PCDOE Optimizing service performance Practice Question
This PCDOE practice question tests your understanding of optimizing service performance. 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.
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Enable cluster autoscaler to scale up new nodes
When a GKE node reports a MemoryPressure condition, it means the node's kubelet is actively evicting pods to free memory, which degrades performance. Enabling cluster autoscaler allows the cluster to automatically provision new nodes when existing nodes are under memory pressure, redistributing pods and alleviating the condition without manual intervention.
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.
✓
Enable cluster autoscaler to scale up new nodes
Why this is correct
Cluster autoscaler adds nodes when pod is unschedulable due to memory pressure, distributing load.
Related concept
Read the scenario before looking for a memorised answer.
✗
Increase the node's memory by changing the machine type
Why it's wrong here
Changing machine type requires creating a new node pool and migrating workloads; not immediate.
✗
Adjust pod resource requests to leave more allocatable memory
Why it's wrong here
Requests affect scheduling but do not free memory on a running node.
✗
Evict pods and delete the node
Why it's wrong here
This is disruptive and does not prevent recurrence.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the misconception that MemoryPressure can be resolved by modifying pod requests or node size, when the correct automated solution is cluster autoscaler to add capacity dynamically.
Detailed technical explanation
How to think about this question
MemoryPressure is triggered when the node's memory usage exceeds the kubelet's eviction threshold (default: 100MiB or 5% of capacity, whichever is smaller). The cluster autoscaler works by monitoring pending pods and scaling up nodes via the Google Compute Engine API, but it does not react directly to MemoryPressure; instead, it scales when pods are unschedulable due to resource constraints. In practice, enabling cluster autoscaler with a proper node pool configuration ensures that new nodes are added before memory pressure causes pod evictions, maintaining 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.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Optimizing service performance — This question tests Optimizing service performance — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Enable cluster autoscaler to scale up new nodes — When a GKE node reports a MemoryPressure condition, it means the node's kubelet is actively evicting pods to free memory, which degrades performance. Enabling cluster autoscaler allows the cluster to automatically provision new nodes when existing nodes are under memory pressure, redistributing pods and alleviating the condition without manual intervention.
What should I do if I get this PCDOE 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.
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Question Discussion
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