GKE 1.1.1 and kubectl delete resource Terminating - kubernetes

A new GKE cluster created at v1.1.1 and using latest kubectl (from gcloud components update) when deleting resources (say a pod) sometimes kubectl get pods in a 'Terminating' state and other times they delete (are removed from kubectl get pods output) right away.
NAME READY STATUS RESTARTS AGE
cassandra 1/1 Terminating 0 44s
Is this new behavior of kubectl? I don't recall it doing this at my prior levels.

Yes, it is new behavior in v1.1.1. PR #9165 added graceful deletion of pods, which causes them to appear in the "Terminating" state for a short amount of time. Issue #1535 has some more background discussion.

You can explicitly set TerminationGracePeriodSeconds to zero in the PodSpec to obtain the old behavior.

Related

Kube pod not in running state

We have a argo-rollout for one of the service. I used the cmd to update the image.
kubectl-argo-rollouts -n ddash5 set image detector detector=starry-academy-177207/detector:deepak-detector-8
I was expecting this to update the pod, but it created a new one.
NAME READY STATUS RESTARTS AGE
detector-5d96bc8456-h2x7p 1/1 Running 0 35m
detector-68f89d8b45-j465j 0/1 Running 0 35m
Even if I delete detector-5d96bc8456-h2x7p, pod gets recreated with the older image.
and detector-68f89d8b45-j465j stays in 0/1 state.
I am new to kube, Can someone give me insights to this?
Thanks!!!
Deepak
You are using argo rollout, where rolling updates allow deployment updates pods instances with new ones. The new Pods will be scheduled on Nodes with available resources.That is the reason new pods are getting created by replacing existing pods.
Instead you can use kubectl set image command which is used to update images of existing deployment, it will update images without recreating the deployment.Use the following command.
kubectl set image deployment/<deployment-name> <container-name>=<image>:<tag>
In your case:
kubectl set image deployment/detector detector=starry-academy-177207/detector:deepak-detector-8
This will update existing deployment, try it and let me know if this works.Found ArgoCD Image updater you can check it.

Auto delete CrashBackoffLoop pods in a deployment

In my kubernetes cluster, there are multiple deployments in a namespace.
For a specific deployment, there is a need to not allow "CrashLoopBackoff" pods to exist.
So basically, when any pod gets to this state, I would want it to be deleted and later a new pod to be created which is already handled by the ReplicaSet.
I tried with custom controllers, with the thought that the SharedInformer would alert about the state of Pod and then I would delete it from that loop.
However, this brings dependency on the pod on which the custom controller would run.
I also tried searching for any option to be configured in the manifest itself, but could not find any.
I am pretty new to Kuberenetes, so need help in the implementation of this behaviour.
Firstly, you should address the reason why the pod has entered the CrashLoopBackOff state rather than just delete it. If you do this, you'll potentially just recreate the problem again and you'll be deleting pods repeatedly. For example, if your pod is trying to access an external DB and that DB is down, it'll CrashLoop, and deleting and restarting the pod won't help fix that.
Secondly, if you want to do this deleting in an automated manner, an easy way would be to run a CronJob resource that goes through your deployment and deletes the CrashLooped pods. You could set the cronjob to run once an hour or whatever schedule you wish.
Deleting the POD and waiting for the New one is like restarting the deployment or POD.
Kubernetes will auto restart your CrashLoopBackoff POD if failing, you can check the Restart count.
NAME READY STATUS RESTARTS AGE
te-pod-1 0/1 CrashLoopBackOff 2 1m44s
This restarts will be similar to what you have mentioned
when any pod gets to this state, I would want it to be deleted and
later a new pod to be created which is already handled by the
ReplicaSet.
If you want to remove Crashing the POD fully and not look for new POD to come up, you have to rollback the deployment.
If there is any issue with your Replicaset and your POD is crashing it would be useless, any number of times you delete and restart the POD it will crash all time, unless you check logs & debug to solve the real issue in replicaset(Deployment).

Kubernetes limit number of retry

For some context, I'm creating an API in python that creates K8s Jobs with user input in ENV variables.
Sometimes, it happens that the Image selected does not exist or has been deleted. Secrets does not exists or Volume isn't created. So it makes the Job in a crashloopbackoff or imagepullbackoff state.
First I'm am wondering if the ressource during this state are allocated to the job?
If yes, I don't want the Job to loop forever and lock resources to a never starting Job.
I've set the backofflimit to 0, but this is when the Job detect a Pod that goes in fail and tries to relaunch an other Pod to retry. In my case, I know that if a Pod fails for a job, then it's mostly due to OOM or code that fails and will always fails due to user input. So retrying will always fail.
But it doesn't limit the number of tries to crashloopbackoff or imagepullbackoff. Is there a way to set to terminate or fail the Job? I don't want to kill it, but just free the ressource and keep the events in (status.container.state.waiting.reason + status.container.state.waiting.message) or (status.container.state.terminated.reason + status.container.state.terminated.exit_code)
Could there be an option to set to limit the number of retry at the creation so I can free resources, but not to remove it to keep logs.
I have tested your first question and YES even if a pod is in crashloopbackoff state, the resources are still allocated to it !!! Here is my test: Are the Kubernetes requested resources by a pod still allocated to it when it is in crashLoopBackOff state?
Thanks for your question !
Long answer short, unfortunately there is no such option in Kubernetes.
However, you can do this manually by checking if the pod is in a crashloopbackoff then, unallocate its resources or simply delete the pod itself.
The following script delete any pod in the crashloopbackoff state from a specified namespace
#!/bin/bash
# This script check the passed namespace and delete pods in 'CrashLoopBackOff state
NAMESPACE="test"
delpods=$(sudo kubectl get pods -n ${NAMESPACE} |
grep -i 'CrashLoopBackOff' |
awk '{print $1 }')
for i in ${delpods[#]}; do
sudo kubectl delete pod $i --force=true --wait=false \
--grace-period=0 -n ${NAMESPACE}
done
Since we have passed the option --grace-period=0 the pod won't automatically restart again.
But, if after using this script or assigning it to a job, you noticed that the pod continues to restart and fall in the CrashLoopBackOff state again for some weird reason. Thera is a workaround for this, which is changing the restart policy of the pod:
A PodSpec has a restartPolicy field with possible values Always,
OnFailure, and Never. The default value is Always. restartPolicy
applies to all Containers in the Pod. restartPolicy only refers to
restarts of the Containers by the kubelet on the same node. Exited
Containers that are restarted by the kubelet are restarted with an
exponential back-off delay (10s, 20s, 40s …) capped at five minutes,
and is reset after ten minutes of successful execution. As discussed
in the Pods document, once bound to a node, a Pod will never be
rebound to another node.
See more details in the documentation or from here.
And that is it! Happy hacking.
Regarding the first question, it is already answered by bguess here.

How can a pod have status ready and terminating?

Curiously, I saw that a pod I had had both ready 1/1 status and status terminating when I ran kubectl get pods. Are these states not mutually exclusive? Why or why not?
For context, this was noticed immediately after I had killed skaffold so these pods were in the middle of shutting down.
When pods are in terminating state, they could still be functioning. The pod could be delayed in termination due to many reasons (eg. could be that you have a PVC attached, other pods are being terminated at the same time, etc). You could test this by running the following on a pod with a PVC attached or another reason to be terminated with a delay:
$ kubectl delete pod mypod-xxxxx-xxxxxx
pod mypod-xxxxx-xxxxxx deleted
$ kubectl delete pod mypod-xxxxx-xxxxxx
pod mypod-xxxxx-xxxxxx deleted
$ kubectl apply mypod.yaml
pod mypod-xxxxx-xxxxxx configured
Sometimes this happens because the pod is still in the terminating period and is functioning normally, so it will be treated as an existing pod that gets configured (neglecting the fact that you usually can't configure pods like this, but you get the point).
The ready column says how many containers are up.
The status terminating means no more traffic is being sent to that pod by the controllers. From kubernetes' docs:
When a user requests deletion of a pod, the system records the
intended grace period before the pod is allowed to be forcefully
killed, and a TERM signal is sent to the main process in each
container. Once the grace period has expired, the KILL signal is sent
to those processes, and the pod is then deleted from the API server.
That's the state it is. The containers are up, finishing processing whatever work it had already and a TERM signal was sent.
I want to update #nrxr answer:
The status terminating means no more traffic is being sent to that pod by the controllers.
That is what we want, but in reality, it not always be like that. The pod may terminate completely and the traffic still forward to it.
For detail please read this blog: https://learnk8s.io/graceful-shutdown.

Why does scaling down a deployment seem to always remove the newest pods?

(Before I start, I'm using minikube v27 on Windows 10.)
I have created a deployment with the nginx 'hello world' container with a desired count of 2:
I actually went into the '2 hours' old pod and edited the index.html file from the welcome message to "broken" - I want to play with k8s to seem what it would look like if one pod was 'faulty'.
If I scale this deployment up to more instances and then scale down again, I almost expected k8s to remove the oldest pods, but it consistently removes the newest:
How do I make it remove the oldest pods first?
(Ideally, I'd like to be able to just say "redeploy everything as the exact same version/image/desired count in a rolling deployment" if that is possible)
Pod deletion preference is based on a ordered series of checks, defined in code here:
https://github.com/kubernetes/kubernetes/blob/release-1.11/pkg/controller/controller_utils.go#L737
Summarizing- precedence is given to delete pods:
that are unassigned to a node, vs assigned to a node
that are in pending or not running state, vs running
that are in not-ready, vs ready
that have been in ready state for fewer seconds
that have higher restart counts
that have newer vs older creation times
These checks are not directly configurable.
Given the rules, if you can make an old pod to be not ready, or cause an old pod to restart, it will be removed at scale down time before a newer pod that is ready and has not restarted.
There is discussion around use cases for the ability to control deletion priority, which mostly involve workloads that are a mix of job and service, here:
https://github.com/kubernetes/kubernetes/issues/45509
what about this :
kubectl scale deployment ingress-nginx-controller --replicas=2
Wait until 2 replicas are up.
kubectl delete pod ingress-nginx-controller-oldest-replica
kubectl scale deployment ingress-nginx-controller --replicas=1
I experienced zero downtime doing so while removing oldest pod.