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KCNA Container Orchestration Practice Question

Which TWO statements about Docker Compose and Kubernetes are correct?

⚠ Common exam trap

A common misconception is that Docker Compose and Kubernetes use the same YAML format, but they are distinct schemas with different top-level keys and resource definitions. Candidates may confuse 'docker-compose.yml' with Kubernetes manifests.

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

✓

Kubernetes provides built-in auto-scaling and self-healing capabilities

Option C is correct because Kubernetes natively provides controllers such as the Horizontal Pod Autoscaler (HPA) for auto-scaling and ReplicaSets/Deployments with liveness and readiness probes for self-healing, restarting or rescheduling failed pods automatically. Option D is correct because Docker Compose orchestrates containers on a single Docker host using a docker-compose.yml file and the docker compose CLI, without any native multi-node scheduling. Option A is wrong because Kubernetes is also widely used in development, testing, edge, and CI environments, not only production. Option B is wrong because although both use YAML, their manifest schemas differ: Compose uses keys like services, image, and ports, while Kubernetes uses apiVersion, kind, metadata, and spec. Option E is wrong because Docker Compose has no built-in multi-node clustering; Docker Swarm or Kubernetes are needed for that.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • ✗

    Kubernetes is only used in production environments

    Why it's wrong here

    Kubernetes runs in development, testing, edge and CI environments, not production alone. The statement is tempting because Kubernetes is widely associated with production workloads, yet minikube, kind and k3s serve local and test use. Compose, by contrast, is typically confined to development.

  • ✗

    Docker Compose and Kubernetes use the same YAML manifest format

    Why it's wrong here

    Compose files and Kubernetes manifests differ in schema, apiVersion and kind fields, and resource semantics, so they are not interchangeable. Compose is tempting because both are declarative YAML, but Kubernetes requires its own manifest structure. Compose suits single-host local development; Kubernetes targets cluster orchestration.

  • ✓

    Kubernetes provides built-in auto-scaling and self-healing capabilities

    Why this is correct

    Kubernetes reconciles desired state through controllers: the ReplicaSet controller replaces failed pods, while the Horizontal Pod Autoscaler scales replicas based on CPU or custom metrics. This satisfies the stem's requirement for built-in auto-scaling and self-healing, capabilities Docker Compose lacks natively.

  • ✓

    Docker Compose is designed for single-host container orchestration

    Why this is correct

    Docker Compose orchestrates containers on one machine only, using a single Docker daemon to manage a shared network and volumes. This satisfies the single-host constraint, unlike Kubernetes, which schedules pods across a cluster of nodes. Compose therefore suits local development and simple deployments, not multi-node resilience.

  • ✗

    Docker Compose supports multi-node clustering out-of-the-box

    Why it's wrong here

    Compose runs containers on a single Docker host and has no native multi-node scheduling or clustering. Kubernetes provides that clustering. Compose is tempting because it orchestrates multiple containers, but only locally. It suits developer workstations and CI test environments, not distributed production clusters.

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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.