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.
An application running on GKE experiences high tail latency. The team is optimizing performance. Which THREE techniques should they consider? (Choose three.)
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Use pod anti-affinity to spread pods across nodes
Pod anti-affinity spreads pods across different nodes, reducing the risk of a single node becoming a hotspot and causing contention for resources like CPU, memory, or network bandwidth. By distributing pods, you minimize queuing delays and improve tail latency, as no single node is overloaded with too many pods competing for the same resources.
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.
✓
Use pod anti-affinity to spread pods across nodes
Why this is correct
Spread reduces resource competition and improves performance.
Related concept
Read the scenario before looking for a memorised answer.
✓
Set proper resource requests and limits to avoid resource contention
Why this is correct
Resource limits prevent any single pod from monopolizing node resources.
Related concept
Read the scenario before looking for a memorised answer.
✗
Enable Istio sidecar injection for all pods
Why it's wrong here
Istio sidecars add network overhead, which can increase tail latency.
Increase the number of replicas for stateless services
Why this is correct
More replicas distribute load and reduce latency for each request.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the misconception that packing pods together (affinity) improves performance by reducing network hops, but in practice, it increases contention and tail latency, while anti-affinity spreads load and improves predictability.
Detailed technical explanation
How to think about this question
Under the hood, pod anti-affinity uses the `podAntiAffinity` field in the pod spec with `requiredDuringSchedulingIgnoredDuringExecution` to enforce hard constraints, or `preferredDuringSchedulingIgnoredDuringExecution` for soft spreading. In real-world scenarios, this is critical for stateful workloads like databases or caching layers (e.g., Redis, Cassandra) where node-level failures or resource starvation directly impact p99 latency.
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 startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
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: Use pod anti-affinity to spread pods across nodes — Pod anti-affinity spreads pods across different nodes, reducing the risk of a single node becoming a hotspot and causing contention for resources like CPU, memory, or network bandwidth. By distributing pods, you minimize queuing delays and improve tail latency, as no single node is overloaded with too many pods competing for the same resources.
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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