The Pending status for a Pod indicates that the Kubernetes scheduler has accepted the Pod but cannot yet place it onto a node. The most common reason for this is insufficient cluster resources (CPU or memory). In this scenario, the first replica of the Deployment was successfully scheduled and is Running, consuming resources on a node. The second replica, with identical resource requests, cannot be scheduled because the remaining available resources in the cluster are not sufficient to meet its needs. The Pod will remain Pending until resources are freed up or a new node is added to the cluster, for example, by the cluster autoscaler.

A: This is incorrect because one replica is already Running. As both Pods have identical resource requests, if one can fit on a node, the other's request is not inherently too large.

C: Incorrect image pull permissions would cause an ImagePullBackOff or ErrImagePull status after the Pod is scheduled to a node, not prevent it from being scheduled (i.e., leave it Pending).

D: While a node preemption could lead to this state, the direct cause of the Pending status is the lack of schedulable resources, which is more accurately described by option B.

1. Kubernetes Documentation

Pod Lifecycle

Pod Phase: The Pending phase is defined as: "The Pod has been accepted by the Kubernetes cluster

but one or more of the containers has not been set up and made ready to run. This includes time a Pod spends waiting to be scheduled..." This confirms that scheduling issues are a primary cause of the Pending state. (Source: https://kubernetes.io/docs/concepts/workloads/pods/pod-lifecycle/#pod-phase)

2. Google Cloud Documentation

GKE

Cluster autoscaler: "Cluster autoscaler automatically resizes the number of nodes in a given node pool

based on the demands of your workloads. ... it adds nodes when there are Pods that failed to schedule in the node pool due to insufficient resources." This directly links the Pending state (failed to schedule) with resource insufficiency. (Source: https://cloud.google.com/kubernetes-engine/docs/concepts/cluster-autoscaler

"How cluster autoscaler works" section).

3. Kubernetes Documentation

Kubernetes Scheduler: The scheduler's role is to assign Pods to nodes. "If no node is suitable

the pod remains unscheduled until the scheduler is able to place it." The primary filtering step in finding a suitable node is checking if a node has enough available resources to meet the Pod's specific resource requests. (Source: https://kubernetes.io/docs/concepts/scheduling-eviction/kube-scheduler/

"The kube-scheduler" section).