Google PCA Manage and provision cloud infrastructure Practice Question
A company runs a critical application on Compute Engine instances in a managed instance group (MIG) across three zones in us-central1. The application uses a Cloud Spanner database. Recently, the application experienced increased latency and timeouts during peak hours. The operations team noticed that the MIG's CPU utilization is consistently above 80% during peak hours, and the autoscaler is configured to scale based on CPU utilization with a target of 60%. However, the autoscaler is not adding new instances quickly enough, causing performance degradation. The team also observed that new instances take over 5 minutes to become healthy and serve traffic. The health check is a simple TCP check on port 8080. The application startup script downloads large configuration files from Cloud Storage. What should the team do to improve the autoscaling response time and reduce latency?
⚠ Common exam trap
The trap here is that candidates focus on tuning the autoscaler parameters (CPU target, health check intervals) rather than identifying the actual bottleneck—the instance startup time—which is a common misconception that autoscaling speed is purely a function of scaling policy settings.
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
✓
Create a custom Compute Engine image that includes the application and configuration, and use it in the MIG.
The primary bottleneck is the long instance startup time (over 5 minutes) caused by downloading large configuration files from Cloud Storage at boot. By creating a custom Compute Engine image that bakes the application and configuration into the image, new instances can start serving traffic almost immediately, drastically reducing the time before they become healthy and the autoscaler can consider them in scaling decisions. This directly addresses the root cause of slow autoscaling response, as the autoscaler cannot add instances faster than they become healthy.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Increase the minimum number of instances in the MIG to handle peak load.
Why it's wrong here
Over-provisioning is costly and not efficient.
- ✗
Reduce the autoscaler target CPU utilization to 40% so it scales earlier.
Why it's wrong here
Lower target triggers scaling sooner but doesn't address slow startup.
- ✓
Create a custom Compute Engine image that includes the application and configuration, and use it in the MIG.
Why this is correct
Custom image reduces startup time, allowing faster scaling.
- ✗
Change the health check to HTTP and reduce the initial delay and check intervals.
Why it's wrong here
Does not reduce instance startup time.
Go deeper
Related to this question
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Introduction to Google Cloud Platform
Key term
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