- A
Delete the under-utilized VMs since low utilization indicates they are no longer needed
Why wrong: Low utilization means VMs are over-provisioned, not unnecessary. The workloads still run on them — they just don't need as many resources as allocated. Deletion would break the workload.
- B
Right-size the VMs by migrating to smaller machine types that match actual CPU and memory consumption, reducing costs proportionally
Right-sizing is the direct action. If VMs use 30% of their resources, a smaller machine type that provides the resources actually needed (with some headroom for spikes) costs significantly less. Active Assist proactively surfaces right-sizing recommendations with projected savings.
- C
Purchase Committed Use Discounts for the over-provisioned VMs to reduce their per-hour cost
Why wrong: CUDs reduce the hourly rate but not the fact that you're paying for over-provisioned resources. You'd be committing to paying for idle capacity at a discount — better than full price, but right-sizing eliminates the idle capacity altogether.
- D
Enable sustained use discounts by ensuring VMs run continuously throughout the month
Why wrong: Sustained Use Discounts apply automatically for VMs that run 25%+ of a month — they don't require any action. They also don't address the over-provisioning problem; they reduce the rate on the same over-sized machine.
Quick Answer
The answer is to right-size the VMs by migrating to smaller machine types that match actual CPU and memory consumption. This is the most straightforward cost optimization action because it directly reduces the per-hour compute cost while preserving workload capacity—since the VMs consistently use less than 30% of their allocated resources, moving to a smaller machine type eliminates wasted capacity without any performance impact. On the Google Cloud Digital Leader exam, this scenario tests your understanding of fundamental cost management principles, often appearing as a trap where candidates might mistakenly choose to delete VMs or switch to preemptible instances, which would risk availability or workload disruption. The key insight is that right-sizing underutilized VMs is a low-risk, immediate cost reduction that aligns with the exam’s focus on operational efficiency. Memory tip: think “30% or less? Downsize to impress”—if a VM consistently uses under 30% of its resources, you can safely shrink it to a smaller machine type.
Cloud Digital Leader Scaling with Google Cloud operations Practice Question
This GCDL practice question tests your understanding of scaling with google cloud operations. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. 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 wants to reduce its Google Cloud costs without reducing its workload capacity. The team identifies that several production VMs consistently use less than 30% of their allocated CPU and memory. What is the most straightforward cost optimization action?
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
Right-size the VMs by migrating to smaller machine types that match actual CPU and memory consumption, reducing costs proportionally
Right-sizing VMs by migrating to smaller machine types that match actual CPU and memory consumption directly reduces the cost per hour while maintaining the same workload capacity. Since the VMs are consistently under-utilized, this approach eliminates wasted resources without affecting performance or availability.
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.
- ✗
Delete the under-utilized VMs since low utilization indicates they are no longer needed
Why it's wrong here
Low utilization means VMs are over-provisioned, not unnecessary. The workloads still run on them — they just don't need as many resources as allocated. Deletion would break the workload.
- ✓
Right-size the VMs by migrating to smaller machine types that match actual CPU and memory consumption, reducing costs proportionally
Why this is correct
Right-sizing is the direct action. If VMs use 30% of their resources, a smaller machine type that provides the resources actually needed (with some headroom for spikes) costs significantly less. Active Assist proactively surfaces right-sizing recommendations with projected savings.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Purchase Committed Use Discounts for the over-provisioned VMs to reduce their per-hour cost
Why it's wrong here
CUDs reduce the hourly rate but not the fact that you're paying for over-provisioned resources. You'd be committing to paying for idle capacity at a discount — better than full price, but right-sizing eliminates the idle capacity altogether.
- ✗
Enable sustained use discounts by ensuring VMs run continuously throughout the month
Why it's wrong here
Sustained Use Discounts apply automatically for VMs that run 25%+ of a month — they don't require any action. They also don't address the over-provisioning problem; they reduce the rate on the same over-sized machine.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the misconception that deleting under-utilized VMs is the simplest cost-saving action, but the question explicitly states workload capacity must be maintained, making right-sizing the correct approach.
Detailed technical explanation
How to think about this question
Right-sizing involves analyzing Cloud Monitoring metrics (e.g., CPU utilization, memory usage) over a representative period (e.g., 2 weeks) and selecting a custom or predefined machine type that closely matches the 95th percentile of usage. Google Cloud's 'gcloud compute instances set-machine-type' command allows live migration to a different machine type without downtime, provided the instance is in the same zone and the new type is compatible. In practice, right-sizing can reduce costs by 30-50% for consistently under-utilized VMs.
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.
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FAQ
Questions learners often ask
What does this GCDL question test?
Scaling with Google Cloud operations — This question tests Scaling with Google Cloud operations — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Right-size the VMs by migrating to smaller machine types that match actual CPU and memory consumption, reducing costs proportionally — Right-sizing VMs by migrating to smaller machine types that match actual CPU and memory consumption directly reduces the cost per hour while maintaining the same workload capacity. Since the VMs are consistently under-utilized, this approach eliminates wasted resources without affecting performance or availability.
What should I do if I get this GCDL 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.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Same concept, more angles
2 more ways this is tested on GCDL
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A company's cloud costs have increased by 40% over the past quarter. The operations team wants to identify and address the root causes. Which cost optimization strategies should they investigate first?
medium- A.Immediately upgrade all infrastructure to the latest generation hardware for better efficiency.
- ✓ B.Identify idle and underutilized resources (oversized VMs, unused disks, unattached IPs), apply lifecycle policies to storage, and commit to CUDs for stable workloads.
- C.Migrate all workloads to Spot VMs immediately to reduce costs by 90%.
- D.Switch cloud providers to whoever has the lowest advertised list price.
Why B: Option B is correct because the first step in cloud cost optimization is to identify and eliminate waste from idle or oversized resources, which is the most common source of cost inefficiency. Applying lifecycle policies to storage and committing to Committed Use Discounts (CUDs) for stable workloads are proven strategies to reduce costs without compromising performance. This approach aligns with Google Cloud's recommended FinOps practices, focusing on immediate, high-impact savings before considering architectural changes.
Variation 2. A cloud team performs a quarterly review of its Compute Engine instances and discovers 15 VMs that have had zero CPU utilization for over 90 days. What is the recommended operational response to these idle resources?
medium- A.Leave the VMs running in case they are needed for future workloads — storage costs are minimal for idle VMs
- ✓ B.Investigate whether each VM is still needed; delete confirmed unused VMs to eliminate wasted spend, potentially saving thousands per month
- C.Upgrade the idle VMs to larger machine types so they can handle future workloads if needed
- D.Apply committed use discounts to the idle VMs to reduce their cost while keeping them available
Why B: Option B is correct because the recommended operational response to idle Compute Engine instances is to investigate their necessity and delete them if unused. Idle VMs with zero CPU utilization for over 90 days incur ongoing costs for persistent disks, static IPs, and other attached resources, even if the CPU is idle. Deleting confirmed unused VMs eliminates this wasted spend, potentially saving thousands per month, aligning with Google Cloud's cost optimization best practices.
Last reviewed: Jun 30, 2026
This GCDL practice question is part of Courseiva's free Google Cloud certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the GCDL exam.
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