Install and access the K8s Web UI Dashboard

While I don’t find the dashboard very useful for configuring anything in the cluster, it can be helpful to find a resource you’ve lost track of or discover resources you didn’t know were there.

Before following this guide, you should have an installed kubernetes cluster. If you don’t, check out the guide how to Install K3s.

Installing the dashboard

To install the dashboard we need to run the following one command on the primary cluster node (in my example, this is k8s-1). K3s installations require the command be prefixed with sudo:

    • K3s:
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      sudo kubectl apply -f https://raw.githubusercontent.com/kubernetes/dashboard/v2.3.1/aio/deploy/recommended.yaml
      

This URL includes the version number, so you will want to double check that it is up-to-date when following the instruction. The latest version will show up at the K8s dashboard latest release page.

Screenshot of terminal output from installing the K8s Web UI Dashboard

Creating the admin user

Accessing the dashboard requires that we supply a token to authorise ourselves. This account is not created by the command above.

  1. On the primary cluster node create a file called dashboard.admin-user.yml with the following content:

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    apiVersion: v1
    kind: ServiceAccount
    metadata:
      name: admin-user
      namespace: kubernetes-dashboard
    

    I recommend using nano to create the file:

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    nano -w dashboard.admin-user.yml
    

    To save the file and exit nano once you’ve copied the contents into the terminal type ctrl+x followed by y to confirm that you want to save the file and finally enter.

    When applied to the cluster this will create our user account called admin-user and store it into the kubernetes-dashboard namespace, which was created by the installation step above.

    • The apiVersion must be set to v1 so that K8s knows which fields are acceptible.
    • The kind must be set to ServiceAccount to tell K8s that we’re attempting to create a user.
  2. Also on the primary cluster node create another file called dashboard.admin-user-role.yml with the following content:

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    apiVersion: rbac.authorization.k8s.io/v1
    kind: ClusterRoleBinding
    metadata:
      name: admin-user
    roleRef:
      apiGroup: rbac.authorization.k8s.io
      kind: ClusterRole
      name: cluster-admin
    subjects:
    - kind: ServiceAccount
      name: admin-user
      namespace: kubernetes-dashboard
    

    When applied to the cluster this will create a “role binding” to bind our user account to the cluster admin role.

    • The apiVersion must be set to rbac.authorization.k8s.io/v1 to tell K8s that we’re using the RBAC API version 1. A different apiVersion will likely change the fields available for use below, so will break our attempt to apply to the cluster.
    • The kind field must be set to ClusterRoleBinding to tell K8s that we’re attempting to create a Cluster Role Binding that binds an account to a cluster role.
    • The metadata.name entry is an arbitrary name for the role binding but it makes sense to name this the same as the user account that we’re binding.
    • subjects list must include one or more items. Each item in the list must have a kind, name, and namespace field.
      • The kind field must be set to ServiceAccount since that is what we used to create our admin-user.
      • The name should be set to the same as that we used in the dashboard.admin-user.yml file, i.e. admin-user.
      • The namespace should be set to the same name as that we used in the dashboard-admin-user.yml file so that K8s can find the correct service account, i.e. kubernetes-dashboard.
    • The roleRef configuration specifies the role that each user in the subjects list is assigned to.
      • The apiGroup field must be set to rbac.authorization.k8s.io to tell K8s that we’re referencing a role-based access control role.
      • The kind field should be set to that of the accounts in the subjects list are granted the role of cluster-admin - This is a default role in K8s.
  3. Apply these configurations to the cluster with the following command:

    • K3s:
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      sudo kubectl create -f dashboard.admin-user.yml -f dashboard.admin-user-role.yml
      

Accessing the dashboard

Accessing the dashboard is tricky because you need to both access over HTTPS, or via localhost (i.e. from the same machine). You also need to get a token to authorise your access with. I will show how to access remotely over HTTPS (do not do this if your cluster is on a public network!):

  1. On the primary cluster node edit the kubernetes-dashboard service:

    • K3s
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      sudo env EDITOR=nano kubectl edit service kubernetes-dashboard -n kubernetes-dashboard
      
    1. Move the cursor down to the line that includes type: ClusterIP and change it to type: NodePort with the same indentation. (This is the configuration path .spec.type)

    2. Save and exit the editor with ctrl+x followed by y to indicate that we want to save the file and finally enter to confirm.

  2. On the primary cluster node run the following to determine the port number to connect to the Web UI:

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    sudo kubectl get service kubernetes-dashboard -n kubernetes-dashboard
    

    In my installation this prints:

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    NAME                   TYPE       CLUSTER-IP     EXTERNAL-IP   PORT(S)         AGE
    kubernetes-dashboard   NodePort   10.43.128.69   <none>        443:31235/TCP   126m
    

    The important part is the PORT column which has the value 443:31235 here. The second number, after the colon (here it is 31235), is the port we will use to connect. The hostname is the primary node address. In my case this will mean an address of https://k8s-1:31235/. Load this address in your web browser and accept the warning about a self-signed security certificate to load the UI.

  3. On the primary cluster node run the following to get your token:

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      echo $(sudo kubectl -n kubernetes-dashboard get secret $(sudo kubectl -n kubernetes-dashboard get sa/admin-user -o jsonpath="{.secrets[0].name}") -o go-template="{{.data.token | base64decode}}")
      

    Copy and paste the output into the field on the Web UI login screen.

You should now be able to navigate to the nodes item in the left-hand menu of the UI to see your nodes:

Screenshot of the Web UI Dashboard showing the nodes view

Other chapters in this series

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