- A
Add a toleration for 'arch=amd64:NoSchedule' to the Pod.
Why wrong: Tolerations allow scheduling on tainted nodes, but the taint would need to be on non-amd64 nodes, which is not described.
- B
Add a label 'kubernetes.io/arch: amd64' to all amd64 nodes and use nodeSelector.
Nodes already have the kubernetes.io/arch label; using nodeSelector with that label is correct.
- C
Use podAntiAffinity to avoid scheduling on arm64 nodes.
Why wrong: Pod anti-affinity is for Pod-to-Pod placement, not node architecture.
- D
Set a runtimeClassName for amd64 in the Pod spec.
Why wrong: RuntimeClassName specifies the runtime (e.g., gVisor), not architecture.
CKA Workloads & Scheduling Practice Question
This CKA practice question tests your understanding of workloads & scheduling. 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 team observes that a Deployment's Pods are being scheduled on nodes with different architectures (amd64 and arm64). The Deployment does not specify nodeSelector or affinity. The cluster has a mix of node pools. What is the best practice to ensure Pods only run on amd64 nodes?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"best"Why it matters: Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
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 a label 'kubernetes.io/arch: amd64' to all amd64 nodes and use nodeSelector.
Option B is correct because the recommended way to constrain Pods to nodes with a specific architecture is to label those nodes (e.g., with `kubernetes.io/arch: amd64`) and then use `nodeSelector` in the Pod spec. This ensures the scheduler only places Pods on nodes matching the label, which is a simple, declarative, and Kubernetes-native approach. The Deployment does not specify any scheduling constraints, so adding `nodeSelector` is the best practice to enforce architecture-specific placement.
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.
- ✗
Add a toleration for 'arch=amd64:NoSchedule' to the Pod.
Why it's wrong here
Tolerations allow scheduling on tainted nodes, but the taint would need to be on non-amd64 nodes, which is not described.
- ✓
Add a label 'kubernetes.io/arch: amd64' to all amd64 nodes and use nodeSelector.
Why this is correct
Nodes already have the kubernetes.io/arch label; using nodeSelector with that label is correct.
Clue confirmation
The clue word "best" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Use podAntiAffinity to avoid scheduling on arm64 nodes.
Why it's wrong here
Pod anti-affinity is for Pod-to-Pod placement, not node architecture.
- ✗
Set a runtimeClassName for amd64 in the Pod spec.
Why it's wrong here
RuntimeClassName specifies the runtime (e.g., gVisor), not architecture.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates confuse tolerations (which handle taints) with node selection (which uses labels and nodeSelector), leading them to pick Option A, even though tolerations alone do not restrict scheduling to specific architectures.
Detailed technical explanation
How to think about this question
Under the hood, `nodeSelector` is a simple label-based constraint that the kube-scheduler evaluates during predicate checks; it matches the Pod's `nodeSelector` field against node labels, which for architecture are typically set automatically by the kubelet via the `kubernetes.io/arch` label (e.g., `amd64`, `arm64`). In a mixed-architecture cluster, nodes in different pools may already have this label, so you can directly use `nodeSelector: { kubernetes.io/arch: amd64 }` without manual labeling, but the best practice is to verify and label nodes if needed. A real-world scenario is a CI/CD pipeline where arm64 nodes are cheaper but incompatible with certain binaries, making architecture pinning critical for reliability.
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 small business has 20 workstations on the 192.168.1.0/24 network and one public IP from its ISP. The router uses PAT (NAT overload) so all 20 devices share one public address using different source ports. NAT questions test whether you understand the four address terms and which direction each translation applies.
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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Workloads & Scheduling — study guide chapter
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FAQ
Questions learners often ask
What does this CKA question test?
Workloads & Scheduling — This question tests Workloads & Scheduling — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Add a label 'kubernetes.io/arch: amd64' to all amd64 nodes and use nodeSelector. — Option B is correct because the recommended way to constrain Pods to nodes with a specific architecture is to label those nodes (e.g., with `kubernetes.io/arch: amd64`) and then use `nodeSelector` in the Pod spec. This ensures the scheduler only places Pods on nodes matching the label, which is a simple, declarative, and Kubernetes-native approach. The Deployment does not specify any scheduling constraints, so adding `nodeSelector` is the best practice to enforce architecture-specific placement.
What should I do if I get this CKA 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: "best". Signals that multiple options may be partially correct. Choose the option that most directly solves the exact problem described, not the one that sounds most complete.
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 11, 2026
This CKA practice question is part of Courseiva's free CNCF 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 CKA exam.
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