Troubleshooting "Pending" Pods in Kubernetes: A Step-by-Step Guide



Understanding the Problem

When you run kubectl get pods in your Kubernetes cluster, you might see pods with a status of "Pending." This means that the pods have not been scheduled and started on the cluster nodes. Several reasons can cause this problem:

Resource Constraints: The nodes may lack available CPU or memory resources to accommodate the pods.

Scheduling Issues: There might not be enough node capacity or the pods may not meet specific node affinity or anti-affinity rules.

Image Pull Issues: The specified container image may not be accessible or could have issues.

Network Issues: Network policies or restrictions may prevent pod scheduling.


Troubleshooting Steps

To resolve the issue of "Pending" pods, follow these steps:


1. Check Pod Events

Use the kubectl describe pods command to check for events associated with the pods :

kubectl describe pods -n <namespace>

For Example

ubuntu@ip-172-31-34-83:~/elk/kubernetes_manifest_yml_files/04-EFK-Log$ kubectl get pods -n efklog
NAME                              READY   STATUS    RESTARTS   AGE
elasticsearch-logging-0           0/1     Pending   0          7m7s
fluentd-es-v2.7.0-cnsr6           0/1     Pending   0          6m16s
fluentd-es-v2.7.0-n9vhl           1/1     Running   0          6m16s
kibana-logging-5bfb55899f-2rmn2   1/1     Running   0          5m42s


ubuntu@ip-172-31-34-83:~/elk/kubernetes_manifest_yml_files/04-EFK-Log$ kubectl describe pods -n efklog

Events:
  Type     Reason            Age    From               Message
  ----     ------            ----   ----               -------
  Warning  FailedScheduling  10m    default-scheduler  0/2 nodes are available: 1 Too many pods, 2 Insufficient memory. preemption: 0/2 nodes are available: 2 No preemption victims found for incoming pod.
  Warning  FailedScheduling  4m58s  default-scheduler  0/2 nodes are available: 2 Insufficient memory, 2 Too many pods. preemption: 0/2 nodes are available: 2 No preemption victims found for incoming pod.

Events:
  Type     Reason            Age                    From               Message
  ----     ------            ----                   ----               -------
  Warning  FailedScheduling  3m58s (x2 over 9m13s)  default-scheduler  0/2 nodes are available: 1 Too many pods. preemption: 0/2 nodes are available: 2 No preemption victims found for incoming pod.

In the above example, we can see that in events it clearly explains that too many pods and Insufficient memory due to which scheduling has failed and pods are in a pending state.

Look for events or messages that explain why the pods are not starting. These events can provide 

valuable insights into the root cause.

2. Review Resource Requests and Limits
Inspect the resource requests and limits specified in your pod YAML files. Ensure that these values are reasonable and match the available resources on your nodes. Adjust them if necessary.

3. Verify Container Image
Check the container image specified in your pod definition. Make sure the image URL is correct and that the image is accessible from your container registry. If the image has issues, consider using a different one or addressing the problems with the current image.

4. Examine Scheduling Constraints
Investigate any node affinity or anti-affinity rules specified in your pod specifications. Ensure that the nodes meet these constraints, or adjust them accordingly.

5. Network Considerations
Review your network policies and restrictions to ensure they are not blocking pod scheduling. Adjust 
policies if needed to allow traffic.

ConclusionTroubleshooting "Pending" pods in Kubernetes can be a multi-faceted process, but by systematically checking resources, images, scheduling constraints, and network policies, you can identify and address the underlying issues. Once resolved, your pods should transition from "Pending" to "Running," allowing your applications to function as expected in your Kubernetes cluster.

By following the steps outlined in this guide, you can effectively diagnose and resolve pod scheduling issues in your Kubernetes environment, ensuring the smooth operation of your containerized applications.