH' to minimize costs during idle periods.
• DCreate separate virtual warehouses for analytical queries and data loading, configure auto-scaling
• EImplement workload management rules to prioritize analytical queries over data loading

• B
  2% (1)
• C
  6% (3)
• D
  81% (38)
• E
  11% (5)

Explanation

The most effective strategy is to separate workloads into dedicated virtual warehouses: one optimized for complex analytical queries (which benefit from larger sizes and multi-cluster auto-scaling) and another for high-volume data loading (which tends to be I/O-bound and benefits from a different configuration). This eliminates resource contention between the two workload types and allows independent auto-scaling policies for each. Option A (increasing T-shirt size) helps but still mixes workloads and may waste resources. Option B (resource monitor notifications) is reactive monitoring, not optimization. Option C (auto-suspend) reduces cost during idle periods but doesn't address peak performance. Option E is not a native Snowflake feature - Snowflake does not have built-in workload management rules like traditional MPP databases.

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