Scheduling and Scaling Flashcards

What is the purpose of the `topologySpreadConstraints` field in a Pod spec?

Answer: To distribute pods evenly across failure domains such as zones or nodes

`topologySpreadConstraints` lets you control how pods are spread across topology domains to improve availability and balance.

Which HPA metric type allows scaling based on a metric exposed by an external system outside the cluster?

Answer: External

The `External` metric type in HPA enables scaling based on metrics from systems outside the Kubernetes cluster, such as a cloud queue depth.

A pod with `requiredDuringSchedulingIgnoredDuringExecution` node affinity cannot be scheduled if the rule is not satisfied. What happens to the pod?

Answer: It stays Pending until a matching node becomes available

Hard affinity rules (`required...`) cause the pod to remain Pending indefinitely if no node satisfies the constraint.

What does the Cluster Autoscaler do when a node has been underutilized for the scale-down delay period?

Answer: Terminates the node and reschedules its pods elsewhere

Cluster Autoscaler removes underutilized nodes from the node group and reschedules the pods that were running on them.

Which kubectl command removes a taint from a node?

Answer: kubectl taint nodes key=value:Effect-

Appending a `-` at the end of the taint specification in `kubectl taint nodes` removes that taint from the node.

When using pod affinity with `preferredDuringSchedulingIgnoredDuringExecution`, what happens if no node satisfies the preference?

Answer: The pod is scheduled on the best available node without the preference being met

Soft affinity (`preferred...`) is a hint, not a requirement; the scheduler places the pod even if the preference cannot be satisfied.

Which KEDA concept defines the external event source that triggers pod scaling?

Answer: Scaler

In KEDA, a Scaler is the component that connects to an external source (like Kafka or Redis) and reports the current metric value used for scaling decisions.