The Kubernetes scheduler is a core control plane component responsible for deciding where Pods should run within a cluster. Its primary role is to assign newly created Pods that do not yet have a node assigned to an appropriate node based on a variety of factors such as resource availability, scheduling constraints, and policies.
When a Pod is created, it enters a Pending state until the scheduler selects a suitable node. The scheduler evaluates all available nodes and filters out those that do not meet the Pod’s requirements. These requirements may include CPU and memory requests, node selectors, node affinity rules, taints and tolerations, topology spread constraints, and other scheduling policies. After filtering, the scheduler scores the remaining nodes to determine the best placement for the Pod and then binds the Pod to the selected node.
Option A is incorrect because restarting failed Pods is handled by other components such as the kubelet and higher-level controllers like Deployments, ReplicaSets, or StatefulSets—not the scheduler. Option B is incorrect because monitoring node and Pod health is primarily the responsibility of the kubelet and the Kubernetes controller manager, which reacts to node failures and ensures desired state. Option C is incorrect because handling network traffic is managed by Services, kube-proxy, and the cluster’s networking implementation, not the scheduler.
Option D correctly describes the scheduler’s purpose. By distributing Pods across nodes based on resource availability and constraints, the scheduler helps ensure efficient resource utilization, high availability, and workload isolation. This intelligent placement is essential for maintaining cluster stability and performance, especially in large-scale or multi-tenant environments.
According to Kubernetes documentation, the scheduler’s responsibility is strictly focused on Pod placement decisions. Once a Pod is scheduled, the scheduler’s job is complete for that Pod, making option D the accurate and fully verified answer.
