KCNA Kubernetes Fundamentals Practice Question
A pod is in 'Pending' state for a long time. What is the most likely cause?
⚠ Common exam trap
CNCF often tests the distinction between scheduling failures (Pending) and runtime failures (CrashLoopBackOff, ImagePullBackOff), so the trap here is confusing a pod that cannot be placed on a node with a pod that fails after it starts running.
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
✓
The scheduler cannot find a node that satisfies the pod's resource requests or constraints
A pod remains in 'Pending' state when it has been accepted by the API server but cannot be scheduled onto a node. The most common cause is that the scheduler cannot find a node that meets the pod's resource requests (CPU/memory) or constraints (node selectors, affinity rules, taints/tolerations). Until a suitable node is found, the pod stays in Pending, waiting for scheduling.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The pod's container has crashed
Why it's wrong here
A crash would result in 'CrashLoopBackOff', not 'Pending'.
- ✗
The pod's service endpoint is misconfigured
Why it's wrong here
Service configuration does not affect pod scheduling.
- ✓
The scheduler cannot find a node that satisfies the pod's resource requests or constraints
Why this is correct
If no node meets the pod's requirements, the pod remains unscheduled.
- ✗
The container image is invalid
Why it's wrong here
An invalid image would cause an error when the container runtime tries to pull it, typically resulting in 'ImagePullBackOff'.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This KCNA 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 KCNA exam.