CKA Workloads & Scheduling Practice Question
Which THREE of the following are valid considerations when using resource requests and limits? (Select 3)
⚠ Common exam trap
Candidates often confuse CPU limits as a guarantee of CPU allocation, when in fact CPU is compressible and limits only throttle usage, while memory limits are hard and can cause OOM kills.
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
✓
Requests are used by the scheduler to decide which node can accommodate the Pod.
The Kubernetes scheduler uses resource requests (CPU and memory) to determine node suitability for a Pod. The scheduler checks if the sum of requests for all Pods on a node, plus the new Pod's requests, is less than or equal to the node's allocatable capacity. Limits are not used for scheduling decisions.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Limits must be equal to requests for a Pod to be scheduled.
Why it's wrong here
Equality of limits and requests is not a scheduling condition. The scheduler chooses nodes based on the sum of container requests compared to node allocatable resources, while limits are only enforced after the Pod runs. Only Guaranteed QoS requires equal requests and limits across all containers; Burstable and BestEffort Pods can have requests lower than limits or no limits at all.
- ✓
Requests are used by the scheduler to decide which node can accommodate the Pod.
Why this is correct
During scheduling, kube-scheduler evaluates each candidate node by subtracting the sum of container requests for CPU and memory from the node's allocatable capacity. A node is deemed feasible only if it can satisfy all requested quantities, because requests represent the minimum resource reservation needed to run the Pod. Limits are deliberately ignored in this admission calculation, making requests the primary input for node fit decisions.
- ✗
CPU limits guarantee the Pod will get that amount of CPU.
Why it's wrong here
CPU limits are a ceiling, not an allocation guarantee. Since CPU is a compressible resource, a container that exceeds its limit is throttled at the cgroup level, reducing its scheduling slices, rather than being provisioned additional CPU. The actual resources the Pod receives depend on node contention and how the scheduler places it based on requests, so a limit never ensures a fixed amount of CPU.
- ✓
The QoS class is determined based on requests and limits.
Why this is correct
Kubernetes classifies a Pod's QoS class by comparing requests and limits set for every container in the Pod. If all containers specify equal requests and limits for both CPU and memory, the class is Guaranteed; if any container's request or limit differs, it is Burstable; if no resources are specified at all, it is BestEffort. This class determines how the kubelet ranks Pods for eviction and OOM score adjustments under memory pressure.
- ✓
Memory limits can cause the Pod to be OOMKilled if exceeded.
Why this is correct
Memory is incompressible, so the kernel enforces a memory limit as a hard cgroup cap. When a container's memory usage exceeds that cap, the OOM killer is triggered and terminates a process with the highest OOM score, often resulting in the entire Pod being restart. This is fundamentally different from CPU throttling because the limit breach causes termination, not just reduced performance.
Go deeper
Related to this question
Learn chapter
Kubernetes Architecture Overview
Key term
Network Policies
A Kubernetes resource that controls how pods communicate with each other and with other network endpoints, acting as a firewall for pod-to-pod traffic.
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.
About these practice questions
Courseiva writes every CKA question from scratch — 302 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
JA
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.