KCNA Kubernetes Fundamentals Practice Question
Which TWO of the following are benefits of using a Deployment over managing ReplicaSets directly? (Choose two.)
⚠ Common exam trap
A common misconception is that Deployments are suitable for stateful workloads or provide direct pod networking, when in fact StatefulSets and Services are the correct solutions for those needs.
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
✓
Declarative scaling
Option B (Declarative scaling) is correct because a Deployment declares the desired replica count in its spec (spec.replicas), and the Deployment controller continuously reconciles the actual number of pods to match that declared state, so scaling is expressed declaratively rather than by manually editing a ReplicaSet. Option D (Automatic rolling updates and rollbacks) is correct because Deployments manage ReplicaSets under the hood to perform rolling updates via spec.strategy (RollingUpdate with maxSurge/maxUnavailable) and preserve revision history (spec.revisionHistoryLimit) so that kubectl rollout undo can roll back to a previous ReplicaSet. Option A is incorrect because stateful workloads requiring stable identities and persistent per-pod storage are handled by StatefulSets, not Deployments. Option C is incorrect because pod IP addresses are a function of the cluster network (e.g., CNI-assigned IPs) and are not a Deployment-specific benefit; direct pod access is generally discouraged in favor of Services. Option E is incorrect because running one pod on every node is the purpose of a DaemonSet, not a Deployment.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Support for stateful workloads
Why it's wrong here
Deployments manage stateless pods; StatefulSets provide stable network identities and persistent volume claims per replica, which Deployments lack. Stateful workloads such as databases need those guarantees, so StatefulSets would be the correct choice there. Deployments instead add rolling updates and rollback across ReplicaSets.
- ✓
Declarative scaling
Why this is correct
A Deployment's spec.replicas field lets you declare the desired pod count, and the Deployment controller reconciles ReplicaSets to match it. Managing ReplicaSets directly requires manual scaling of each set, so declarative scaling is a genuine Deployment benefit.
- ✗
Direct access to pod IP addresses
Why it's wrong here
Direct pod IP access is a networking capability, not something a Deployment provides over a ReplicaSet — both create pods with routable IPs, so it does not distinguish them. It is tempting because direct pod addressing matters when debugging connectivity or configuring headless Services, but that scenario concerns Service types and CNI behaviour, not workload-controller choice.
- ✓
Automatic rolling updates and rollbacks
Why this is correct
Deployments automate rolling updates by creating a new ReplicaSet and shifting replicas gradually, and retain revision history so kubectl rollout undo can revert to a prior ReplicaSet. Bare ReplicaSets provide neither mechanism, making this a real advantage.
- ✗
Ability to run a pod on every node
Why it's wrong here
Running a pod on every node is the function of a DaemonSet, not a Deployment; Deployments manage ReplicaSets to provide rolling updates and rollback. It is tempting because DaemonSets do guarantee per-node coverage, which is the right choice for node-level agents such as log collectors or monitoring daemons.
Go deeper
Related to this question
About these practice questions
Courseiva writes every KCNA question from scratch — 930 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 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.