- A
Set memory requests and limits for all pods to match their actual memory usage.
Pods with requests are classified as Burstable (or Guaranteed if limits equal requests). These are evicted after BestEffort pods. Proper requests also help the scheduler distribute pods evenly, reducing node pressure.
- B
Increase the node machine type to have more memory.
Why wrong: Larger nodes reduce pressure temporarily but don't fix the root cause: pods without requests still have BestEffort QoS and will be evicted first under any memory pressure.
- C
Configure pod disruption budgets (PDBs) to prevent eviction.
Why wrong: PDBs protect against voluntary disruptions (like node drain), not kubelet-initiated evictions due to memory pressure. OOM-based evictions ignore PDBs.
- D
Enable cluster autoscaler to add nodes before memory pressure occurs.
Why wrong: Cluster autoscaler adds nodes when pods are unschedulable, not when pods are running but under memory pressure. It doesn't prevent eviction of running pods.
Google ACE Practice Question: Your GKE application's pods are being evicted…
This ACE practice question tests your understanding of ace exam topics. 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.
Your GKE application's pods are being evicted frequently during periods of high traffic. You notice that pods without resource requests are being evicted first. The nodes are running at ~85% memory utilization. What should you do to reduce pod eviction?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"first"Why it matters: Order matters here. You are being tested on which action comes before the others — not which action is generally useful.
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
Set memory requests and limits for all pods to match their actual memory usage.
Setting memory requests and limits for all pods to match their actual memory usage ensures that the Kubernetes scheduler can accurately allocate resources and make informed scheduling decisions. Without requests, pods are treated as BestEffort QoS class, making them the first candidates for eviction under memory pressure (when nodes exceed ~85% utilization). By defining requests, pods are classified as Burstable or Guaranteed, which gives them higher priority during eviction and prevents unnecessary disruptions.
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.
- ✓
Set memory requests and limits for all pods to match their actual memory usage.
Why this is correct
Pods with requests are classified as Burstable (or Guaranteed if limits equal requests). These are evicted after BestEffort pods. Proper requests also help the scheduler distribute pods evenly, reducing node pressure.
Clue confirmation
The clue word "first" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Increase the node machine type to have more memory.
Why it's wrong here
Larger nodes reduce pressure temporarily but don't fix the root cause: pods without requests still have BestEffort QoS and will be evicted first under any memory pressure.
- ✗
Configure pod disruption budgets (PDBs) to prevent eviction.
Why it's wrong here
PDBs protect against voluntary disruptions (like node drain), not kubelet-initiated evictions due to memory pressure. OOM-based evictions ignore PDBs.
- ✗
Enable cluster autoscaler to add nodes before memory pressure occurs.
Why it's wrong here
Cluster autoscaler adds nodes when pods are unschedulable, not when pods are running but under memory pressure. It doesn't prevent eviction of running pods.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the misconception that increasing node resources or adding nodes (autoscaling) solves eviction, when the real issue is the lack of resource requests that determines eviction priority under memory pressure.
Detailed technical explanation
How to think about this question
Under the hood, the kubelet uses the OOM score adjuster and eviction signals (e.g., memory.available) to rank pods by QoS class: BestEffort (no requests/limits) are killed first, then Burstable (requests < limits), and finally Guaranteed (requests == limits). In practice, setting requests to match actual usage also prevents CPU throttling and improves node utilization predictability, which is critical for maintaining SLOs in production clusters.
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.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Questions learners often ask
What does this ACE question test?
Read the scenario before looking for a memorised answer.
What is the correct answer to this question?
The correct answer is: Set memory requests and limits for all pods to match their actual memory usage. — Setting memory requests and limits for all pods to match their actual memory usage ensures that the Kubernetes scheduler can accurately allocate resources and make informed scheduling decisions. Without requests, pods are treated as BestEffort QoS class, making them the first candidates for eviction under memory pressure (when nodes exceed ~85% utilization). By defining requests, pods are classified as Burstable or Guaranteed, which gives them higher priority during eviction and prevents unnecessary disruptions.
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.
Are there clue words in this question I should notice?
Yes — watch for: "first". Order matters here. You are being tested on which action comes before the others — not which action is generally useful.
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 →
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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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