20+ practice questions focused on Workloads & Scheduling — one of the most tested topics on the Certified Kubernetes Administrator CKA exam. Each question includes a detailed explanation so you learn why the right answer is correct.
Start Workloads & Scheduling PracticeA DevOps team wants to ensure that a critical web application pod runs on a dedicated set of nodes with SSDs. Which Kubernetes feature should they use to achieve this?
Explanation: Node affinity is a Kubernetes feature that allows you to constrain which nodes a pod can be scheduled on based on node labels. By labeling nodes with SSDs (e.g., `disk-type=ssd`) and defining a `requiredDuringSchedulingIgnoredDuringExecution` node affinity rule in the pod spec, the scheduler will only place the pod on nodes matching that label, ensuring it runs on the dedicated set of nodes.
A Kubernetes cluster has a deployment with 3 replicas. After a node failure, you notice that only 2 pods are running, and the deployment has not rescheduled the missing pod. What is the most likely cause?
Explanation: When a node fails, the node controller marks the node as `NodeReady=False` and waits for a configurable timeout (`pod-eviction-timeout`, default 5 minutes) before evicting pods. Until eviction, the deployment's ReplicaSet sees the pod as still existing (though on an unreachable node) and does not create a replacement. Option C correctly identifies that the node controller has not yet evicted the pod, which is the default behavior.
You have a StatefulSet with 5 pods, each requiring a unique stable network identity. The StatefulSet is scaled down from 5 to 3. Which pods will be terminated?
Explanation: When a StatefulSet is scaled down, Kubernetes terminates pods in reverse order of their ordinal indices, starting from the highest. For a StatefulSet with 5 pods (ordinals 0-4) scaled to 3, pods with ordinals 4 and 3 are terminated first, ensuring that the remaining pods (0, 1, 2) maintain their stable network identities and storage.
An application requires that a pod runs on a node that has a GPU. The cluster has nodes with and without GPUs labeled as 'gpu=true' and 'gpu=false'. Which scheduling method should be used?
Explanation: Option D is correct because `nodeSelector` is the simplest and most direct way to force a pod to run only on nodes that have a specific label, such as `gpu=true`. This ensures the pod is scheduled exclusively on GPU-equipped nodes without requiring taints, tolerations, or complex affinity rules. The `nodeSelector` field in the pod spec matches against node labels at scheduling time, making it ideal for this straightforward requirement.
A cluster administrator wants to ensure that no pods are scheduled on the master node(s). Which approach is the best practice?
Explanation: Adding a taint to the master node(s) with the `node-role.kubernetes.io/master:NoSchedule` effect is the best practice because it prevents the Kubernetes scheduler from placing any pods on that node unless a pod explicitly tolerates the taint. This ensures that only critical system pods (which include the toleration) can run on the master, keeping it dedicated to cluster control plane operations.
+15 more Workloads & Scheduling questions available
Practice all Workloads & Scheduling questions1. Baseline your knowledge
Start with 10 questions to gauge your current understanding of Workloads & Scheduling. This tells you whether you need a concept refresher or just practice.
2. Review every explanation
For each question — right or wrong — read the full explanation. Understanding why an answer is correct is more valuable than knowing the answer itself.
3. Focus on exam traps
Workloads & Scheduling questions on the CKA frequently use trap wording. Look for subtle differences in answers that test your precision, not just general knowledge.
4. Reach 80% consistently
Do repeated sessions until you score 80%+ three times in a row. Then move to mixed-mode practice to test cross-topic recall under realistic conditions.
The exact number varies per candidate. Workloads & Scheduling is tested as part of the Certified Kubernetes Administrator CKA blueprint. Practicing with targeted Workloads & Scheduling questions ensures you can handle any format or difficulty that appears.
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Difficulty is subjective, but Workloads & Scheduling is a high-priority exam concept tested in multiple ways — direct recall, scenario analysis, and command-output interpretation. Consistent practice is the best way to build confidence.
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