Certified Kubernetes Application Developer (CKAD) Practice Test

In Kubernetes architecture, the scheduler is responsible for efficiently distributing tasks across the available resources within a cluster. Its primary function is to watch for newly created pods that do not have a node assigned and then select an appropriate node for the pod to run on based on various constraints and requirements.

The scheduler takes into account several factors such as resource availability (CPU and memory), node affinity and anti-affinity rules, taints and tolerations, and other scheduling policies that define how workloads should be spread across the cluster. By optimizing the placement of pods, the scheduler plays a crucial role in achieving an efficient and balanced use of the cluster's resources, helping to maximize performance and minimize potential bottlenecks.

While the controller manages the state of the cluster and the Kubelet ensures that the containers are running properly on each node, and the API server acts as the front-end for the Kubernetes control plane, it is specifically the scheduler that focuses on task distribution and optimal resource management.