The correct action is to stop the instance, change the machine type to n2-standard-4, and start it again. This directly implements the Cloud Cost Optimization recommender’s rightsizing suggestion, which flagged the instance as over-provisioned given its consistent 25% CPU utilization during peak hours. By briefly stopping the instance to switch to a smaller, well-tested machine type, the engineer reduces cost without risking prolonged downtime or application instability. On the Google Professional Cloud DevOps Engineer exam, this scenario tests your understanding of the recommender’s output and the safe, sequential steps for rightsizing—a common trap is attempting a live migration or changing the machine type while the instance is running, which is not supported for most production workloads. Remember the mnemonic “Stop, Swap, Start” to recall the minimal-risk workflow: stop the VM, swap the machine type, then start it again.
PCDOE Managing Google Cloud costs Practice Question
This PCDOE practice question tests your understanding of managing google cloud costs. Examine the command output carefully: the correct answer depends on what the output actually shows, not on general recall alone. 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.
Network Topology
Refer to the exhibit. The output shows a recommendation from the Cloud Cost Optimization recommender for an instance in us-central1-a. The instance is a production web server that consistently runs at 25% CPU utilization during peak hours. What should the DevOps engineer do to implement this recommendation with minimal risk?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Stop the instance, change the machine type to n2-standard-4, and start it again.
Option A is correct because the Cloud Cost Optimization recommender has identified that the current instance is over-provisioned for its actual workload (25% CPU utilization during peak hours). By stopping the instance, changing the machine type to n2-standard-4 (which has 4 vCPUs and 16 GB RAM, matching the recommended 4 vCPUs and 15 GB memory), and starting it again, the engineer rightsizes the instance without incurring downtime during the change itself. This approach minimizes risk because the instance is stopped only briefly for the machine type change, and the new machine type is a standard, well-tested configuration that aligns with the recommender's analysis.
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.
✓
Stop the instance, change the machine type to n2-standard-4, and start it again.
Why this is correct
This directly implements the recommendation with minimal risk.
Related concept
Read the scenario before looking for a memorised answer.
✗
Ignore the recommendation because the instance is production and any change might cause downtime.
Why it's wrong here
The recommendation is based on low utilization, and a machine type change can be done with a brief restart.
✗
Add a second n2-standard-4 instance behind a load balancer to distribute load.
Why it's wrong here
This would increase cost, not reduce it.
✗
Use a custom machine type with 4 vCPUs and 32 GB memory to ensure enough RAM.
Why it's wrong here
The recommendation is for n2-standard-4 (16 GB RAM), and over-provisioning RAM may not be needed.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the misconception that production instances should never be modified, but the correct approach is to use the recommender's suggestion with a controlled stop/start process, which minimizes risk and is a standard cost optimization practice.
Detailed technical explanation
How to think about this question
The Cloud Cost Optimization recommender in Google Cloud uses historical usage metrics (CPU, memory, network) to suggest machine type changes that maintain performance while reducing cost. For Compute Engine instances, changing the machine type requires stopping the instance, which causes a brief outage; however, for production web servers, this can be mitigated by using a managed instance group with rolling updates or by scheduling the change during a maintenance window. The recommender specifically targets underutilized resources, and the n2-standard-4 machine type provides 4 vCPUs and 16 GB RAM, which is a direct match for the recommended 4 vCPUs and 15 GB memory, ensuring the instance has adequate resources for its peak workload.
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 startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Managing Google Cloud costs — This question tests Managing Google Cloud costs — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Stop the instance, change the machine type to n2-standard-4, and start it again. — Option A is correct because the Cloud Cost Optimization recommender has identified that the current instance is over-provisioned for its actual workload (25% CPU utilization during peak hours). By stopping the instance, changing the machine type to n2-standard-4 (which has 4 vCPUs and 16 GB RAM, matching the recommended 4 vCPUs and 15 GB memory), and starting it again, the engineer rightsizes the instance without incurring downtime during the change itself. This approach minimizes risk because the instance is stopped only briefly for the machine type change, and the new machine type is a standard, well-tested configuration that aligns with the recommender's analysis.
What should I do if I get this PCDOE 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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Question Discussion
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