Google Associate Cloud Engineer Question 228
Select 4Google Cloud PlatformAs a Google Cloud Associate Cloud Engineer, you are tasked with setting up an autoscaling configuration for an instance group that runs a web application. The application needs to handle varying web traffic efficiently. Which of the following actions should you take to ensure the instance group scales appropriately with the load?
- A
Set the target CPU utilization to 60% to ensure instances scale up before they become over-utilized.
- B
Configure a minimum number of instances to 3 to ensure availability even during low traffic.
- C
Enable predictive autoscaling to anticipate future demand based on historical patterns.
- D
Set the maximum number of instances to 20 to prevent excessive scaling and control costs.
- E
Use a fixed-size instance group instead of an autoscaling group to simplify management.
Show answer and explanation
Correct answers: A, B, C, D
Explanation
To effectively handle varying web traffic, configuring autoscaling parameters such as target CPU utilization, minimum instances, and maximum instances is essential. Predictive autoscaling further enhances the system's ability to manage load by anticipating future demand. A fixed-size instance group would not be suitable as it cannot dynamically adjust to changing loads.
- A. Correct.
Setting the target CPU utilization to 60% helps the system start scaling out before resources are fully utilized, ensuring responsiveness to load.
- B. Correct.
Configuring a minimum number of instances ensures that there is always at least a baseline level of service, which is crucial for availability.
- C. Correct.
Enabling predictive autoscaling allows the system to adjust resources based on anticipated demand derived from historical data, optimizing performance.
- D. Correct.
Setting a maximum number of instances helps control costs and prevent the system from over-provisioning during unexpected peaks.
- E. Incorrect.
Using a fixed-size instance group does not allow the system to adjust resources based on load, which is contrary to the requirements for handling varying traffic efficiently.