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issue w/ k8sMaster.sh on azure VM

I executed step by step the script and everything was fine except the node status: never get ready.
I assume the issue is the following "NetworkReady=false reason:NetworkPluginNotReady message:docker: network plugin is not ready: cni config uninitialized" see below

That's the output of:

kubectl describe node k8s-master
Name:               k8s-master
Roles:              master
Labels:             beta.kubernetes.io/arch=amd64
                    beta.kubernetes.io/os=linux
                    kubernetes.io/hostname=k8s-master
                    node-role.kubernetes.io/master=
Annotations:        kubeadm.alpha.kubernetes.io/cri-socket: /var/run/dockershim.sock
                    node.alpha.kubernetes.io/ttl: 0
                    volumes.kubernetes.io/controller-managed-attach-detach: true
CreationTimestamp:  Thu, 03 Jan 2019 18:13:03 +0000
Taints:             node.kubernetes.io/not-ready:NoExecute
                    node-role.kubernetes.io/master:NoSchedule
                    node.kubernetes.io/not-ready:NoSchedule
Unschedulable:      false
Conditions:
  Type             Status  LastHeartbeatTime                 LastTransitionTime                Reason                       Message
  ----             ------  -----------------                 ------------------                ------                       -------
  OutOfDisk        False   Thu, 03 Jan 2019 18:20:53 +0000   Thu, 03 Jan 2019 18:13:02 +0000   KubeletHasSufficientDisk     kubelet has sufficient disk space available
  MemoryPressure   False   Thu, 03 Jan 2019 18:20:53 +0000   Thu, 03 Jan 2019 18:13:02 +0000   KubeletHasSufficientMemory   kubelet has sufficient memory available
  DiskPressure     False   Thu, 03 Jan 2019 18:20:53 +0000   Thu, 03 Jan 2019 18:13:02 +0000   KubeletHasNoDiskPressure     kubelet has no disk pressure
  PIDPressure      False   Thu, 03 Jan 2019 18:20:53 +0000   Thu, 03 Jan 2019 18:13:02 +0000   KubeletHasSufficientPID      kubelet has sufficient PID available
  Ready            False   Thu, 03 Jan 2019 18:20:53 +0000   Thu, 03 Jan 2019 18:13:02 +0000   KubeletNotReady              runtime network not ready: NetworkReady=false reason:NetworkPluginNotReady message:docker: network plugin is not ready: cni config uninitialized
Addresses:
  InternalIP:  10.0.0.4
  Hostname:    k8s-master
Capacity:
 attachable-volumes-azure-disk:  16
 cpu:                            1
 ephemeral-storage:              30428648Ki
 hugepages-1Gi:                  0
 hugepages-2Mi:                  0
 memory:                         944140Ki
 pods:                           110
Allocatable:
 attachable-volumes-azure-disk:  16
 cpu:                            1
 ephemeral-storage:              28043041951
 hugepages-1Gi:                  0
 hugepages-2Mi:                  0
 memory:                         841740Ki
 pods:                           110
System Info:
 Machine ID:                 654ff64976f040a6acae661503aa9786
 System UUID:                A3E82C61-AE64-BA4D-AD00-F1B4C059EF48
 Boot ID:                    c74801bd-e52f-4daa-92bd-d1993b4cc89c
 Kernel Version:             4.15.0-1036-azure
 OS Image:                   Ubuntu 16.04.5 LTS
 Operating System:           linux
 Architecture:               amd64
 Container Runtime Version:  docker://18.6.1
 Kubelet Version:            v1.12.1
 Kube-Proxy Version:         v1.12.1
PodCIDR:                     192.168.0.0/24
Non-terminated Pods:         (6 in total)
  Namespace                  Name                                  CPU Requests  CPU Limits  Memory Requests  Memory Limits
  ---------                  ----                                  ------------  ----------  ---------------  -------------
  kube-system                coredns-869f847d58-jvbl7              100m (10%)    0 (0%)      70Mi (8%)        170Mi (20%)
  kube-system                etcd-k8s-master                       0 (0%)        0 (0%)      0 (0%)           0 (0%)
  kube-system                kube-apiserver-k8s-master             250m (25%)    0 (0%)      0 (0%)           0 (0%)
  kube-system                kube-controller-manager-k8s-master    200m (20%)    0 (0%)      0 (0%)           0 (0%)
  kube-system                kube-proxy-jzj5x                      0 (0%)        0 (0%)      0 (0%)           0 (0%)
  kube-system                kube-scheduler-k8s-master             100m (10%)    0 (0%)      0 (0%)           0 (0%)
Allocated resources:
  (Total limits may be over 100 percent, i.e., overcommitted.)
  Resource                       Requests    Limits
  --------                       --------    ------
  cpu                            650m (65%)  0 (0%)
  memory                         70Mi (8%)   170Mi (20%)
  attachable-volumes-azure-disk  0           0
Events:
  Type    Reason                   Age                    From                    Message
  ----    ------                   ----                   ----                    -------
  Normal  Starting                 8m31s                  kubelet, k8s-master     Starting kubelet.
  Normal  NodeAllocatableEnforced  8m31s                  kubelet, k8s-master     Updated Node Allocatable limit across pods
  Normal  NodeHasSufficientDisk    8m30s (x6 over 8m31s)  kubelet, k8s-master     Node k8s-master status is now: NodeHasSufficientDisk
  Normal  NodeHasSufficientMemory  8m30s (x6 over 8m31s)  kubelet, k8s-master     Node k8s-master status is now: NodeHasSufficientMemory
  Normal  NodeHasNoDiskPressure    8m30s (x5 over 8m31s)  kubelet, k8s-master     Node k8s-master status is now: NodeHasNoDiskPressure
  Normal  NodeHasSufficientPID     8m30s (x6 over 8m31s)  kubelet, k8s-master     Node k8s-master status is now: NodeHasSufficientPID
  Normal  Starting                 6m2s                   kube-proxy, k8s-master  Starting kube-proxy.

Comments

  • serewicz
    serewicz Posts: 1,000

    Hello,

    The labs have not been tested on Azure, so there are some unknowns. I would start with looking at a few things:

    Please view the state of all of your pods. Are there some who are not running or other issues?
    Have you ensured there are no firewalls or restrictions between nodes?
    What does kubectl get events show, if anything?
    If you look in the log files on the node, with journalctl, are there errors or messages to help troubleshoot?

    Should you be able to find an error, or perhaps a pod which is not running, it can be useful to start the troubleshooting process.

    Regards,

  • chrispokorni
    chrispokorni Posts: 2,313
    edited January 2019

    Hi @crixo ,
    Looking at your output, lines 12 - 14 indicate that you seem to be experiencing an issue which was supposed to be fixed, but I guess it was only fixed temporarily - where the nodes had an extra taint that prevented them to become Ready.
    In Lab 2.1 section [Deploy a Master Node using Kubeadm], at the end of step 2, the master was expected to be in a NotReady state, just like shown in the lab output:
    kubectl get node
    NAME STATUS ROLE ...
    ckad-1 NotReady master ...
    After completing the section [Deploy a Minion Node], and continuing with [Configure the Master Node], in step 7 both nodes should show NotReady. At this point, steps 8 -12 will guide you to remove the taints which prevent the nodes from going into ready state, and at the end of step 12 both your master and minion should be in Ready state.
    Regards,
    -Chris

  • crixo
    crixo Posts: 31

    Hi @chrispokorni,
    removing the Taints solved the problem, but I have also to upgrade (master and worker) k8s tools to version 1.13.0-00 as suggested here: https://forum.linuxfoundation.org/discussion/855684/section-2-1-5-cannot-get-resource-error-thrown-during-sudo-kubeadm-join

    I changed both k8sMaster.sh and k8sSecond.sh as following

    sudo apt-get install -y kubeadm=1.13.0-00 kubelet=1.13.0-00 kubectl=1.13.0-00

    now with the following azure VMs sizes:

    MASTER_SKU='Standard_B2s'
    AGENT_SKU='Standard_B1s'
    

    I'm able to create the cluster and continue the lab.
    Thanks a lot for the support

  • chrispokorni
    chrispokorni Posts: 2,313
    edited January 2019

    Hi @crixo ,
    The labs have been only tested as released, on K8s v1.12.1. The kubeadm issue between the 2 versions 1.12.1 and 1.13 can be resolved with a fix posted earlier in the forum, without an upgrade to 1.13, and that way you can complete the labs on 1.12:

    sudo kubeadm init --kubernetes-version 1.12.1 --pod-network-cidr 192.168.0.0/16

    There may be a chance that the labs work fine on 1.13, but in case they don't, that's the fix.
    Regards,
    -Chris

  • crixo
    crixo Posts: 31

    Hi @chrispokorni,
    adding --kubernetes-version 1.12.1 solve the problem and now I'm able to run the first part of the lab w/o upgrading to 1.13.

    I wonder if there's any option to avoid the Taints on both nodes (it saves some time after VMs provisioning).
    who's adding the Taints? My guess is kubeadm; if so, is there any option to avoiding it?
    An other option could be adding an additional tolerations on the calico.yaml in order to tolerate the Taints if those cannot be removed. Am I on the right track?

  • chrispokorni
    chrispokorni Posts: 2,313

    @crixo
    I am glad it worked and you are able to continue with the labs on 1.12.
    The taints have been going thru changes lately. Before 1.12 there was only 1 taint, then when 1.12 was released there were 2 taints, then immediately after it went back to 1 taint. Now it changed again.
    Kubernetes is a fast-moving project and features could change within a week.
    Tolerations would not necessarily work, or would work as long as you remembered to add them to any deployment/pod definition because taints affect pod scheduling in general, not only calico. By removing taints once, you don't have to worry about them in the future :smile:
    -Chris

  • Hi @pistle,

    As you can tell, the course does not make use of AKS. The shell script installs Kubernetes components and initializes the control plane node for you.

    Regards,
    -Chris

  • serewicz
    serewicz Posts: 1,000

    @Pistle - We do not test our labs using Azure. Too many problems. Instead I would suggest using GCE, AWS, Digital Ocean, VirtualBox, VMWare, extra laptops - basically anything but Azure.

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