hardMultiple Choice
Google ACE Practice Question: A company manages a production GKE cluster with…
A company manages a production GKE cluster with node auto-upgrade enabled. They want to ensure that during a node upgrade, the workloads are rescheduled gracefully without downtime. What Kubernetes resource should be configured on their Deployments?
⚠ Common exam trap
ACE often tests the difference between PDB (voluntary disruption control) and HPA (scaling) — candidates pick HPA thinking more replicas automatically prevents downtime, but HPA does not gate evictions.
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
✓
PodDisruptionBudget
A PodDisruptionBudget (PDB) limits the number of pods of a replicated application that can be voluntarily disrupted at once (via minAvailable or maxUnavailable). During node upgrades, GKE drains nodes by evicting pods, and the PDB ensures enough replicas remain available to serve traffic, preventing downtime.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
PodDisruptionBudget
Why this is correct
PodDisruptionBudget (PDB) is the correct answer because it is the Kubernetes object specifically designed to protect applications during voluntary disruptions, such as GKE node auto-upgrades that drain nodes. A PDB uses minAvailable or maxUnavailable to define how many pods must remain available during evictions; when a node is being upgraded, the eviction API checks the PDB and blocks eviction of a pod if it would violate the budget. This ensures the production workload retains a guaranteed number of replicas, preventing downtime during node maintenance.
- ✗
HorizontalPodAutoscaler
Why it's wrong here
HorizontalPodAutoscaler (HPA) is incorrect because it only adjusts the replica count based on observed CPU or custom metrics, not to protect pods from eviction. During a GKE node auto-upgrade, nodes are drained, and HPA does not participate in the eviction decision-making process—pods are still terminated regardless of whether they are within the autoscaler's target. While HPA might scale up after pod loss to compensate, it cannot prevent the disruption from occurring in the first place.
- ✗
ResourceQuota
Why it's wrong here
ResourceQuota is wrong because it enforces aggregate resource consumption limits for a namespace (e.g., total CPU, memory, or pod count) and does not control eviction behavior or availability during voluntary disruptions. A ResourceQuota neither blocks the node drain during auto-upgrades nor guarantees any minimum number of running pods; it only rejects new pods if the quota would be exceeded, which is an admission control feature, not a disruption-protection feature.
- ✗
Node affinity rules
Why it's wrong here
Node affinity rules are incorrect because they influence initial pod placement by constraining pods to nodes with specific labels, but they have no effect on the eviction process during a node auto-upgrade. When GKE drains a node for upgrades, pods scheduled via node affinity are still terminated and rescheduled elsewhere only if they fit the affinity constraints on other nodes; there is no mechanism in affinity that delays or prevents the eviction itself, so availability is not preserved.
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Key term
Anthos
Anthos is a Google Cloud platform that lets you run applications consistently across different computing environments, like on-premises data centers and multiple public clouds.
Key term
GKE
GKE is Google's managed Kubernetes service that automates deploying, scaling, and managing containerized applications in the cloud.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official Google Cloud exam blueprint
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