DEA-C02 Performance Optimization Practice Question
A user complains that a dashboard query is slow during peak hours. The warehouse is configured with auto-suspend and auto-resume. What is the most likely cause of the latency observed during the initial execution?
⚠ Common exam trap
Candidates often incorrectly attribute the latency to network congestion or result cache misses, failing to realize that a suspended warehouse must provision resources before it can process any query.
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
✓
Warehouse provisioning time.
When a warehouse is in a suspended state, the first query submitted triggers a 'cold start' as Snowflake provisions compute resources. This process involves allocating virtual nodes, which takes a few seconds, leading to latency. This is a common occurrence in environments using auto-suspend to save costs. Understanding this behavior is vital for performance tuning, as engineers often confuse this infrastructure provisioning time with actual query execution performance issues.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The query result cache is full.
Why it's wrong here
The query result cache does not have a capacity limit that causes slow performance. If it is full, Snowflake simply removes the oldest entries. This mechanism is transparent to the user and does not cause latency during query execution; instead, it simply results in a cache miss.
- ✓
Warehouse provisioning time.
Why this is correct
When a warehouse is suspended, the first query triggers the provisioning of compute resources. This latency is inherent to the cloud-native architecture of Snowflake. Once the resources are active, subsequent queries will run faster because the compute is already 'warm' and ready to process incoming execution requests.
- ✗
The warehouse size is too small.
Why it's wrong here
While a small warehouse might process data slower, it does not explain the initial latency observed only during the start of a workload. Warehouse size impacts the duration of the query execution once it begins, not the initialization time required to provision the hardware resources in the cloud.
- ✗
The metadata cache is invalidated.
Why it's wrong here
Metadata caching is handled automatically by Snowflake. There is no user-facing mechanism for metadata cache invalidation that would cause latency upon warehouse resume. This is a background process that ensures data consistency across the environment and does not contribute to the observed query startup delay.
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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
This DEA-C02 practice question is part of Courseiva's free Snowflake certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the DEA-C02 exam.