I have spun up a Kubernetes cluster in AWS using the official "kube-up" mechanism. By default, an addon that monitors the cluster and logs to InfluxDB is created. It has been noted in this post that InfluxDB quickly fills up disk space on nodes, and I am seeing this same issue.
The problem is, when I try to kill the InfluxDB replication controller and service, it "magically" comes back after a time. I do this:
kubectl delete rc --namespace=kube-system monitoring-influx-grafana-v1
kubectl delete service --namespace=kube-system monitoring-influxdb
kubectl delete service --namespace=kube-system monitoring-grafana
Then if I say:
kubectl get pods --namespace=kube-system
I do not see the pods running anymore. However after some amount of time (minutes to hours), the replication controllers, services, and pods are back. I don't know what is restarting them. I would like to kill them permanently.
You probably need to remove the manifest files for influxdb from the /etc/kubernetes/addons/ directory on your "master" host. Many of the kube-up.sh implementations use a service (usually at /etc/kubernetes/kube-master-addons.sh) that runs periodically and makes sure that all the manifests in /etc/kubernetes/addons/ are active.
You can also restart your cluster, but run export ENABLE_CLUSTER_MONITORING=none before running kube-up.sh. You can see other environment settings that impact the cluster kube-up.sh builds at cluster/aws/config-default.sh
Related
Installed airflow in kubernetes using the repo https://airflow-helm.github.io/charts and airflow-stable/airflow with version 8.1.3. So I have Airflow v2.0.1 installed. I have it setup using external postgres database and using the kubernetes executor.
What I have noticed is when airflow related pods are done they go into a "NotReady" status. This happens with the update-db pod at startup and also pods launched by the kubernetes executioner. When I go into airflow and look at the task some are successful and some can be failure, but either way the related pods are in "NotReady" status. In the values file I set the below thinking it would delete the pods when they are done. I've gone through the logs and made sure one of the dags ran as intended and was success in the related task was success and of course the related pod when it was done went into "NotReady" status.
The values below are located in Values.airflow.config.
AIRFLOW__KUBERNETES__DELETE_WORKER_PODS: "true"
AIRFLOW__KUBERNETES__DELETE_WORKER_PODS_ON_FAILURE: "true"
So I'm not really sure what I'm missing and if anyone has seen this behavior? It's also really strange that the upgrade-db pod is doing this too.
Screenshot of kubectl get pods for the namespace airflow is deployed in with the "NotReady" pods
Figured it out. The K8 namespace had auto injection of linkerd sidecar container for each pod. Would have to just use celery executioner or setup some sort of k8 job to cleanup completed pods and jobs that don’t get cleaned up due to the linkerd container running forever in those pods.
I am trying to deploy pods on the EKS cluster. Below are some screen shots which shows that AWS EKS cluster is created and is active, group nodes are also active, now when i try to deploy any pod like nginx, wordpress or something else, these are not in the ready state. I tried deploying kubernetes dashboard and its in ready state, but why others are not in ready state do not know and that's why their URLs are not reachable.
also, while checking logs it says as below:
Error from server (NotFound): pods "deployment-2048-64549f6964-87d59" not found
Pods are in pending state. If a Pod is stuck in Pending it means that it can not be scheduled onto a node. It can happen because there are insufficient resources of one type or another that prevent pods scheduling.
You can look at the output by kubectl describe <deployment/pod_name>. There will be messages from the scheduler about why it can not schedule your pod.
k8s version: 1.12.1
I created pod with api on node and allocated an IP (through flanneld). When I used the kubectl describe pod command, I could not get the pod IP, and there was no such IP in etcd storage.
It was only a few minutes later that the IP could be obtained, and then kubectl get pod STATUS was Running.
Has anyone ever encountered this problem?
Like MatthiasSommer mentioned in comment, process of creating pod might take a while.
If POD will stay for a longer time in ContainerCreating status you can check what is stopping it change to status Running by command:
kubectl describe pod <pod_name>
Why creating of pod may take a longer time?
Depends on what is included in manifest, pod can share namespace, storage volumes, secrets, assignin resources, configmaps etc.
kube-apiserver validates and configures data for api objects.
kube-scheduler needs to check and collect resurces requrements, constraints, etc and assign pod to the node.
kubelet is running on each node and is ensures that all containers fulfill pod specification and are healty.
kube-proxy is also running on each node and it is responsible for network on pod.
As you see there are many requests, validates, syncs and it need a while to create pod fulfill all requirements.
In Kelsey Hightower's Kubernetes Up and Running, he gives two commands :
kubectl get daemonSets --namespace=kube-system kube-proxy
and
kubectl get deployments --namespace=kube-system kube-dns
Why does one use daemonSets and the other deployments?
And what's the difference?
Kubernetes deployments manage stateless services running on your cluster (as opposed to for example StatefulSets which manage stateful services). Their purpose is to keep a set of identical pods running and upgrade them in a controlled way. For example, you define how many replicas(pods) of your app you want to run in the deployment definition and kubernetes will make that many replicas of your application spread over nodes. If you say 5 replica's over 3 nodes, then some nodes will have more than one replica of your app running.
DaemonSets manage groups of replicated Pods. However, DaemonSets attempt to adhere to a one-Pod-per-node model, either across the entire cluster or a subset of nodes. A Daemonset will not run more than one replica per node. Another advantage of using a Daemonset is that, if you add a node to the cluster, then the Daemonset will automatically spawn a pod on that node, which a deployment will not do.
DaemonSets are useful for deploying ongoing background tasks that you need to run on all or certain nodes, and which do not require user intervention. Examples of such tasks include storage daemons like ceph, log collection daemons like fluentd, and node monitoring daemons like collectd
Lets take the example you mentioned in your question: why iskube-dns a deployment andkube-proxy a daemonset?
The reason behind that is that kube-proxy is needed on every node in the cluster to run IP tables, so that every node can access every pod no matter on which node it resides. Hence, when we make kube-proxy a daemonset and another node is added to the cluster at a later time, kube-proxy is automatically spawned on that node.
Kube-dns responsibility is to discover a service IP using its name and only one replica of kube-dns is enough to resolve the service name to its IP. Hence we make kube-dns a deployment, because we don't need kube-dns on every node.
How to delete all the contents from a kubernetes node? Contents include deployments, replica sets etc. I tried to delete deplyoments seperately. But kubernetes recreates all the pods again. Is there there any ways to delete all the replica sets present in a node?
If you are testing things, the easiest way would be
kubectl delete deployment --all
Althougth if you are using minikube, the easiest would probably be delete the machine and start again with a fresh node
minikube delete
minikube start
If we are talking about a production cluster, Kubernetes has a built-in feature to drain a node of the cluster, removing all the objects from that node safely.
You can use kubectl drain to safely evict all of your pods from a node before you perform maintenance on the node. Safe evictions allow the pod’s containers to gracefully terminate and will respect the PodDisruptionBudgets you have specified.
Note: By default kubectl drain will ignore certain system pods on the node that cannot be killed; see the kubectl drain documentation for more details.
When kubectl drain returns successfully, that indicates that all of the pods (except the ones excluded as described in the previous paragraph) have been safely evicted (respecting the desired graceful termination period, and without violating any application-level disruption SLOs). It is then safe to bring down the node by powering down its physical machine or, if running on a cloud platform, deleting its virtual machine.
First, identify the name of the node you wish to drain. You can list all of the nodes in your cluster with
kubectl get nodes
Next, tell Kubernetes to drain the node:
kubectl drain <node name>
Once it returns (without giving an error), you can power down the node (or equivalently, if on a cloud platform, delete the virtual machine backing the node). drain waits for graceful termination. You should not operate on the machine until the command completes.
If you leave the node in the cluster during the maintenance operation, you need to run
kubectl uncordon <node name>
afterwards to tell Kubernetes that it can resume scheduling new pods onto the node.
Please, note that if there are any pods that are not managed by ReplicationController, ReplicaSet, DaemonSet, StatefulSet or Job, then drain will not delete any pods unless you use --force, as mentioned in the docs.
kubectl drain <node name> --force
minikube delete --all
in case you are using minikube
it will let you start a new clean cluster.
in case you run on Kubernetes :
kubectl delete pods,deployments -A --all
it will remove it from all namespaces, you can add more objects in the same command .
Kubenertes provides namespaces object for isolation and separation of concern. Therefore, It is recommended to apply all of the k8s resources objects (Deployment, ReplicaSet, Pods, Services and other) in a custom namespace.
Now If you want to remove all of the relevant and related k8s resources, you just need to delete the namespace which will remove all of these resources.
kubectl create namespace custom-namespace
kubectl create -f deployment.yaml --namespace=custom-namespace
kubectl delete namespaces custom-namespace
I have attached a link for further research.
Namespaces
I tried so many variations to delete old pods from tutorials, including everything here.
What finally worked for me was:
kubectl delete replicaset --all
Deleting them one at a time didn't seem to work; it was only with the --all flag that all pods were deleted without being recreated.