The answer is to upgrade the hosts to support GPUs with larger memory capacity or add additional GPUs to each host. This is correct because the esxtop data shows a GPU memory bottleneck—memory utilization is above 95% with high GPU mem wait times, while CPU utilization remains low—indicating that the vGPU profiles are exhausting physical GPU memory before reaching compute limits. On the VCP-DCV exam, this scenario tests your ability to differentiate between GPU compute and GPU memory bottlenecks in Horizon VDI, a common trap where candidates mistakenly adjust vCPU or RAM settings instead of addressing the physical GPU resource. Remember that vGPU profiles consume both compute slices and dedicated memory; when wait times spike for memory, the fix is always more physical GPU memory, not more CPU. A useful memory tip: “Memory waits mean memory gates”—if the scheduler reports high GPU mem wait, you need larger or additional GPUs.
VCP-DCV vSphere Performance and Scaling Practice Question
This VCP-DCV practice question tests your understanding of vsphere performance and scaling. 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 vSphere administrator manages a cluster for a VDI workload using VMware Horizon. Each virtual desktop runs a GPU-intensive application and is assigned a vGPU profile (profile: grid_m60-1q) with 4 vCPUs and 8 GB RAM. The ESXi hosts are equipped with NVIDIA M60 GPUs (each host has 2 GPUs, each with 2 physical GPUs? Actually M60 has 2 GPUs on one card, but let's keep generic). The administrator receives complaints of poor graphics performance and high latency. The administrator runs esxtop and observes that the total CPU utilization for the hosts is low (average 30%), but the GPU memory utilization is consistently above 95%, and the vGPU scheduler reports high 'GPU mem' wait times. The number of VMs per host is within the GPU profile limits. What is the most effective way to improve performance?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Upgrade the hosts to support GPUs with larger memory capacity or add additional GPUs to each host.
The bottleneck is GPU memory, not CPU. The most effective solution is to upgrade to GPUs with higher memory capacity or add more GPUs. Option D directly addresses this. Option A would increase GPU memory per VM but reduce the total number of VMs, possibly not needed. Option B might not help. Option C could reduce GPU load but at the cost of user experience.
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.
✗
Change the vGPU profile to a larger profile (e.g., grid_m60-2q) for all VMs.
Why it's wrong here
This would allocate more GPU memory per VM, but may exceed GPU capacity and is not the best first step.
✗
Increase the CPU reservation for each VDI VM.
Why it's wrong here
CPU resources are not the bottleneck; GPU memory is.
✗
Reduce the number of vCPUs per VM from 4 to 2.
Why it's wrong here
Reducing vCPUs may affect application performance and does not address GPU memory contention.
✓
Upgrade the hosts to support GPUs with larger memory capacity or add additional GPUs to each host.
Why this is correct
Increasing GPU memory capacity directly resolves the memory contention bottleneck.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
Use explanations to understand the rule behind the answer.
TExam Day Tips
→Underline the problem statement mentally.
→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 practitioner preparing for the VCP-DCV exam encounters this exact type of scenario on the job. The correct answer here is not the most general option — it is the best answer for the specific constraint described. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Real exam questions reward reading the full scenario before eliminating options, because the constraint defines which answer fits.
What to study next
Got this wrong? Here's your next step.
Identify which VCP-DCV exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
vSphere Performance and Scaling — This question tests vSphere Performance and Scaling — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Upgrade the hosts to support GPUs with larger memory capacity or add additional GPUs to each host. — The bottleneck is GPU memory, not CPU. The most effective solution is to upgrade to GPUs with higher memory capacity or add more GPUs. Option D directly addresses this. Option A would increase GPU memory per VM but reduce the total number of VMs, possibly not needed. Option B might not help. Option C could reduce GPU load but at the cost of user experience.
What should I do if I get this VCP-DCV question wrong?
Identify which VCP-DCV exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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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