- A
Set higher memory limits on the Pods being evicted
Why wrong: Higher memory limits allow Pods to use more memory, which may increase node memory pressure — not a fix for eviction caused by missing requests.
- B
Add explicit memory requests (and optionally limits) to all Pod specs
Pods without requests have BestEffort QoS and are evicted first. Setting memory requests elevates Pods to Burstable QoS. Matching requests and limits creates Guaranteed QoS — the most eviction-resistant class.
- C
Disable node-level eviction by modifying kubelet configuration
Why wrong: Disabling eviction lets nodes run out of memory and crash — eviction is a safety mechanism. The fix is sizing Pods correctly.
- D
Add more nodes to the cluster to increase available memory
Why wrong: Adding nodes helps capacity, but doesn't fix the root cause — Pods without requests can continue to consume unbounded memory, causing the same issue on the new nodes.
Quick Answer
The answer is to add explicit memory requests and optionally limits to all Pod specs. This is the correct long-term fix for GKE pod eviction under memory pressure because without resource requests, Pods are classified as BestEffort or Burstable under Kubernetes’ Quality of Service (QoS) classes, making them the first to be evicted by the kubelet when node memory hits 98%. By defining memory requests, you give the scheduler the data it needs to place Pods only on nodes with sufficient available memory, preventing overcommitment at the scheduling level rather than just reacting to evictions. On the Google Associate Cloud Engineer exam, this scenario tests your understanding of Kubernetes resource management and QoS tiers—a common trap is choosing a short-term fix like increasing node size or adding more replicas, which doesn’t address the root cause of missing requests. Memory tip: “No request means no rest”—Pods without requests are always first to be evicted under pressure.
Google ACE Practice Question: Ensuring successful operation of a cloud solution
This ACE practice question tests your understanding of ensuring successful operation of a cloud solution. 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 monitoring alert fires at 3 AM — the team's GKE Pods are being evicted. Investigation shows node memory is at 98%. Pods without resource requests are being evicted first. What is the long-term fix to prevent evictions?
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
Add explicit memory requests (and optionally limits) to all Pod specs
B is correct because setting explicit memory requests ensures the Kubernetes scheduler can accurately place Pods on nodes with sufficient resources, preventing the node from being overcommitted. Without requests, Pods are treated as burstable or best-effort, making them the first candidates for eviction under the kubelet's Quality of Service (QoS) classes when node memory pressure hits 98%. This is a long-term fix because it enforces proper resource governance at the scheduling level, not just a reactive measure.
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 higher memory limits on the Pods being evicted
Why it's wrong here
Higher memory limits allow Pods to use more memory, which may increase node memory pressure — not a fix for eviction caused by missing requests.
- ✓
Add explicit memory requests (and optionally limits) to all Pod specs
Why this is correct
Pods without requests have BestEffort QoS and are evicted first. Setting memory requests elevates Pods to Burstable QoS. Matching requests and limits creates Guaranteed QoS — the most eviction-resistant class.
Clue confirmation
The clue word "first" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Disable node-level eviction by modifying kubelet configuration
Why it's wrong here
Disabling eviction lets nodes run out of memory and crash — eviction is a safety mechanism. The fix is sizing Pods correctly.
- ✗
Add more nodes to the cluster to increase available memory
Why it's wrong here
Adding nodes helps capacity, but doesn't fix the root cause — Pods without requests can continue to consume unbounded memory, causing the same issue on the new nodes.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the misconception that raising limits or adding capacity is the fix, but the real issue is the absence of requests, which prevents the scheduler from making informed placement decisions and leaves Pods in the lowest QoS class.
Detailed technical explanation
How to think about this question
Kubernetes assigns QoS classes based on resource specifications: Guaranteed (requests == limits for all resources), Burstable (requests < limits or requests set without limits), and BestEffort (no requests or limits). BestEffort Pods are evicted first under memory pressure, followed by Burstable Pods exceeding their requests. The kubelet uses the oom_score_adj mechanism (values from -998 to 1000) to prioritize eviction, with BestEffort Pods receiving the highest score (1000), making them the first to be killed. In a real-world scenario, a team might see recurring evictions at 3 AM due to a batch job with no requests, and simply adding nodes would not fix the root cause—the lack of resource declarations.
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 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. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. 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.
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?
Ensuring successful operation of a cloud solution — This question tests Ensuring successful operation of a cloud solution — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Add explicit memory requests (and optionally limits) to all Pod specs — B is correct because setting explicit memory requests ensures the Kubernetes scheduler can accurately place Pods on nodes with sufficient resources, preventing the node from being overcommitted. Without requests, Pods are treated as burstable or best-effort, making them the first candidates for eviction under the kubelet's Quality of Service (QoS) classes when node memory pressure hits 98%. This is a long-term fix because it enforces proper resource governance at the scheduling level, not just a reactive measure.
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 →
Same concept, more angles
1 more ways this is tested on ACE
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. 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?
medium- ✓ A.Set memory requests and limits for all pods to match their actual memory usage.
- B.Increase the node machine type to have more memory.
- C.Configure pod disruption budgets (PDBs) to prevent eviction.
- D.Enable cluster autoscaler to add nodes before memory pressure occurs.
Why A: 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.
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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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