CKA Troubleshooting Practice Question
You have a Pod that is stuck in Pending state. Running 'kubectl describe pod' shows events: '0/4 nodes are available: 1 node(s) had taint {node-role.kubernetes.io/control-plane: }, 3 node(s) had taint {key: value}, that the pod didn't tolerate.' How can you resolve this issue?
⚠ Common exam trap
A common misconception in the CKA exam is that removing taints from nodes is the only fix, but the correct Kubernetes approach is to add tolerations to the Pod spec, preserving node isolation for other workloads.
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 appropriate tolerations to the Pod's spec
The Pod is stuck in Pending because none of the nodes can schedule it due to taints that the Pod does not tolerate. Option D is correct because adding the appropriate tolerations to the Pod's spec tells the scheduler that the Pod can tolerate those taints, allowing it to be scheduled on the tainted nodes. This directly addresses the mismatch between node taints and Pod tolerations. A common misconception in the CKA exam is that removing taints from nodes is the only fix, but the correct Kubernetes approach is to add tolerations to the Pod spec, preserving node isolation for other workloads.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Increase the Pod's resource requests
Why it's wrong here
Increasing a Pod's CPU or memory requests will actually make it harder to schedule, as it requires nodes with more allocatable capacity. It does nothing to resolve scheduling blocks caused by taints and tolerations. If a node has a taint that the Pod does not tolerate, the scheduler will reject it regardless of how many resources are requested.
- ✗
Remove the taints from all nodes using 'kubectl taint nodes --all key:value-'
Why it's wrong here
While removing taints from all nodes would allow the Pod to schedule, this is an unsafe and overly broad administrative action. Taints are typically placed on nodes to dedicate them to specific workloads, such as GPU-heavy tasks or system control plane components. Stripping these taints globally can cause unintended workloads to flood these specialized nodes, disrupting cluster-wide resource isolation.
- ✗
Delete the Pod and recreate it with a different name
Why it's wrong here
Simply renaming a Pod does not alter its underlying manifest or configuration. The Kubernetes scheduler evaluates scheduling decisions based on the Pod's spec, specifically looking for matching tolerations to bypass node taints. Recreating the Pod with a new name but the same specification will result in the same pending state because the scheduling constraints remain completely unchanged.
- ✓
Add appropriate tolerations to the Pod's spec
Why this is correct
Adding matching tolerations to the Pod's specification directly instructs the kube-scheduler that this Pod is allowed to run on nodes with corresponding taints. This is the standard, least-privilege method to resolve scheduling issues on tainted nodes without compromising the cluster's overall node isolation strategy. Once the toleration is applied, the scheduler can successfully bind the Pod to the tainted node.
Visual reference
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Related to this question
Learn chapter
Kubernetes Architecture Overview
Key term
Container Runtime
A container runtime is software that runs containers by using the host operating system's kernel to isolate processes, manage filesystem layers, and handle networking.
Key term
Ingress Resources
Ingress Resources are Kubernetes API objects that manage external access to services inside a cluster, typically HTTP and HTTPS traffic, by defining rules for routing requests based on hostnames and paths.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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.