Snowflake SnowPro Certification Practice Test 2025 - Free SnowPro Practice Questions and Study Guide

In Snowflake, compute scaling behavior is designed to enhance performance and efficiency when handling queries. When queries are currently running, Snowflake does not allow the compute resources to scale out. Instead, it operates with the resources allocated at the time the queries are initiated.

This means that once a query starts executing, it utilizes the pre-allocated compute warehouse, and any scaling operations—such as adding more compute nodes—cannot take effect until the ongoing queries are completed and the warehouse is in a state that permits resizing.

The reason this is important is that Snowflake's architecture aims to maintain query integrity and performance without introducing latency due to changes in compute resources while active queries are processing. In this way, Snowflake ensures that workloads remain consistent and predictable, based on the resources originally assigned for each query, leading to a more reliable performance experience for users.

The other choices may suggest varying circumstances under which compute scaling could occur, but in the context of running queries, the fact remains that compute resources cannot dynamically scale out until those queries are resolved.