HomeNewsHow to Debug Kubernetes “FailedScheduling” Errors

How to Debug Kubernetes “FailedScheduling” Errors

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Pod scheduling points are one of the crucial widespread Kubernetes errors. There are a number of the reason why a brand new Pod can get caught in a Pending state with FailedScheduling as its cause. 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 guide intervention. You’ll want to analyze the foundation trigger and take motion to repair your cluster. On this article, you’ll learn to diagnose and resolve this downside so you may 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 cases to your Nodes and people Nodes have to drag 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 previous nevertheless it’s nonetheless within the Pending state. Pods don’t normally take this lengthy to start out containers so it’s time to start out investigating what Kubernetes is ready for.

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

$ kubectl describe pod demo-pod

  Kind     Purpose            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 rationale 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 the moment inconceivable: 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 might settle for.

Understanding FailedScheduling Errors and Related Issues

Kubernetes can solely schedule Pods onto nodes which have spare sources out there. Nodes with exhausted CPU or reminiscence capability can’t take any extra Pods. Pods may 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 aircraft 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 out there, 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 by which nodes could be deemed ineligible to host a Pod, regardless of having sufficient system sources:

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

It’s the accountability of kube-scheduler, the Kubernetes scheduler, to work by means of these circumstances and determine 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 normally reveals why every node in your cluster was unable to take the Pod. You need to 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 foundation trigger on this case. You possibly can scale your cluster with new nodes to resolve {hardware} consumption issues, including sources that can present further flexibility. As this can even increase your prices, it’s worthwhile checking whether or not you’ve obtained any redundant Pods in your cluster first. Deleting unused sources will release capability for brand new ones.

You possibly can examine the out there 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 out there reminiscence. If a brand new Pod requested 1 Gi for itself then the node could be unable to just accept the scheduling request. Monitoring this data for every of your nodes might help you assess whether or not your cluster is changing into over-provisioned. It’s vital to have spare capability out there in case certainly one of your nodes turns into unhealthy and its workloads must be rescheduled to a different.

Scheduling failures as a consequence of there being no schedulable nodes will present a message much like the next within the FailedScheduling occasion:

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

Nodes which are 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. For those who’re utilizing 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, be sure 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 except 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 triggered the FailedScheduling state will permit Kubernetes to renew scheduling your pending Pods. They’ll begin working routinely shortly after the management aircraft detects the adjustments to your nodes. You don’t must manually restart or recreate your Pods, except the problem’s as a consequence of errors in your Pod’s manifest comparable to 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 current nodes are working low on {hardware} sources comparable to CPU, reminiscence, and disk. When that is the case, you may resolve the issue by scaling your cluster to incorporate further nodes.

Scheduling failures additionally come up when Pods specify affinities, anti-affinities, and node selectors that may’t at the moment be happy by the nodes out there in your cluster. Cordoned and tainted nodes additional scale back the choices out there to Kubernetes. This type of situation could be addressed by checking your manifests for typos in labels and eradicating constraints you not want.

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