Debug Running Pods

This page explains how to debug Pods running (or crashing) on a Node.

Before you begin

  • Your Pod should already be scheduled and running. If your Pod is not yet running, start with Debugging Pods.
  • For some of the advanced debugging steps you need to know on which Node the Pod is running and have shell access to run commands on that Node. You don't need that access to run the standard debug steps that use kubectl.

Using kubectl describe pod to fetch details about pods

For this example we'll use a Deployment to create two pods, similar to the earlier example.

apiVersion: apps/v1
kind: Deployment
  name: nginx-deployment
      app: nginx
  replicas: 2
        app: nginx
      - name: nginx
        image: nginx
            memory: "128Mi"
            cpu: "500m"
        - containerPort: 80

Create deployment by running following command:

kubectl apply -f
deployment.apps/nginx-deployment created

Check pod status by following command:

kubectl get pods
NAME                                READY   STATUS    RESTARTS   AGE
nginx-deployment-67d4bdd6f5-cx2nz   1/1     Running   0          13s
nginx-deployment-67d4bdd6f5-w6kd7   1/1     Running   0          13s

We can retrieve a lot more information about each of these pods using kubectl describe pod. For example:

kubectl describe pod nginx-deployment-67d4bdd6f5-w6kd7
Name:         nginx-deployment-67d4bdd6f5-w6kd7
Namespace:    default
Priority:     0
Node:         kube-worker-1/
Start Time:   Thu, 17 Feb 2022 16:51:01 -0500
Labels:       app=nginx
Annotations:  <none>
Status:       Running
  IP:           2001:db8::1
Controlled By:  ReplicaSet/nginx-deployment-67d4bdd6f5
    Container ID:   containerd://5403af59a2b46ee5a23fb0ae4b1e077f7ca5c5fb7af16e1ab21c00e0e616462a
    Image:          nginx
    Image ID:
    Port:           80/TCP
    Host Port:      0/TCP
    State:          Running
      Started:      Thu, 17 Feb 2022 16:51:05 -0500
    Ready:          True
    Restart Count:  0
      cpu:     500m
      memory:  128Mi
      cpu:        500m
      memory:     128Mi
    Environment:  <none>
      /var/run/secrets/ from kube-api-access-bgsgp (ro)
  Type              Status
  Initialized       True 
  Ready             True 
  ContainersReady   True 
  PodScheduled      True 
    Type:                    Projected (a volume that contains injected data from multiple sources)
    TokenExpirationSeconds:  3607
    ConfigMapName:           kube-root-ca.crt
    ConfigMapOptional:       <nil>
    DownwardAPI:             true
QoS Class:                   Guaranteed
Node-Selectors:              <none>
Tolerations:        op=Exists for 300s
                    op=Exists for 300s
  Type    Reason     Age   From               Message
  ----    ------     ----  ----               -------
  Normal  Scheduled  34s   default-scheduler  Successfully assigned default/nginx-deployment-67d4bdd6f5-w6kd7 to kube-worker-1
  Normal  Pulling    31s   kubelet            Pulling image "nginx"
  Normal  Pulled     30s   kubelet            Successfully pulled image "nginx" in 1.146417389s
  Normal  Created    30s   kubelet            Created container nginx
  Normal  Started    30s   kubelet            Started container nginx

Here you can see configuration information about the container(s) and Pod (labels, resource requirements, etc.), as well as status information about the container(s) and Pod (state, readiness, restart count, events, etc.).

The container state is one of Waiting, Running, or Terminated. Depending on the state, additional information will be provided -- here you can see that for a container in Running state, the system tells you when the container started.

Ready tells you whether the container passed its last readiness probe. (In this case, the container does not have a readiness probe configured; the container is assumed to be ready if no readiness probe is configured.)

Restart Count tells you how many times the container has been restarted; this information can be useful for detecting crash loops in containers that are configured with a restart policy of 'always.'

Currently the only Condition associated with a Pod is the binary Ready condition, which indicates that the pod is able to service requests and should be added to the load balancing pools of all matching services.

Lastly, you see a log of recent events related to your Pod. "From" indicates the component that is logging the event. "Reason" and "Message" tell you what happened.

Example: debugging Pending Pods

A common scenario that you can detect using events is when you've created a Pod that won't fit on any node. For example, the Pod might request more resources than are free on any node, or it might specify a label selector that doesn't match any nodes. Let's say we created the previous Deployment with 5 replicas (instead of 2) and requesting 600 millicores instead of 500, on a four-node cluster where each (virtual) machine has 1 CPU. In that case one of the Pods will not be able to schedule. (Note that because of the cluster addon pods such as fluentd, skydns, etc., that run on each node, if we requested 1000 millicores then none of the Pods would be able to schedule.)

kubectl get pods
NAME                                READY     STATUS    RESTARTS   AGE
nginx-deployment-1006230814-6winp   1/1       Running   0          7m
nginx-deployment-1006230814-fmgu3   1/1       Running   0          7m
nginx-deployment-1370807587-6ekbw   1/1       Running   0          1m
nginx-deployment-1370807587-fg172   0/1       Pending   0          1m
nginx-deployment-1370807587-fz9sd   0/1       Pending   0          1m

To find out why the nginx-deployment-1370807587-fz9sd pod is not running, we can use kubectl describe pod on the pending Pod and look at its events:

kubectl describe pod nginx-deployment-1370807587-fz9sd
  Name:		nginx-deployment-1370807587-fz9sd
  Namespace:	default
  Node:		/
  Labels:		app=nginx,pod-template-hash=1370807587
  Status:		Pending
  Controllers:	ReplicaSet/nginx-deployment-1370807587
      Image:	nginx
      Port:	80/TCP
      QoS Tier:
        memory:	Guaranteed
        cpu:	Guaranteed
        cpu:	1
        memory:	128Mi
        cpu:	1
        memory:	128Mi
      Environment Variables:
      Type:	Secret (a volume populated by a Secret)
      SecretName:	default-token-4bcbi
    FirstSeen	LastSeen	Count	From			        SubobjectPath	Type		Reason			    Message
    ---------	--------	-----	----			        -------------	--------	------			    -------
    1m		    48s		    7	    {default-scheduler }			        Warning		FailedScheduling	pod (nginx-deployment-1370807587-fz9sd) failed to fit in any node
  fit failure on node (kubernetes-node-6ta5): Node didn't have enough resource: CPU, requested: 1000, used: 1420, capacity: 2000
  fit failure on node (kubernetes-node-wul5): Node didn't have enough resource: CPU, requested: 1000, used: 1100, capacity: 2000

Here you can see the event generated by the scheduler saying that the Pod failed to schedule for reason FailedScheduling (and possibly others). The message tells us that there were not enough resources for the Pod on any of the nodes.

To correct this situation, you can use kubectl scale to update your Deployment to specify four or fewer replicas. (Or you could leave the one Pod pending, which is harmless.)

Events such as the ones you saw at the end of kubectl describe pod are persisted in etcd and provide high-level information on what is happening in the cluster. To list all events you can use

kubectl get events

but you have to remember that events are namespaced. This means that if you're interested in events for some namespaced object (e.g. what happened with Pods in namespace my-namespace) you need to explicitly provide a namespace to the command:

kubectl get events --namespace=my-namespace

To see events from all namespaces, you can use the --all-namespaces argument.

In addition to kubectl describe pod, another way to get extra information about a pod (beyond what is provided by kubectl get pod) is to pass the -o yaml output format flag to kubectl get pod. This will give you, in YAML format, even more information than kubectl describe pod--essentially all of the information the system has about the Pod. Here you will see things like annotations (which are key-value metadata without the label restrictions, that is used internally by Kubernetes system components), restart policy, ports, and volumes.

kubectl get pod nginx-deployment-1006230814-6winp -o yaml
apiVersion: v1
kind: Pod
  creationTimestamp: "2022-02-17T21:51:01Z"
  generateName: nginx-deployment-67d4bdd6f5-
    app: nginx
    pod-template-hash: 67d4bdd6f5
  name: nginx-deployment-67d4bdd6f5-w6kd7
  namespace: default
  - apiVersion: apps/v1
    blockOwnerDeletion: true
    controller: true
    kind: ReplicaSet
    name: nginx-deployment-67d4bdd6f5
    uid: 7d41dfd4-84c0-4be4-88ab-cedbe626ad82
  resourceVersion: "1364"
  uid: a6501da1-0447-4262-98eb-c03d4002222e
  - image: nginx
    imagePullPolicy: Always
    name: nginx
    - containerPort: 80
      protocol: TCP
        cpu: 500m
        memory: 128Mi
        cpu: 500m
        memory: 128Mi
    terminationMessagePath: /dev/termination-log
    terminationMessagePolicy: File
    - mountPath: /var/run/secrets/
      name: kube-api-access-bgsgp
      readOnly: true
  dnsPolicy: ClusterFirst
  enableServiceLinks: true
  nodeName: kube-worker-1
  preemptionPolicy: PreemptLowerPriority
  priority: 0
  restartPolicy: Always
  schedulerName: default-scheduler
  securityContext: {}
  serviceAccount: default
  serviceAccountName: default
  terminationGracePeriodSeconds: 30
  - effect: NoExecute
    operator: Exists
    tolerationSeconds: 300
  - effect: NoExecute
    operator: Exists
    tolerationSeconds: 300
  - name: kube-api-access-bgsgp
      defaultMode: 420
      - serviceAccountToken:
          expirationSeconds: 3607
          path: token
      - configMap:
          - key: ca.crt
            path: ca.crt
          name: kube-root-ca.crt
      - downwardAPI:
          - fieldRef:
              apiVersion: v1
              fieldPath: metadata.namespace
            path: namespace
  - lastProbeTime: null
    lastTransitionTime: "2022-02-17T21:51:01Z"
    status: "True"
    type: Initialized
  - lastProbeTime: null
    lastTransitionTime: "2022-02-17T21:51:06Z"
    status: "True"
    type: Ready
  - lastProbeTime: null
    lastTransitionTime: "2022-02-17T21:51:06Z"
    status: "True"
    type: ContainersReady
  - lastProbeTime: null
    lastTransitionTime: "2022-02-17T21:51:01Z"
    status: "True"
    type: PodScheduled
  - containerID: containerd://5403af59a2b46ee5a23fb0ae4b1e077f7ca5c5fb7af16e1ab21c00e0e616462a
    lastState: {}
    name: nginx
    ready: true
    restartCount: 0
    started: true
        startedAt: "2022-02-17T21:51:05Z"
  phase: Running
  - ip:
  - ip: 2001:db8::1
  qosClass: Guaranteed
  startTime: "2022-02-17T21:51:01Z"

Examining pod logs

First, look at the logs of the affected container:

kubectl logs ${POD_NAME} ${CONTAINER_NAME}

If your container has previously crashed, you can access the previous container's crash log with:

kubectl logs --previous ${POD_NAME} ${CONTAINER_NAME}

Debugging with container exec

If the container image includes debugging utilities, as is the case with images built from Linux and Windows OS base images, you can run commands inside a specific container with kubectl exec:

kubectl exec ${POD_NAME} -c ${CONTAINER_NAME} -- ${CMD} ${ARG1} ${ARG2} ... ${ARGN}

As an example, to look at the logs from a running Cassandra pod, you might run

kubectl exec cassandra -- cat /var/log/cassandra/system.log

You can run a shell that's connected to your terminal using the -i and -t arguments to kubectl exec, for example:

kubectl exec -it cassandra -- sh

For more details, see Get a Shell to a Running Container.

Debugging with an ephemeral debug container

FEATURE STATE: Kubernetes v1.25 [stable]

Ephemeral containers are useful for interactive troubleshooting when kubectl exec is insufficient because a container has crashed or a container image doesn't include debugging utilities, such as with distroless images.

Example debugging using ephemeral containers

You can use the kubectl debug command to add ephemeral containers to a running Pod. First, create a pod for the example:

kubectl run ephemeral-demo --restart=Never

The examples in this section use the pause container image because it does not contain debugging utilities, but this method works with all container images.

If you attempt to use kubectl exec to create a shell you will see an error because there is no shell in this container image.

kubectl exec -it ephemeral-demo -- sh
OCI runtime exec failed: exec failed: container_linux.go:346: starting container process caused "exec: \"sh\": executable file not found in $PATH": unknown

You can instead add a debugging container using kubectl debug. If you specify the -i/--interactive argument, kubectl will automatically attach to the console of the Ephemeral Container.

kubectl debug -it ephemeral-demo --image=busybox:1.28 --target=ephemeral-demo
Defaulting debug container name to debugger-8xzrl.
If you don't see a command prompt, try pressing enter.
/ #

This command adds a new busybox container and attaches to it. The --target parameter targets the process namespace of another container. It's necessary here because kubectl run does not enable process namespace sharing in the pod it creates.

You can view the state of the newly created ephemeral container using kubectl describe:

kubectl describe pod ephemeral-demo
Ephemeral Containers:
    Container ID:   docker://b888f9adfd15bd5739fefaa39e1df4dd3c617b9902082b1cfdc29c4028ffb2eb
    Image:          busybox
    Image ID:       docker-pullable://busybox@sha256:1828edd60c5efd34b2bf5dd3282ec0cc04d47b2ff9caa0b6d4f07a21d1c08084
    Port:           <none>
    Host Port:      <none>
    State:          Running
      Started:      Wed, 12 Feb 2020 14:25:42 +0100
    Ready:          False
    Restart Count:  0
    Environment:    <none>
    Mounts:         <none>

Use kubectl delete to remove the Pod when you're finished:

kubectl delete pod ephemeral-demo

Debugging using a copy of the Pod

Sometimes Pod configuration options make it difficult to troubleshoot in certain situations. For example, you can't run kubectl exec to troubleshoot your container if your container image does not include a shell or if your application crashes on startup. In these situations you can use kubectl debug to create a copy of the Pod with configuration values changed to aid debugging.

Copying a Pod while adding a new container

Adding a new container can be useful when your application is running but not behaving as you expect and you'd like to add additional troubleshooting utilities to the Pod.

For example, maybe your application's container images are built on busybox but you need debugging utilities not included in busybox. You can simulate this scenario using kubectl run:

kubectl run myapp --image=busybox:1.28 --restart=Never -- sleep 1d

Run this command to create a copy of myapp named myapp-debug that adds a new Ubuntu container for debugging:

kubectl debug myapp -it --image=ubuntu --share-processes --copy-to=myapp-debug
Defaulting debug container name to debugger-w7xmf.
If you don't see a command prompt, try pressing enter.

Don't forget to clean up the debugging Pod when you're finished with it:

kubectl delete pod myapp myapp-debug

Copying a Pod while changing its command

Sometimes it's useful to change the command for a container, for example to add a debugging flag or because the application is crashing.

To simulate a crashing application, use kubectl run to create a container that immediately exits:

kubectl run --image=busybox:1.28 myapp -- false

You can see using kubectl describe pod myapp that this container is crashing:

    Image:         busybox
    State:          Waiting
      Reason:       CrashLoopBackOff
    Last State:     Terminated
      Reason:       Error
      Exit Code:    1

You can use kubectl debug to create a copy of this Pod with the command changed to an interactive shell:

kubectl debug myapp -it --copy-to=myapp-debug --container=myapp -- sh
If you don't see a command prompt, try pressing enter.
/ #

Now you have an interactive shell that you can use to perform tasks like checking filesystem paths or running the container command manually.

Don't forget to clean up the debugging Pod when you're finished with it:

kubectl delete pod myapp myapp-debug

Copying a Pod while changing container images

In some situations you may want to change a misbehaving Pod from its normal production container images to an image containing a debugging build or additional utilities.

As an example, create a Pod using kubectl run:

kubectl run myapp --image=busybox:1.28 --restart=Never -- sleep 1d

Now use kubectl debug to make a copy and change its container image to ubuntu:

kubectl debug myapp --copy-to=myapp-debug --set-image=*=ubuntu

The syntax of --set-image uses the same container_name=image syntax as kubectl set image. *=ubuntu means change the image of all containers to ubuntu.

Don't forget to clean up the debugging Pod when you're finished with it:

kubectl delete pod myapp myapp-debug

Debugging via a shell on the node

If none of these approaches work, you can find the Node on which the Pod is running and create a Pod running on the Node. To create an interactive shell on a Node using kubectl debug, run:

kubectl debug node/mynode -it --image=ubuntu
Creating debugging pod node-debugger-mynode-pdx84 with container debugger on node mynode.
If you don't see a command prompt, try pressing enter.

When creating a debugging session on a node, keep in mind that:

  • kubectl debug automatically generates the name of the new Pod based on the name of the Node.
  • The root filesystem of the Node will be mounted at /host.
  • The container runs in the host IPC, Network, and PID namespaces, although the pod isn't privileged, so reading some process information may fail, and chroot /host may fail.
  • If you need a privileged pod, create it manually or use the --profile=sysadmin flag.

Don't forget to clean up the debugging Pod when you're finished with it:

kubectl delete pod node-debugger-mynode-pdx84

Debugging Profiles

When using kubectl debug to debug a node via a debugging Pod, a Pod via an ephemeral container, or a copied Pod, you can apply a debugging profile to them using the --profile flag. By applying a profile, specific properties such as securityContext are set, allowing for adaptation to various scenarios.

The available profiles are as follows:

legacyA set of properties backwards compatibility with 1.22 behavior
generalA reasonable set of generic properties for each debugging journey
baselineA set of properties compatible with PodSecurityStandard baseline policy
restrictedA set of properties compatible with PodSecurityStandard restricted policy
netadminA set of properties including Network Administrator privileges
sysadminA set of properties including System Administrator (root) privileges

Assume that you create a Pod and debug it. First, create a Pod named myapp as an example:

kubectl run myapp --image=busybox:1.28 --restart=Never -- sleep 1d

Then, debug the Pod using an ephemeral container. If the ephemeral container needs to have privilege, you can use the sysadmin profile:

kubectl debug -it myapp --image=busybox:1.28 --target=myapp --profile=sysadmin
Targeting container "myapp". If you don't see processes from this container it may be because the container runtime doesn't support this feature.
Defaulting debug container name to debugger-6kg4x.
If you don't see a command prompt, try pressing enter.
/ #

Check the capabilities of the ephemeral container process by running the following command inside the container:

/ # grep Cap /proc/$$/status
CapPrm:	000001ffffffffff
CapEff:	000001ffffffffff

This means the container process is granted full capabilities as a privileged container by applying sysadmin profile. See more details about capabilities.

You can also check that the ephemeral container was created as a privileged container:

kubectl get pod myapp -o jsonpath='{.spec.ephemeralContainers[0].securityContext}'

Clean up the Pod when you're finished with it:

kubectl delete pod myapp
Last modified June 27, 2024 at 8:48 AM PST: add description about debugging profile (0c8a63f4a2)