December 4, 2022

Graphic with the Kubernetes logo

Pod scheduling points are some of the widespread Kubernetes errors. There are a number of explanation why a brand new Pod can get caught in a Pending state with FailedScheduling as its purpose. A Pod that shows this standing gained’t begin any containers so that you’ll be unable to make use of your utility.

Pending Pods brought on by scheduling issues don’t usually begin working with out some handbook intervention. You’ll want to analyze the basis trigger and take motion to repair your cluster. On this article, you’ll learn to diagnose and resolve this downside so you’ll be able to convey your workloads up.

Figuring out a FailedScheduling Error

It’s regular for Pods to point out a Pending standing for a brief interval after you add them to your cluster. Kubernetes must schedule container situations to your Nodes and people Nodes have to tug the picture from its registry. The primary signal {that a} Pod’s failed scheduling is when it nonetheless exhibits as Pending after the same old startup interval has elapsed. You possibly can verify the standing by working Kubectl’s get pods command:

$ kubectl get pods

demo-pod    0/1     Pending     0           4m05s

demo-pod is over 4 minutes outdated but it surely’s nonetheless within the Pending state. Pods don’t often take this lengthy to start out containers so it’s time to start out investigating what Kubernetes is ready for.

The subsequent analysis step is to retrieve the Pod’s occasion historical past utilizing the describe pod command:

$ kubectl describe pod demo-pod

  Kind     Cause            Age       From               Message
  ----     ------            ----      ----               -------
  Warning  FailedScheduling  4m        default-scheduler  0/4 nodes can be found: 1 Too many pods, 3 Inadequate cpu.

The occasion historical past confirms a FailedScheduling error is the explanation for the extended Pending state. This occasion is reported when Kubernetes can’t allocate the required variety of Pods to any of the employee nodes in your cluster.

The occasion’s message reveals why scheduling is at present not possible: there are 4 nodes within the cluster however none of them can take the Pod. Three of the nodes have inadequate CPU capability whereas the opposite has reached a cap on the variety of Pods it will probably settle for.

Understanding FailedScheduling Errors and Comparable Issues

Kubernetes can solely schedule Pods onto nodes which have spare sources obtainable. Nodes with exhausted CPU or reminiscence capability can’t take any extra Pods. Pods can even fail scheduling in the event that they explicitly request extra sources than any node can present. This maintains your cluster’s stability.

The Kubernetes management airplane is conscious of the Pods already allotted to the nodes in your cluster. It makes use of this data to find out the set of nodes that may obtain a brand new Pod. A scheduling error outcomes when there’s no candidates obtainable, leaving the Pod caught Pending till capability is freed up.

Kubernetes can fail to schedule Pods for different causes too. There are a number of methods wherein nodes might be deemed ineligible to host a Pod, regardless of having sufficient system sources:

  • The node might need been cordoned by an administrator to cease it receiving new Pods forward of a upkeep operation.
  • The node may very well be tainted with an impact that stops Pods from scheduling. Your Pod gained’t be accepted by the node until it has a corresponding toleration.
  • Your Pod is likely to be requesting a hostPort which is already sure on the node. Nodes can solely present a specific port quantity to a single Pod at a time.
  • Your Pod may very well be utilizing a nodeSelector meaning it must be scheduled to a node with a specific label. Nodes that lack the label gained’t be eligible.
  • Pod and Node affinities and anti-affinities is likely to be unsatisfiable, inflicting a scheduling battle that stops new Pods from being accepted.
  • The Pod might need a nodeName field that identifies a particular node to schedule to. The Pod shall be caught pending if that node is offline or unschedulable.

It’s the accountability of kube-scheduler, the Kubernetes scheduler, to work by way of these situations and establish the set of nodes that may take a brand new Pod. A FailedScheduling occasion happens when not one of the nodes fulfill the factors.

Resolving the FailedScheduling State

The message displayed subsequent to FailedScheduling occasions often reveals why every node in your cluster was unable to take the Pod. You should use this data to start out addressing the issue. Within the instance proven above, the cluster had 4 Pods, three the place the CPU restrict had been reached, and one which had exceeded a Pod depend restrict.

Cluster capability is the basis trigger on this case. You possibly can scale your cluster with new nodes to resolve {hardware} consumption issues, including sources that may present further flexibility. As this will even increase your prices, it’s worthwhile checking whether or not you’ve acquired any redundant Pods in your cluster first. Deleting unused sources will liberate capability for brand new ones.

You possibly can examine the obtainable sources on every of your nodes utilizing the describe node command:

$ kubectl describe node demo-node

Allotted sources:
  (Whole limits could also be over one hundred pc, i.e., overcommitted.)
  Useful resource           Requests     Limits
  --------           --------     ------
  cpu                812m (90%)   202m (22%)
  reminiscence             905Mi (57%)  715Mi (45%)
  ephemeral-storage  0 (0%)       0 (0%)
  hugepages-2Mi      0 (0%)       0 (0%)

Pods on this node are already requesting 57% of the obtainable reminiscence. If a brand new Pod requested 1 Gi for itself then the node could be unable to simply accept the scheduling request. Monitoring this data for every of your nodes may also help you assess whether or not your cluster is turning into over-provisioned. It’s necessary to have spare capability obtainable in case one in every of your nodes turns into unhealthy and its workloads must be rescheduled to a different.

Scheduling failures attributable to there being no schedulable nodes will present a message just like the next within the FailedScheduling occasion:

0/4 nodes can be found: 4 node(s) have been unschedulable

Nodes which might be unschedulable as a result of they’ve been cordoned will embody SchedulingDisabled of their standing area:

$ kubectl get nodes
NAME       STATUS                     ROLES                  AGE   VERSION
node-1     Prepared,SchedulingDisabled   control-plane,grasp   26m   v1.23.3

You possibly can uncordon the node to permit it to obtain new Pods:

$ kubectl uncordon node-1
node/node-1 uncordoned

When nodes aren’t cordoned and have enough sources, scheduling errors are usually brought on by tainting or an incorrect nodeSelector area in your Pod. Should you’re using nodeSelector, verify you haven’t made a typo and that there are Pods in your cluster which have the labels you’ve specified.

When nodes are tainted, ensure you’ve included the corresponding toleration in your Pod’s manifest. For example, right here’s a node that’s been tainted so Pods don’t schedule until they’ve a demo-taint: permit toleration:

$ kubectl taint nodes node-1 demo-taint=permit:NoSchedule

Modify your Pod manifests to allow them to schedule onto the Node:

    - key: demo-taint
      operator: Equal
      worth: permit
      impact: NoSchedule

Resolving the issue that induced the FailedScheduling state will permit Kubernetes to renew scheduling your pending Pods. They’ll begin working robotically shortly after the management airplane detects the adjustments to your nodes. You don’t must manually restart or recreate your Pods, until the difficulty’s attributable to errors in your Pod’s manifest reminiscent of incorrect affinity or nodeSelector fields.


FailedScheduling errors happen when Kubernetes can’t place a brand new Pod onto any node in your cluster. This is actually because your present nodes are working low on {hardware} sources reminiscent of CPU, reminiscence, and disk. When that is the case, you’ll be able to resolve the issue by scaling your cluster to incorporate additional nodes.

Scheduling failures additionally come up when Pods specify affinities, anti-affinities, and node selectors that may’t at present be glad by the nodes obtainable in your cluster. Cordoned and tainted nodes additional cut back the choices obtainable to Kubernetes. This type of difficulty might be addressed by checking your manifests for typos in labels and eradicating constraints you now not want.

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