Configure Tanzu Kubernetes Grid to use Active Directory

Tanzu Kubernetes Grid includes and supports packages for dex and Gangway.  These are used to extend authentication to LDAP and OIDC endpoints.  Recall that Kubernetes does not do user-management or traditional authentication.  As a K8s cluster admin, you can create service accounts of course, but those are not meant to be used by developers.

Think of dex as a transition layer, it uses ‘connectors’ for upstream Identity providers (IdP) like Active Directory for LDAP or Okta for SAML and presents an OpenID Connect (OIDC) endpoint for k8s to use.

TKG provides not only the packages mentioned above, but also a collection of yaml files and documentation for implementation.  The current version (as of May 12, 2020) documentation for configuring authentication is pretty general, the default values in the config files are suitable for OpenLDAP.  So, I thought I’d share the specific settings for connecting dex to Active Directory.

Assumptions:

    1. TKG Management cluster is deployed
    2. Following the VMware documentation
    3. Using the TKG-provided tkg-extensions
    4. dex will be deployed to management cluster or to a specific workload cluster

Edits to authentication/dex/vsphere/ldap/03-cm.yaml – from Docs

  1. Replace <MGMT_CLUSTER_IP> with the IP address of one of the control plane nodes of your management cluster.  This is one of the control plane nodes where we’re putting dex
  2. If the LDAP server is listening on the default port 636, which is the secured configuration, replace <LDAP_HOST> with the IP or DNS address of your LDAP server. If the LDAP server is listening on any other port, replace <LDAP_HOST> with the address and port of the LDAP server, for example 192.168.10.22:389 or ldap.mydomain.com:389.  Never, never, never use unencrypted LDAP.  You’ll need to specify port 636 unless your targeted AD controller is also a Global Catalog server in which case you’ll specify port 3269.  Check with the AD team if you’re unsure.
  3. If your LDAP server is configured to listen on an unsecured connection, uncomment insecureNoSSL: true. Note that such connections are not recommended as they send credentials in plain text over the network. Never, never, never use unencrypted LDAP.
  4. Update the userSearch and groupSearch parameters with your LDAP server configuration.  This need much more detail – see steps below

Edits to authentication/dex/vsphere/ldap/03-cm.yaml – AD specific

  1. Obtain the root CA public certificate for your AD controller. Save a base64-encoded version of the certificate: echo root64.cer | base64 > rootcer.b64 for example will write the data from the PEM-encoded root64.cer file into a base64-encoded file named rootcer.b64
  2. Add the base64-encoded certificate content to the rootCAData key.  Be sure to remove the leading “#”.  This is an alternative to using the rootCA key, where we’ll have to place the file on each Control Plane node
  3. Update the userSearch values as follows:
    key default set to notes
    baseDN ou=people,

    dc=vmware,dc=com

    DN of OU in AD under

    which user accounts are found

    Example: ou=User Accounts,DC=ragazzilab,DC=com
    filter “(objectClass=

    posixAccount)”

    “(objectClass=person)”
    username uid userPrincipalName
    idAttr uid DN Case-sensitive
    emailAttr mail userPrincipalName
    nameAttr givenName cn
  4. Update the groupSearch values as follows:
    key default set to notes
    baseDN ou=people,

    dc=vmware,dc=com

    DN of OU in AD under

    which security Groups are found

    Example: DC=ragazzilab,DC=com
    filter “(objectClass=

    posixGroup)”

    “(objectClass=group)”
    userAttr uid DN Case-Sensitive
    groupAttr memberUid “member:1.2.840.113556.1.4.1941:” This is necessary to search within nested groups in AD
    nameAttr cn cn

Other important Notes
When you create the oidc secret in the workload clusters running Gangway, the clientSecret value is base64-encoded, but the corresponding secret for the workload cluster in the staticClients section of the dex configmMap is decoded. This can be confusing since the decoded value is also randomly-generated.

Replicating images from DockerHub to Harbor

Harbor LogoI found the documentation for actually replicating images from DockerHub to a local Harbor instance to be missing.  So here’s what I’ve found:

Objective: Replicate the images for the Yelb sample application to local Harbor repo

Set-up and Prereqs

  1. A local Harbor instance – I’ll be using an Enterprise PKS foundation with Harbor 1.10
  2. An account for DockerHub

Steps

      1. Login to Harbor Web GUI as an administrator. Navigate to Administration/Registries
      2. Add Endpoint for local Harbor by clicking ‘New Endpoint’ and entering the following:
        • Provider: harbor
        • Name: local (or FQDN or whatever)
        • Description: optional
        • Endpoint URL: the actual URL for your harbor instance beginning with https and ending with :443
        • Access ID: username for an admin or user that at least has Project Admin permission to the target Projects/namespaces
        • Access Secret: Password for the account above
        • Verify Remote Cert: typically checked
      3. Add Endpoint for Docker Hub by clicking ‘New Endpoint’ and entering the following:
        • Provider: docker-hub
        • Name: dockerhub (or something equally profound)
        • Description: optional
        • Endpoint URL: pre-populated/li>
        • Access ID: username for your account at dockerhub
        • Access Secret: Password for the account above
        • Verify Remote Cert: typically checked

        Notice that this is for general dockerhub, not targeting a particular repo.

      4. Configure Replications for the Yelb Images
        You may create replications for several images at once using a variety of filters, but I’m going to create a replication rule for each image we need. I think this makes it easier to identify a problem, removes the risk of replicating too much and makes administration easier. Click ‘New Replication Rule‘ enter the following to create our first rule:

        • Name: yelb-db-0.5
        • Description: optional
        • Replication Mode: Pull-based (because we’re pulling the image from DockerHub)
        • Source registry: dockerhub
        • Source Registry Filter – Name: mreferre/yelb-db
        • Source Registry Filter – Tag: 0.5
        • Source Registry Filter – Resource: pre-populated
        • Destination Namespace: yelb (or whatever Project you want the images saved to)
        • Trigger Mode: Select ‘Manual’ for a one-time sync or select ‘Scheduled’ if you want to ensure the image is replicated periodically. Note that the schedule format is cron with seconds, so 0 0 23 * * 5 would trigger the replication to run every Friday at 23:00:00. Scheduled replication makes sense when the tag filter is ‘latest’ for example
        • Override: leave checked to overwrite the image if it already exists
        • Enable rule: leave checked to keep the rule enabled
      5. Add the remaining Replication Rules:
        Name Name Filter Tag Filter Dest Namespace
        yelb-ui-latest mreferre/yelb-ui latest yelb
        yelb-appserver-latest mreferre/yelb-appserver latest yelb
        redis-4.0.2 library/redis 4.0.2 yelb

        Note that redis is an official image, so we have to include library/

Adding a private Docker registry to a PKS 1.5 Windows Kubernetes cluster

Pivotal Container Service (PKS) 1.5 and Kubernetes 1.14 bring *beta* support for Workers running Windows.  This means that we can provide the advantages of Kubernetes to a huge array of applications running on Windows.  I see this especially useful for Windows applications that you don’t have the source code for and/or do not want to invest in reworking it for .NET core or languages that run on Linux.

In nearly all cases, you’ll need an image with your applications’ dependencies or configuration and in the real world, we don’t want those in the public space like dockerhub.  Enter Private Docker Repositories.

PKS Enterprise includes VMware Harbor as a private registry, it’s very easy to deploy alongside PKS and provides a lot of important functionality.  The Harbor interface uses TLS/SSL; you may use a self-signed, enterprise PKI-signed or public CA-signed certificate.  If you chose to not use a public CA-signed certificate ($!), the self-signed or PKI-signed certificate must be trusted by the docker engine on each Kubernetes worker node.

Clusters based on Ubuntu Xenial Stemcells:

  • The operator/administrator simply puts the CA certificate into the “Trusted Certificates” box of the Security section in Ops Manager.
  • When BOSH creates the VMs for kubernetes clusters, the trusted certificates are added to the certificate store automatically.
  • If using an enterprise PKI where all of the internal certificates are signed by the Enterprise CA, this method makes it very easy to trust and “un-trust” CAs.

Clusters based on Windows 2019 Stemcells:

This is one of those tasks that is easier to perform on Linux that it is on Windows.  Unfortunately, Windows does not automatically add the Trusted Certificates from Ops Manager to the certificate store, so extra steps are required.

    1. Obtain the Registry CA Certificate.  In Harbor, you may click the “REGISTRY CERTIFICATE” link while in a Project.  Save the certificate to where the BOSH cli is installed (Ops Manager typically).
    2.  Connect BOSH cli to director.  This may be done on the Ops Manager.
    3. List BOSH-managed vms to identify the service_instance deployment corresponding to the targeted K8s cluster by matching the VM IP address to the IP address of the master node as reported by PKS cluster.
    4. Run this command to copy the certificate to the Windows worker
      bosh -e ENV -d DEPLOYMENT scp root.cer WINDOWS-WORKER:/
      • ENV – your environment alias in the BOSH cli
      • DEPLOYMENT – the BOSH deployment that corresponds to the k8s cluster; ex: service-instance_921bd35d-c46d-4e7a-a289-b577ff743e15
      • WINDOWS-WORKER – the instance name of the specific Windows worker VM; ex: windows-worker/277536dd-a7e6-446b-acf7-97770be18144

      This command copies the local file named root.cer to the root folder on the Windows VM

    5. Use BOSH to SSH into the Windows Worker.
      bosh -e ENV -d DEPLOYMENT ssh WINDOWS-WORKER
      • ENV – your environment alias in the BOSH cli
      • DEPLOYMENT – the BOSH deployment that corresponds to the k8s cluster; ex: service-instance_921bd35d-c46d-4e7a-a289-b577ff743e15
      • WINDOWS-WORKER – the instance name of the specific Windows worker VM; ex: windows-worker/277536dd-a7e6-446b-acf7-97770be18144

      SSH into Windows node, notice root.cer on the filesystem
    6. In the Windows SSH session run “powershell.exe” to enter powershell
    7. At the PS prompt, enter
      Import-certificate -filepath .\root.cer -CertStoreLocation 
      Cert:\LocalMachine\Root

      The example above imports the local file “root.cer” into the Trusted Root Certificate Store

    8. Type “exit” twice to exit PS and SSH
    9. Repeat steps 5-8 for each worker node.

Add docker-registry secret to k8s cluster

Whether the k8s cluster is running Windows workers or not, you’ll want to add credentials for authenticating to harbor.  These credentials are stored in a secret. To add the secret, use this command:

kubectl create secret docker-registry harbor \
--docker-server=HARBOR_FQDN \
--docker-username=HARBOR_USER \
--docker-password=USER_PASS \
--docker-email=USER_EMAIL
  • HARBOR_FQDN – FQDN for local/private Harbor registry
  • HARBOR_USER – name of user in Harbor with access to project and repos containing the desired images
  • USER_PASS – username for the above account
  • USER_EMAIL – email adddress for the above account

Note that this secret is namespaced; it needs to be added to the namespace of the deployments that will reference it

More info

Here’s an example deployment yaml for a Windows K8s cluster that uses a local private docker registry.  Note that Windows clusters cannot leverage NSX-T yet, so this example uses a NodePort to expose the service.

Logging into a Kubernetes cluster with an OIDC LDAP account

I confess, most of my experience with Kubernetes is with Pivotal Container Service (PKS) Enterprise.  PKS makes it rather easy to get started and I found that I took some tasks for granted.

In PKS Enterprise, one can use the pks cli to not only life-cycle clusters, but to obtain the credentials to the cluster and automatically update the kubeconfig with the account information.  So, administrative/operations users can run the command “pks get-credentials my-cluster” to have a kubeconfig updated with the authentication tokens and parameters to connect to my-cluster.

K8s OIDC using UAA on PKS

The PKS controller includes the User Account and Authentication (UAA) component, which is used to authenticate users into PKS Enterprise.  UAA can also be easily configured to connect to an existing LDAP service – this is the desired configuration in most organizations so that users account exist in one place (Active Directory in my example).

So, I found myself wondering “I don’t want to provide the PKS CLI to developers, so how can they connect kubectl to the cluster?”

Assumptions:

  • PKS Enterprise on vSphere (with or without NSX-T)
  • Active Directory
  • Developer user account belongs to the k8s-devs security group in AD

Prerequisite configuration:

  1. UAA on PKS configured a with UAA User Account Store: LDAP Server.  This links UAA to LDAP/Active Directory
  2. User Search Filter: userPrincipalName={0}  This means that users can login as user@domain.tld
  3. Group Search Filter: member={0} This ensures that AD groups may be used rather than specifying individual users
  4. Configure created clusters to use UAA as the OIDC provider: Enabled  This pre-configures the kubernetes API to use OpenID Connect with UAA. If not using PKS Enterprise, you’ll need to provide another OpenID Connect-Compliant endpoint (like Dex), link it to Active Directory and update the kubernetes cluster api manually to use the OpenID Authentication.

 

Operator: Create Role and RoleBinding:

While authentication is handled by OIDC/UAA/LDAP, Authorization must be configured on the cluster to provide access to resources via RBAC.  This is done by defining a Role (or clusterRole) that indicates what actions may be taken on what resources and a RoleBinding which links the Role to one or more “subjects”.

  1.  Authenticate to kubernetes cluster with an administrative account (for example, using PKS cli to connect)
  2.  Create yaml file for our Role and RoleBinding:
    kind: Role
    apiVersion: rbac.authorization.k8s.io/v1
    metadata:
      name: developers
    rules:
    - apiGroups: ["", "extensions", "apps"]
      resources: ["deployments", "replicasets", "pods"]
      verbs: ["get", "list", "watch", "create", "update", "patch", "delete"] 
      # You can also use ["*"]
    ---
    kind: RoleBinding
    apiVersion: rbac.authorization.k8s.io/v1beta1
    metadata:
      name: developer-dev-binding
    subjects:
    - kind: Group
      name: k8s-devs
      apiGroup: rbac.authorization.k8s.io
    roleRef:
      kind: Role
      name: developers
      apiGroup: rbac.authorization.k8s.io
    

    In the example above, we’re creating a Role named “developers”, granting access to the core, extensions and apps API groups and several actions against deployments, replicaSets and pods. Notice that developers in this role would have have access to secrets (for example)
    The example RoleBinding binds a group named “k8s-devs” to the developers role. Notice that we have not created the k8s-devs group in Kubernetes or UAA; it exists in Active Directory

  3. Use Kubectl to apply the yaml, creating the Role and Rolebinding in the targeted namespace

 

Creating the kubeconfig – the hard way

To get our developer connected with kubectl, they’ll need a kubeconfig with the authentication and connection details.  The Hard way steps are:

  1. Operator obtains the cluster’s certificate authority data.  This can be done via curl or by copying the value from the existing kubeconfig.
  2. Operator creates a template kubeconfig, replacing the value specified, then sends it to the developer user
    apiVersion: v1
    clusters:
    - cluster:
      certificate-authority-data: <OBTAINED IN STEP 1 >
      server: < FQDN to Master Node. >
      name: PROVIDED-BY-ADMIN
    contexts:
    - context:
        cluster: PROVIDED-BY-ADMIN
        user: PROVIDED-BY-USER
      name:  PROVIDED-BY-ADMIN
    current-context: PROVIDED-BY-ADMIN
    kind: Config
    preferences: {}
    users:
    - name: PROVIDED-BY-USER
      user:
        auth-provider:
          config:
            client-id: pks_cluster_client
            cluster_client_secret: ""
            id-token: PROVIDED-BY-USER
            idp-issuer-url: https://PROVIDED-BY-ADMIN:8443/oauth/token
            refresh-token:  PROVIDED-BY-USER
          name: oidc
  3. The developer user obtains the id_token and refresh_token from UAA, via a curl command
    curl 'https://PKS-API:8443/oauth/token' -k -XPOST -H
    'Accept: application/json' -d "client_id=pks_cluster_client&client_secret=""&grant_type=password&username=UAA-USERNAME&response_type=id_token" --data-urlencode password=UAA-PASSWORD
  4. The developer user updates the kubeconfig with the id_token and refresh token in the kubeconfig

 

Creating the kubeconfig – the easy way

Assuming the developer is using Mac or Linux…

  1. Install jq on developer workstation
  2. Download the get-pks-k8s-config.sh script, make it executable (chmod +x get-pks.k8s.config.sh)
  3. Execute the script (replace the params with your own)
    ./get-pks-k8s-config.sh --API=api.pks.mydomain.com \
    --CLUSTER=cl1.pks.mydomain.com \
    --USER=dev1@mydomain.com \
    --NS=scratch
    • API – FQDN to PKS Controller, for UAA
    • CLUSTER – FQDN to master node of k8s cluster
    • USER – userPrincipalName for the user
    • NS – Namespace to target; optional
  4. After entering the user’s password, the script will set the params in the kubeconfig and switch context automatically

Try it out
Our developer user should able to “see” pods but not namespaces for example:

dev1 can see pods but not namespaces

 

Creating the kubeconfig – the easiest way

  1. Provide the developer with the PKS CLI tool, remember we have not added them to any group or role with PKS admin permissions.
  2. Provide the developer with the PKS API endpoint FQDN and the cluster name
  3. The developer may run this command to generate the updated kubeconfig and set the current context
    pks get-kubeconfig CLUSTERNAME -a API -u USER -k

    • CLUSTERNAME is the name of the cluster
    • API – FQDN to PKS Controller
    • USER – userPrincipalName for the user
  4. You’ll be prompted for the account password. Once entered, the tool will fetch the user-specific kubeconfig.
Use PKS CLI to get the kubeconfig

 

Manually creating a Kubernetes cluster with kubeadm

I’ve talked about Pivotal Container Service (PKS) before and now work for Pivotal, so I’ve frequently got K8s on my mind.  I’ve discussed at length the benefits of PKS and the creation of K8s clusters, but didn’t have much of a point of reference for alternatives.  I know about Kelsey Hightower’s book and was looking for something a little less in-the-weeds.

Enter kubeadm, included in recent versions of K8s.  With this tool, you’re better able to understand what goes into a cluster, how the master and workers are related and how the networking is organized.  I really wanted to stand up a K8s cluster alongside a PKS-managed cluster in order to better understand the differences (if any).  This is also a part of the Linux Foundation training “Kubernetes Fundamentals”.  I don’t want to spoil the course for you, but will point to some of the docs on kubernetes.io

 

Getting Ready

I used VMware Fusion on the Macbook to create and run two Ubuntu 18.04 VMs.  Each was a linked clone with 2GB RAM, 1vCPU.  Had to make sure that they had different MAC addresses, IP, UUIDs and host names. I’m sure you can use nearly any virtualization tool to get your VMs running.  Once running, be sure you can SSH into each.

Install Docker

I thought, “hey I’ve done this before” and just installed Docker as per usual, but that method does not leverage the correct cgroup driver, so we’ll want to install Docker with the script found here.

Install Tools

Once again, the kubernetes.io site provides commands to properly install kubeadm, kubelet and kubectl on our Ubuntu nodes.  Use the commands on that page to ensure kubelet is installed and held to the correct version.

Choose your CNI pod network

Ok, what?  CNI is the Container Network Interface is a specification for networking add-ons for K8s.  Kubeadm requires that we use a pod network addon that uses the CNI spec.  The pod network – we may have only one per k8s cluster – is the network that the pods communicate on; think of it as using a NAT rather than the network you’ve actually assigned to the Ubuntu nodes.  Further, this can be confusing, because this address space is not what is actually assigned to the pods.  This address space is used when we “expose” a service.  What pod-network-cidr you assign depends on which network add-on you select.  In my case, I went with Canal as it seems to be both powerful and flexible.  Also, the pod-network cidr used by Calico is “192.168.0.0/16”, which is already in use in my home lab – it may not have actually been a conflict, but it certainly would be confusing if it were in use twice.

Create the master node
Make sure you’re ssh’d into your designated “Master” Ubuntu VM, make sure that you’ve installed kubeadm, kubelet, kubectl and docker from the steps above.  If you also choose canal, you’ll initialize the master node (not on the worker node – we’ll have a different command for that one) by running

kubeadm init –pod-network-cidr=10.244.0.0/16

Exactly that CIDR. It’ll take a few minutes to download, install and configure the k8s components.  When the initialization has completed, you’ll see a message like this:

Your Kubernetes control-plane has initialized successfully!

To start using your cluster, you need to run the following as a regular user:

mkdir -p $HOME/.kube
sudo cp -i /etc/kubernetes/admin.conf $HOME/.kube/config
sudo chown $(id -u):$(id -g) $HOME/.kube/config

You should now deploy a pod network to the cluster.
Run “kubectl apply -f [podnetwork].yaml” with one of the options listed at:
https://kubernetes.io/docs/concepts/cluster-administration/addons/

Then you can join any number of worker nodes by running the following on each as root:

kubeadm join 192.168.1.129:6443 –token zdjzrp.5jad4gihqjo46olg \
–discovery-token-ca-cert-hash sha256:90d1b349aa93a7130ee91668e4e763a4c29e5fc1502060191b38ea0e31d3cec8

Using, this, we’ll exit su and run the

mkdir -p $HOME/.kube
sudo cp -i /etc/kubernetes/admin.conf $HOME/.kube/config
sudo chown $(id -u):$(id -g) $HOME/.kube/config

Make a note of the bottom section as we’ll need it in order to join our worker to the newly-formed cluster.

Sanity-check:

On the master, run kubectl get nodes.  you’ll notice that we have 1 node and it’s not ready:

Install the network pod add-on

Referencing the docs, you’ll note that Canal has a couple yaml files to be applied to our cluster.  So, again on our master node, we’ll run these commands to install and configure Canal:


kubectl apply -f https://docs.projectcalico.org/v3.3/getting-started/kubernetes/installation/hosted/canal/rbac.yaml
kubectl apply -f https://docs.projectcalico.org/v3.3/getting-started/kubernetes/installation/hosted/canal/canal.yaml

Sanity-check:

On the master, run kubectl get nodes.  You’ll now notice that we still have 1 node but now it’s ready:

Enable pod placement on master
By default, the cluster will not put pods on the master node. If you want to use a single-node cluster or use compute capacity on the master node for pods, we’ll need to remove the taint.

Default taint on master

We’ll remove the taint with the command

kubectl taint nodes –all node-role.kubernetes.io/master-

Join worker to cluster
You saved the output from kubeadm init earlier, right? We’ll need that now to join the worker to the cluster. On the worker VM, become root via sudo su – and run that command:

Join worker to cluster

Now, back on master, we run kubectl get nodes and can see both nodes!

Master and Worker Ready

Summary and Next Steps

At this point, we have a functional kubernetes cluster with 1 master and 1 worker.  Next in this series, we’ll deploy some applications and compare the behavior to a PKS-managed kubernetes cluster.

 

Using Helm and Dynamic PersistentVolumes with Multi-AZ PKS on vSphere

So, you’ve installed PKS and created a PKS cluster.  Excellent!  Now what?

We want to use helm charts to deploy applications.  Many of the charts use PersistentVolumes, so getting PVs set up is our first step.

There are a couple of complicating factors to be aware of when it comes to PVs in a multi-AZ/multi-vSphere-Cluster environment.  First, you probably have cluster-specific datastores – particularly if you are using Pivotal Ready Architecture and VSAN.  These datastores are not suitable for PersistentVolumes consumed by applications deployed to our Kubernetes cluster.  To work-around this, we’ll need to provide some shared block storage to each host in each cluster.  Probably the simplest way to do this is with an NFS share.

Prerequisites:

Common datastore; NFS share or iSCSI

In production, you’ll want a production-quality fault-tolerant solution for NFS or iSCSI, like Dell EMC Isilon. For this proof-of-concept, I’m going to use an existing NFS server, create a volume and share it to the hosts in the three vSphere clusters where the PKS workload VMs will run.  In this case, the NFS datastore is named “sharednfs” ’cause I’m creative like that.  Make sure that your hosts have adequate permissions to the share.  Using VMFS on iSCSI is supported, just be aware that you may need to cable-up additional NICs if yours are already consumed by N-VDS and/or VSAN.

Workstation Prep

We’ll need a handful of command-line tools, so make sure your workstation has the PKS CLI and Kubectl CLI from Pivotal and you’ve downloaded and extracted Helm.

PKS Cluster
We’ll want to provision a cluster using the PKS CLI tool.  This document assumes that your cluster was provisioned successfully, but nothing else has been done to it.  For my environment, I configured the “medium” plan to use 3 Masters and 3 Workers in all three AZs, then created the cluster with the command

pks create-cluster pks1cl1 --external-hostname cl1.pks1.lab13.myenv.lab --plan "medium" --num-nodes "3"


Logged-in
Make sure you’re logged into the Kubernetes cluster. In PKS, the easiest way to do this is via the PKS cli:

pks login -a api.pks1.lab13.myenv.lab -u pksadmin -p my_password --skip-ssl-validation
pks cluster pks1cl1
pks get-credentials pks1cl1
kubectl config use-context pks1cl1
kubectl get nodes -o wide

Where “pks1cl1″ is replaced by your cluster’s name,”api.pks1.lab13.myenv.lab” is replaced by the FQDN to your PKS API server, “pksadmin” is replaced by the username with admin rights to PKS and “my_password” is replaced with that account’s password.

Procedure:

  1. Create storageclass
    • Create storageclass spec yaml. Note that the file is named storageclass-nfs.yml and we’re naming the storage class itself “nfs”:
      kind: StorageClass
      apiVersion: storage.k8s.io/v1
      metadata:
        name: nfs
        annotations:
          storageclass.kubernetes.io/is-default-class: "true"
      provisioner: kubernetes.io/vsphere-volume
      parameters:
        diskformat: thin
        datastore: sharednfs
        fstype: ext3
      

    • Apply the yml with kubectl

      kubectl create -f storageclass-nfs.yml

    • Create a sample PVC (Persistent Volume Claim). Note that the file is names pvc-sample.yml, the PVC name is “pvc-sample” and uses the “nfs” storageclass we created above. This step is not absolutely necessary, but will help confirm we can use the storage.
      kind: PersistentVolumeClaim
      apiVersion: v1
      metadata:
        name: pvc-sample
        annotations:
          volume.beta.kubernetes.io/storage-class: nfs
      spec:
        accessModes:
          - ReadWriteOnce
        resources:
          requests:
            storage: 1Gi
        storageClassName: nfs
      
    • Apply the yml with kubectl

      kubectl create -f pvc-sample.yml


      If you’re watching vSphere closely, you’ll see a VMDK created in the kubevols folder of the NFS datastore

    • Check that the PVC was created with

      kubectl get pvc

      and

      kubectl describe pvc pvc-sample

    • Remove sample PVC with

      kubectl delete -f pvc-sample

  2. Configure Helm and Tiller
    • Create Service Account for tiller with
      apiVersion: v1
      kind: ServiceAccount
      metadata:
        name: tiller
        namespace: kube-system
      ---
      apiVersion: rbac.authorization.k8s.io/v1beta1
      kind: ClusterRoleBinding
      metadata:
        name: tiller
      roleRef:
        apiGroup: rbac.authorization.k8s.io
        kind: ClusterRole
        name: cluster-admin
      subjects:
        - kind: ServiceAccount
          name: tiller
          namespace: kube-system
      
    • Apply the service account yml with Kubectl

      kubectl create -f rbac-config.yml

    • Initialize helm and tiller with

      helm init --service-account tiller

    • Check that tiller is ready

      helm version


      Look for a version number for the version; note that it might take a few seconds for tiller in the cluster to get ready.

  3. Deploy sample helm chart
    • Update helm local chart repository. We do this so that we can be sure that helm can reach the public repo and to cache teh latest information to our local repo.

      helm repo update


      If this step results in a certificate error, you may have to add the cert to the trusted certificates on the workstation.

    • Install helm chart with ingress enabled. Here, I’ve selected the Dokuwiki app. The command below will enable ingress, so we can access it via routable IP and it will use the default storageclass we configured earlier.

      helm install --name dokuwiki \
      --set ingress.enabled="true",dokuwikiUsername=admin,dokuwikiPassword=password \
      stable/dokuwiki

      Edit – April 23 2019 – Passing the credentials in here makes connecting easier later.

    • Confirm that the app was deployed
      helm list
      kubectl get pods -n default
      kubectl get services -n default


      From the get services results, make a note of the external IP address – in the example above, it’s 192.13.6.73

    • Point a browser at the external address from the previous step and marvel at your success in deploying Dokuwiki via helm to Kubernetes!
      If you want to actually login to your Dokuwiki instance, first obtain the password for the user account with this command:

      kubectl get secret -n default dokuwiki-dokuwiki \
      -o jsonpath="{.data.dockuwiki-password}" | base64 --decode

      Then login with username “user” and that password.

       

      Edit – 04/23/19 – Login with the username and password you included in the helm install command

  4. Additional info
    • View Persistent Volume Claims with

      kubectl get pvc -n default


      This will list the PVCs and the volumes in the “default” namespace. Note the volume corresponds to the name of the VMDK on the datastore.

    • Load-Balancer
      Notice that since we are leveraging the NSX-T Container Networking Interface and enabled the ingress when we installed dokuwiki, a load-balancer in NSX-T was automatically created for us to point to the application.

This took me some time to figure out; had to weed through a lot of documentation – some of which contradicted itself and quite a bit of trial-and-error. I hope this helps save someone time later!