Kubernetes pod stays Pending with event 'FailedScheduling: 0/3 nodes are available: 3 Insufficient cpu' or 'Insufficient memory'. How do I fix it?

Applies to: Kubernetes, any recent version; managed or self-hosted clusters

How it was checked: Compiled on 2026-10-30 from the Kubernetes docs on debugging pods and managing container resources; not reproduced by Exuvia.

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Fix

Cause: the scheduler could not find any node with enough unreserved capacity for the pod's resource requests. Scheduling is based on requests (not live usage), so a node can look idle yet be full on paper. The same Pending state with a similar message can also come from taints, node selectors/affinity, or hostPort conflicts, so read the full event text. Fix (best first): 1. Run kubectl describe pod POD_NAME and read the FailedScheduling event. It lists, per reason, how many nodes were rejected (for example Insufficient cpu, Insufficient memory, node(s) had untolerated taint, didn't match Pod's node affinity/selector). 2. See what is allocated: kubectl describe node NODE_NAME and read "Allocated resources", or kubectl top nodes if metrics-server is installed. 3. Lower the pod's resource requests if they are larger than the app really needs. Set requests from measured usage, not guesses. A request bigger than the largest node's allocatable capacity can never schedule, no matter how many nodes you add. 4. Free capacity by removing unused workloads or right-sizing over-requested ones, or add nodes (or let the cluster autoscaler add them if configured; check its logs if it did not scale up). 5. If the event names taints or affinity instead, add the right toleration or fix the selector rather than adding capacity. 6. Avoid hostPort unless required; it limits you to one pod per node. Use a Service instead. Verify: kubectl get pod shows the pod moved to ContainerCreating then Running, and kubectl get events no longer shows new FailedScheduling entries for it. Sources: https://kubernetes.io/docs/tasks/debug/debug-application/debug-pods/ https://kubernetes.io/docs/concepts/configuration/manage-resources-containers/

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