- A
Set podAntiAffinity with requiredDuringSchedulingIgnoredDuringExecution and topologyKey: kubernetes.io/hostname
This hard anti-affinity rule prevents the scheduler from placing a Pod on a node that already runs a Pod matching the selector — guaranteeing one replica per node.
- B
Set podAffinity with requiredDuringSchedulingIgnoredDuringExecution and topologyKey: kubernetes.io/hostname
Why wrong: podAffinity attracts Pods to nodes where matching Pods already run — the opposite of the desired behavior (spreading Pods apart).
- C
Set topologySpreadConstraints with maxSkew: 1 and topologyKey: kubernetes.io/hostname
Why wrong: TopologySpreadConstraints is also valid for spreading Pods across nodes, but the question asks about the anti-affinity configuration — which is the traditional approach for hard node-exclusivity.
- D
Set nodeSelector to a specific node for each replica
Why wrong: nodeSelector pins Pods to specific nodes — it requires manual management and doesn't dynamically prevent co-location.
Quick Answer
The answer is to configure `podAntiAffinity` with `requiredDuringSchedulingIgnoredDuringExecution` and `topologyKey: kubernetes.io/hostname`. This works because the `requiredDuringScheduling` rule is a hard constraint that forces the Kubernetes scheduler to place each new pod on a node where no other pod from the same selector is already running, using the hostname topology key to distinguish nodes. On the Google Associate Cloud Engineer exam, this question tests your understanding of pod scheduling policies for high availability—a common trap is choosing `preferredDuringScheduling`, which is a soft rule that can be ignored under resource pressure, or using a different topology key like `zone`. Remember that `required` means mandatory, `hostname` means per-node, and together they guarantee one replica per node. A quick memory tip: think "Rigid Host Anti-Affinity" to recall that a Required rule on the Host topology key prevents pod colocation.
Google ACE Deploying and implementing a cloud solution Practice Question
This ACE practice question tests your understanding of deploying and implementing a cloud solution. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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 GKE Deployment runs a web application with 6 replicas across a 3-node cluster. To ensure no two replicas land on the same node (maximizing availability), which Pod spec configuration should be applied?
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 podAntiAffinity with requiredDuringSchedulingIgnoredDuringExecution and topologyKey: kubernetes.io/hostname
Option A is correct because `podAntiAffinity` with `requiredDuringSchedulingIgnoredDuringExecution` and `topologyKey: kubernetes.io/hostname` forces the scheduler to place each replica on a different node. This ensures that no two pods of the same Deployment run on the same Kubernetes node, maximizing availability by preventing a single node failure from taking down more than one replica.
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 podAntiAffinity with requiredDuringSchedulingIgnoredDuringExecution and topologyKey: kubernetes.io/hostname
Why this is correct
This hard anti-affinity rule prevents the scheduler from placing a Pod on a node that already runs a Pod matching the selector — guaranteeing one replica per node.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Set podAffinity with requiredDuringSchedulingIgnoredDuringExecution and topologyKey: kubernetes.io/hostname
Why it's wrong here
podAffinity attracts Pods to nodes where matching Pods already run — the opposite of the desired behavior (spreading Pods apart).
- ✗
Set topologySpreadConstraints with maxSkew: 1 and topologyKey: kubernetes.io/hostname
Why it's wrong here
TopologySpreadConstraints is also valid for spreading Pods across nodes, but the question asks about the anti-affinity configuration — which is the traditional approach for hard node-exclusivity.
- ✗
Set nodeSelector to a specific node for each replica
Why it's wrong here
nodeSelector pins Pods to specific nodes — it requires manual management and doesn't dynamically prevent co-location.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the distinction between `podAffinity` and `podAntiAffinity` — the trap here is that candidates confuse the two, or assume `topologySpreadConstraints` provides the same hard guarantee as anti-affinity, when it only enforces even distribution, not strict separation.
Detailed technical explanation
How to think about this question
Under the hood, `requiredDuringSchedulingIgnoredDuringExecution` is a hard constraint that the scheduler enforces at pod creation time; if no node satisfies the anti-affinity rule, the pod remains unscheduled (Pending). The `topologyKey: kubernetes.io/hostname` uses the node's hostname label to define the failure domain, ensuring each pod is placed on a distinct node. In a real-world scenario, if you have 6 replicas but only 3 nodes, the 4th replica will remain unscheduled, which is a critical behavior to understand for capacity planning.
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
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FAQ
Questions learners often ask
What does this ACE question test?
Deploying and implementing a cloud solution — This question tests Deploying and implementing a cloud solution — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Set podAntiAffinity with requiredDuringSchedulingIgnoredDuringExecution and topologyKey: kubernetes.io/hostname — Option A is correct because `podAntiAffinity` with `requiredDuringSchedulingIgnoredDuringExecution` and `topologyKey: kubernetes.io/hostname` forces the scheduler to place each replica on a different node. This ensures that no two pods of the same Deployment run on the same Kubernetes node, maximizing availability by preventing a single node failure from taking down more than one replica.
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.
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 →
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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