CKAD Application Deployment Practice Question

Answer analysis

Option-by-option breakdown

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

• ✗

  To update the application version without downtime

  Why it's wrong here

  A HorizontalPodAutoscaler adjusts the replica count of a workload's pods based on observed metrics such as CPU utilisation; it never performs version transitions. Rolling updates, which replace pods incrementally under a Deployment's update strategy, achieve zero-downtime releases. That is what this option describes, making it tempting, but the HPA's axis is scaling, not release management.

• ✗

  To restart pods automatically when they fail

  Why it's wrong here

  A HorizontalPodAutoscaler adjusts the replica count of a workload based on observed metrics such as CPU utilisation; it never restarts containers. Restarting failed pods is the kubelet's liveness probe behaviour, so this option describes self-healing rather than scaling. HPA would be the right answer when the requirement is scaling replicas in response to load.

• ✗

  To distribute incoming traffic across multiple pods

  Why it's wrong here

  An HPA adjusts replica count based on metrics such as CPU utilisation; traffic distribution is the job of a Service. It would be the right tool when demand must scale pod numbers up or down automatically.

• ✓

  To automatically adjust the number of pods based on resource metrics

  Why this is correct

  The HPA controller watches metrics such as CPU utilisation and adjusts a workload's replica count to meet a target, scaling pods horizontally. It satisfies the requirement to match capacity to demand automatically rather than manually resizing deployments.

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