- A
N2 machine family with custom vCPU and memory configuration
Why wrong: N2 custom machines support up to 896 GB memory per VM, but the memory-optimized M series is specifically designed and priced for high-memory workloads with better per-GB memory pricing.
- B
Memory-optimized (M1 or M2) machine family
M1 (m1-megamem, m1-ultramem) and M2 (m2-megamem, m2-ultramem, m2-hypermem) are purpose-built for high-memory workloads, offering configurations well above 768 GB RAM.
- C
Compute-optimized (C2) machine family
Why wrong: C2 machines are optimized for CPU-intensive workloads with high clock speeds, not for large memory configurations. C2 machines have moderate memory relative to CPU.
- D
Accelerator-optimized (A2) machine family
Why wrong: A2 machines are optimized for GPU-accelerated workloads (NVIDIA A100 GPUs). They are not designed for high-memory analytics without GPU computation.
Quick Answer
The answer is the memory-optimized M1 or M2 machine family. This is correct because these families are purpose-built for high-memory workloads like in-memory analytics, offering configurations with up to 12 TB of RAM, while standard machine types such as N2 or N1 max out at far lower memory capacities and cannot provide a 768 GB RAM instance. On the Google Associate Cloud Engineer exam, this question tests your understanding of specialized machine families and their use cases; a common trap is selecting the general-purpose N2 family, which lacks the high-memory SKUs required. Remember the key distinction: for CPU or balanced workloads, choose N-series, but for massive RAM needs like 768 GB, you must go memory-optimized. A helpful memory tip is to think “M for Memory” — M1 and M2 are your go-to when you need massive amounts of RAM.
Google ACE Planning and configuring a cloud solution Practice Question
This ACE practice question tests your understanding of planning and configuring a cloud solution. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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.
You are designing a GKE cluster for a workload that requires high-memory instances (768 GB RAM) for in-memory analytics. Standard machine types in GCP don't offer this configuration. Which machine family should you select for the node pool?
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
Memory-optimized (M1 or M2) machine family
The M1 and M2 memory-optimized machine families are specifically designed for workloads requiring large amounts of RAM, such as in-memory analytics, with configurations offering up to 12 TB of memory. Standard machine types like N2 do not provide 768 GB RAM instances, making memory-optimized families the correct choice for this high-memory requirement.
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.
- ✗
N2 machine family with custom vCPU and memory configuration
Why it's wrong here
N2 custom machines support up to 896 GB memory per VM, but the memory-optimized M series is specifically designed and priced for high-memory workloads with better per-GB memory pricing.
- ✓
Memory-optimized (M1 or M2) machine family
Why this is correct
M1 (m1-megamem, m1-ultramem) and M2 (m2-megamem, m2-ultramem, m2-hypermem) are purpose-built for high-memory workloads, offering configurations well above 768 GB RAM.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Compute-optimized (C2) machine family
Why it's wrong here
C2 machines are optimized for CPU-intensive workloads with high clock speeds, not for large memory configurations. C2 machines have moderate memory relative to CPU.
- ✗
Accelerator-optimized (A2) machine family
Why it's wrong here
A2 machines are optimized for GPU-accelerated workloads (NVIDIA A100 GPUs). They are not designed for high-memory analytics without GPU computation.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the misconception that custom machine types (like N2) can be scaled arbitrarily for memory, but GCP imposes hard limits on custom configurations (e.g., max 624 GB for N2), making memory-optimized families the only viable option for RAM-intensive workloads like 768 GB in-memory analytics.
Detailed technical explanation
How to think about this question
Memory-optimized M1 and M2 machines use Intel Xeon Scalable processors with up to 12 TB of RAM (M2) and are optimized for memory bandwidth and capacity, supporting large in-memory databases like SAP HANA. Under the hood, these machines employ a higher memory-to-vCPU ratio (e.g., M2-ultramem-208 offers 208 vCPUs and 5.88 TB RAM), which is critical for analytics workloads that require massive datasets to be held entirely in RAM for sub-second query performance. In real-world scenarios, choosing the wrong family can lead to out-of-memory errors or excessive swapping, severely degrading performance.
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
An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.
What to study next
Got this wrong? Here's your next step.
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FAQ
Questions learners often ask
What does this ACE question test?
Planning and configuring a cloud solution — This question tests Planning and configuring a cloud solution — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Memory-optimized (M1 or M2) machine family — The M1 and M2 memory-optimized machine families are specifically designed for workloads requiring large amounts of RAM, such as in-memory analytics, with configurations offering up to 12 TB of memory. Standard machine types like N2 do not provide 768 GB RAM instances, making memory-optimized families the correct choice for this high-memory requirement.
What should I do if I get this ACE 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 →
Last reviewed: Jun 30, 2026
This ACE 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 ACE exam.
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