- A
Increase the target CPU utilization to 90% to allow more requests per instance.
Why wrong: Higher utilization may cause overload, worsening errors.
- B
Switch to a machine type with more memory, e.g., n1-highmem-8, and increase min_replica_count.
High memory instances reduce memory contention, and more replicas absorb traffic spikes.
- C
Enable canary traffic splitting to reduce load on the main endpoint.
Why wrong: Canary deployment doesn't directly handle spikes; it's for rollout.
- D
Reduce the model batch size from 32 to 1 to lower memory per request.
Why wrong: Smaller batch size increases CPU overhead per request and may not resolve 502s if memory is insufficient.
Quick Answer
The answer is to switch to a machine type with more memory, like n1-highmem-8, and increase min_replica_count. This resolves the intermittent 502 errors because Vertex AI endpoints return 502s when instances are overwhelmed or timing out, often due to memory pressure during traffic spikes—the CPU utilization target of 60% doesn’t prevent memory exhaustion on standard instances. On the Google Professional Machine Learning Engineer exam, this tests your understanding of autoscaling and resource allocation for large language models; a common trap is focusing on CPU or GPU when the bottleneck is memory, not compute. Remember the mnemonic “High Mem, More Replicas” to avoid chasing the wrong metric.
PMLE Serving and scaling models Practice Question
This PMLE practice question tests your understanding of serving and scaling models. 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.
Your team is serving a large language model on Vertex AI using a custom container. The endpoint experiences intermittent 502 errors during traffic spikes. The autoscaling configuration uses a CPU utilization target of 60% and the model is deployed on n1-standard-4 instances. The model requires significant memory. Which combination of changes is most likely to resolve the issue?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"most likely"Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
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
Switch to a machine type with more memory, e.g., n1-highmem-8, and increase min_replica_count.
The 502 errors likely indicate the instances are overwhelmed or timing out. Increasing the machine type to a high-memory instance reduces memory pressure, and adding more replicas through a lower target scaling metric or higher min replicas provides capacity. Tuning batch size helps but is secondary. GPU may not help if the issue is memory.
Key principle: NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
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 target CPU utilization to 90% to allow more requests per instance.
Why it's wrong here
Higher utilization may cause overload, worsening errors.
- ✓
Switch to a machine type with more memory, e.g., n1-highmem-8, and increase min_replica_count.
Why this is correct
High memory instances reduce memory contention, and more replicas absorb traffic spikes.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Static NAT maps one inside address to one outside address.
- ✗
Enable canary traffic splitting to reduce load on the main endpoint.
Why it's wrong here
Canary deployment doesn't directly handle spikes; it's for rollout.
- ✗
Reduce the model batch size from 32 to 1 to lower memory per request.
Why it's wrong here
Smaller batch size increases CPU overhead per request and may not resolve 502s if memory is insufficient.
Common exam traps
Common exam trap: NAT rules depend on direction and matching traffic
NAT is not only about the public address. The inside/outside interface roles and the ACL or rule that matches traffic are just as important.
Detailed technical explanation
How to think about this question
NAT questions usually test address translation, overload/PAT behaviour, static mappings and whether the right traffic is being translated. Read the interface direction and address terms carefully.
KKey Concepts to Remember
- Static NAT maps one inside address to one outside address.
- PAT allows many inside hosts to share one public address using ports.
- Inside local and inside global describe the private and translated addresses.
- NAT ACLs identify traffic for translation, not always security filtering.
TExam Day Tips
- Identify inside and outside interfaces first.
- Check whether the scenario needs static NAT, dynamic NAT or PAT.
- Do not confuse NAT matching ACLs with normal packet-filtering intent.
Key takeaway
NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated.
Real-world example
How this comes up in practice
A cloud solutions architect for a retail company is evaluating services for a new workload. The correct answer here reflects best practice for the specific scenario described — not a general cloud recommendation. NAT direction and interface roles matter as much as the IP address mapping. Inside/outside designation controls which traffic is translated. Cloud exam questions reward reading the constraint carefully: the same technology can be right or wrong depending on the use case.
What to study next
Got this wrong? Here's your next step.
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related PMLE NAT questions on configuration and troubleshooting.
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Serving and scaling models — study guide chapter
Learn the concepts, then practise the questions
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Serving and scaling models practice questions
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FAQ
Questions learners often ask
What does this PMLE question test?
Serving and scaling models — This question tests Serving and scaling models — Static NAT maps one inside address to one outside address..
What is the correct answer to this question?
The correct answer is: Switch to a machine type with more memory, e.g., n1-highmem-8, and increase min_replica_count. — The 502 errors likely indicate the instances are overwhelmed or timing out. Increasing the machine type to a high-memory instance reduces memory pressure, and adding more replicas through a lower target scaling metric or higher min replicas provides capacity. Tuning batch size helps but is secondary. GPU may not help if the issue is memory.
What should I do if I get this PMLE question wrong?
Review the four NAT address types (inside local, inside global, outside local, outside global), PAT port overload, and static vs dynamic NAT use cases. Then practise related PMLE NAT questions on configuration and troubleshooting.
Are there clue words in this question I should notice?
Yes — watch for: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
What is the key concept behind this question?
Static NAT maps one inside address to one outside address.
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Last reviewed: Jun 24, 2026
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