The correct answer is to create a custom Compute Engine image that bakes the application and configuration files directly into the image for the managed instance group. This solves the autoscaler not adding instances fast enough because the root cause is the slow startup time—new instances take over five minutes to become healthy due to downloading large configuration files from Cloud Storage at boot. By pre-loading the application and configuration into the image, new instances can pass the TCP health check and serve traffic almost instantly, allowing the autoscaler to react to CPU spikes much more quickly. On the Google Professional Cloud Architect exam, this scenario tests your understanding that autoscaling response is limited by instance startup latency, not just scaling policy settings; a common trap is to adjust autoscaler cooldown periods or increase the target CPU utilization, which fails to address the bottleneck. Memory tip: "Bake it, don't break it"—pre-baking the image eliminates the boot-time download delay, making the autoscaler truly responsive.
Google PCA Manage and provision cloud infrastructure Practice Question
This PCA practice question tests your understanding of manage and provision cloud infrastructure. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
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?
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.
Option C is correct because 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.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
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.
Related concept
Read the scenario before looking for a memorised answer.
✗
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.
Common exam traps
Common exam trap: answer the scenario, not the keyword
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.
Detailed technical explanation
How to think about this question
Managed instance group autoscalers use a signal (e.g., CPU utilization) and a target value to decide how many instances to add or remove, but the actual scaling speed is limited by the time it takes for new instances to pass the health check and become 'healthy' in the group. A custom image with pre-baked configuration eliminates the need for startup scripts to download large files, reducing instance initialization from minutes to seconds. In real-world scenarios, this approach is critical for applications with bursty traffic patterns where even a 2-minute delay can cause cascading timeouts and degraded user experience.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
Related glossary terms
Concepts from this question explained
These glossary pages explain the core terms tested in this PCA question in full detail.
Manage and provision cloud infrastructure — This question tests Manage and provision cloud infrastructure — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Create a custom Compute Engine image that includes the application and configuration, and use it in the MIG. — Option C is correct because 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.
What should I do if I get this PCA question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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