A Snowflake environment hosts two distinct workloads: daily ETL processes that require significant compute power and ad-hoc analytical queries from business users. You want to optimize cost and perfor

Question

Options

• AUse a single, large virtual warehouse for both ETL and ad-hoc queries, with auto-suspend
• BUse one virtual warehouse sized for the ETL workload and another, smaller virtual warehouse for
• CUse a single, small virtual warehouse for both ETL and ad-hoc queries to minimize cost.
• DUse a single, large virtual warehouse for ETL and disable auto-suspend to ensure consistent
• EUse separate virtual warehouses for ETL and ad-hoc queries, and configure resource monitors to

• A
  14% (6)
• B
  58% (25)
• C
  23% (10)
• D
  5% (2)

Explanation

Separating workloads into dedicated virtual warehouses (B) prevents resource contention - ETL jobs won't starve business users and vice versa - while right-sizing each warehouse to its workload avoids over-provisioning. Adding resource monitors (E) closes the loop on cost control by setting credit limits and alerts per warehouse, giving you both performance isolation and spend visibility. Together, B and E follow Snowflake's core best practice: workload isolation + cost governance.

Why the distractors fail:

• A - A single large warehouse wastes credits on ad-hoc queries that rarely need that much compute, even with auto-suspend.
• C - A single small warehouse bottlenecks the ETL workload, degrading performance and extending run times, which can actually cost more in credits.
• D - Disabling auto-suspend is an anti-pattern; the warehouse burns credits while idle, directly inflating cost with no benefit.

Memory tip: Think "right-size, right-purpose, right-guardrails." Two workloads with different shapes → two warehouses sized to fit → resource monitors as the safety net. Any answer that collapses multiple workloads into one warehouse, or removes cost controls, is a red flag.

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