CKA Troubleshooting Practice Question
You are troubleshooting a pod that is in 'Pending' state. 'kubectl describe pod' shows '0/1 nodes are available: 1 Insufficient memory, 1 node(s) had taint {node-role.kubernetes.io/control-plane: }, that the pod didn't tolerate'. Which TWO actions can resolve the issue?
⚠ Common exam trap
In a single-node cluster (indicated by '0/1 nodes are available'), any scheduling failure message lists all reasons why that single node failed. You must resolve all listed constraints (both the taint and the resource insufficiency) for the pod to schedule.
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
✓
Reduce the memory request in the container spec to fit available memory
The pod is pending because the single node in the cluster (0/1 nodes available) has two blocking issues: 1) Insufficient memory to satisfy the pod's request, and 2) a control-plane taint that the pod does not tolerate. To resolve this and allow the pod to schedule on this node, both issues must be addressed: you must reduce the memory request in the container spec to fit the available memory (Option A) AND add a toleration for the control-plane taint to the pod spec (Option E).
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Reduce the memory request in the container spec to fit available memory
Why this is correct
The scheduler reports Insufficient memory, meaning no node has enough allocatable memory for the pod's request. Lowering the container's memory request brings it within available capacity, allowing the scheduler to bind the pod to a suitable node.
- ✗
Add a node selector to the pod spec to target a specific node
Why it's wrong here
A node selector narrows placement to labelled nodes, and the only candidate already fails on memory and taints, so it cannot resolve Pending. It is tempting because selectors steer scheduling, and it would be correct when the pod must land on nodes with particular hardware, zone or topology labels.
- ✗
Increase the memory request to prioritize scheduling
Why it's wrong here
Raising the memory request increases the scheduler's demand, so the node reporting Insufficient memory rejects the pod even harder. It is tempting because requests drive scheduling decisions, and it would be correct when the pod is being evicted or throttled after placement, not when no node can satisfy its current request.
- ✗
Add resource limits without changing requests
Why it's wrong here
Limits cap runtime consumption and are not consulted by the scheduler, so adding them leaves the Insufficient memory rejection unchanged. It is tempting because limits and requests appear together in the same resource block, and it would be correct when a running container needs bounding to protect node stability.
- ✓
Add a toleration for the control-plane taint to the pod spec
Why this is correct
Adding a toleration matching `node-role.kubernetes.io/control-plane` lets the scheduler consider the control-plane node, which the taint currently excludes. However, the pod still requests more memory than any node offers, so toleration alone only satisfies the taint constraint; the memory shortfall must also be addressed.
Visual reference
Go deeper
Related to this question
Learn chapter
Installing Kubernetes with kubeadm
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.
Key term
kubectl Command Reference
kubectl is the command-line tool used to interact with and manage Kubernetes clusters by sending commands to the Kubernetes API.
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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.