CKAD Application Deployment Practice Question
You have an HPA that scales a Deployment based on CPU utilization. You want to prevent the Deployment from scaling down for at least 5 minutes. Which HPA behavior field should you configure?
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
✓
behavior.scaleDown.stabilizationWindowSeconds
To prevent scaling down, you can set a stabilization window on the scaleDown policy. Option B correctly sets a stabilizationWindowSeconds in the scaleDown behavior.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
behavior.scaleUp.policies[0].periodSeconds
Why it's wrong here
behavior.scaleUp.policies[0].periodSeconds is scoped inside the scaleUp behavior block, so it only affects how frequently replica additions are allowed (e.g., how many replicas may be added per the specified period). It has no influence on the scaleDown path, meaning it cannot introduce any delay before the HPA reduces replicas after CPU utilization drops. A cooldown for scale-down must be configured through scaleDown.stabilizationWindowSeconds, not through a field under scaleUp.
- ✓
behavior.scaleDown.stabilizationWindowSeconds
Why this is correct
Setting behavior.scaleDown.stabilizationWindowSeconds configures the HPA to remember the desired replica counts from the last N seconds and, when scaling down, to use the maximum of those historical values instead of the newest recommendation. This creates the cooldown effect: after CPU utilization falls, the controller will not immediately shrink to the new lower desired count; it will only step down once the higher value ages out of the window. This prevents rapid, oscillating scale-downs during transient load dips and is exactly the field needed to avoid premature replica reduction.
- ✗
behavior.scaleUp.stabilizationWindowSeconds
Why it's wrong here
behavior.scaleUp.stabilizationWindowSeconds, if configured, would buffer scale-up decisions by requiring the CPU-based recommendation to remain steady for the entire window before additional replicas are added. However, it is scoped to the scaleUp behavior block, so it cannot delay or dampen scale-down activity when CPU utilization drops. Since scaleUp and scaleDown are evaluated as independent phases, this field leaves the scaleDown path untouched, meaning it would not help prevent quick replica removal.
- ✗
behavior.scaleDown.policies[0].periodSeconds
Why it's wrong here
behavior.scaleDown.policies[0].periodSeconds defines the sliding window over which a scale-down policy's rate is measured, such as allowing only one replica reduction per 60-second period. It does not create a wait-and-see cooldown after a scaling decision; it merely caps the velocity of replica removals once the HPA has already decided to scale down. The stabilizationWindowSeconds field on the same scaleDown block is what introduces a delay by retaining the maximum desired replica count from recent history, so periodSeconds is the wrong mechanism for adding a pre-scale-down cooldown.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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