Google Cloud Professional Data Engineer Exam 2025 – 400 Free Practice Questions to Pass the Exam

Cloud Functions enhance data process performance by running only when triggered by specific events. This event-driven architecture allows functions to execute in response to various triggers such as changes in Cloud Storage, updates to a Pub/Sub message, or HTTP requests. This approach optimizes resource utilization because these functions are executed only when needed, leading to cost savings and reduced idle resource consumption.

Since functions are executed in a serverless environment, they automatically scale based on the incoming event load. This means that during high-demand periods, multiple instances can be activated seamlessly, providing excellent performance without the need for manual intervention. This design is particularly beneficial in data processing scenarios, as it allows for the efficient handling of tasks such as data ingestion, transformation, and loading, which can respond dynamically to changes in the data pipeline.

The other options do not accurately reflect how Cloud Functions operate. For instance, while optimizing legacy systems can be a general benefit of moving to cloud-native architectures, it doesn't specifically capture the essence of how Cloud Functions enhance performance through event-driven execution. Constant user supervision is contrary to the serverless model, where functions are expected to run independently. Finally, while user input can trigger functions in certain scenarios, relying solely on user input to operate would contradict the automated, event-driven nature