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2022-01-12

VMware Tanzu Community Edition Kubernetes Platform in a Homelab

Back in October, VMware announced [1] Tanzu Community Edition [2] as way to provide "a full-featured, easy-to-manage Kubernetes platform that’s perfect for users and learners alike." TCE bundles a bunch of open-source components together in a modular, "batteries included but swappable" way:

Image: Tanzu Community Edition components

[1] announced

[2] Tanzu Community Edition

I've been meaning to brush up on my Kubernetes skills so I thought deploying and using TCE in my self-contained homelab [3] would be a fun and rewarding learning exercise - and it was!

[3] homelab

Here's how I did it.

Planning

TCE supports several different deployment scenarios and targets. It can be configured as separate Management and Workload Clusters or as a single integrated Standalone Cluster, and deployed to cloud providers like AWS and Azure, on-premise vSphere, or even a local Docker environment. I'll be using the standard Management + Workload Cluster setup in my on-prem vSphere, so I start by reviewing the Prepare to Deploy a Cluster to vSphere [4] documentation to get an idea of what I'll need.

[4] Prepare to Deploy a Cluster to vSphere

Looking ahead, part of the installation process creates a local KIND [5] cluster for bootstrapping the Management and Workload clusters. I do most of my home computing (and homelab work) by using the Linux environment available on my Chromebook [6]. Unfortunately I know from past experience that KIND will not work within this environment so I'll be using a Debian 10 VM to do the deployment.

[5] KIND

[6] Linux environment available on my Chromebook

Networking

The Kubernetes node VMs will need to be attached to a network with a DHCP server to assign their addresses, and that network will need to be able to talk to vSphere. My router handles DHCP for the range `192.168.1.101-250` so I'll plan on using that.

I'll also need to set aside a few static IPs for this project. These will need to be routable and within the same subnet as the DHCP range, but excluded from that DHCP range.

| IP Address                    | Purpose                              |
|-------------------------------|--------------------------------------|
| `192.168.1.60`                | Control plane for Management cluster |
| `192.168.1.61`                | Control plane for Workload cluster   |
| `192.168.1.64 - 192.168.1.80` | IP range for Workload load balancer  |

Prerequisites

Moving on to the Getting Started [7], I'll need to grab some software before I can actually Get Started.

[7] Getting Started

Kubernetes control plane image

I need to download a VMware OVA which can be used for deploying my Kubernetes nodes from the VMWare Customer Connect portal here [8]. There are a few different options available. I'll get the Photon release with the highest Kubernetes version currently available, `photon-3-kube-v1.21.2+vmware.1-tkg.2-12816990095845873721.ova`.

[8] here

Once the file is downloaded, I'll log into my vCenter and use the **Deploy OVF Template** action to deploy a new VM using the OVA. I won't bother booting the machine once deployed but will rename it to `k8s-node` to make it easier to identify later on and then convert it to a template.

Image: New k8s-node template

Docker

I've already got Docker installed on this machine, but if I didn't I would follow the instructions here [9] to get it installed and then follow these instructions [10] to enable management of Docker without root.

[9] here

[10] these instructions

I also verify that my install is using `cgroup` version 1 as version 2 is not currently supported:

docker info | grep -i cgroup 
 Cgroup Driver: cgroupfs 
 Cgroup Version: 1

`kubectl` binary

Next up, I'll install `kubectl` as described here [11] - though the latest version is currently `1.23` and that won't work with the `1.21` control plane node image I downloaded from VMware (`kubectl` needs to be within one minor version of the control plane). Instead I need to find the latest `1.22` release.

[11] as described here

I can look at the releases page on GithHub [12] to see that the latest release for me is `1.22.5`. With this newfound knowledge I can follow the Install kubectl binary with curl on Linux [13] instructions to grab that specific version:

[12] releases page on GithHub

[13] Install kubectl binary with curl on Linux

curl -sLO https://dl.k8s.io/release/v1.22.5/bin/linux/amd64/kubectl 
sudo install -o root -g root -m 0755 kubectl /usr/local/bin/kubectl

[sudo] password for john:
kubectl version --client 
Client Version: version.Info{Major:"1", Minor:"22", GitVersion:"v1.22.5", 
  GitCommit:"5c99e2ac2ff9a3c549d9ca665e7bc05a3e18f07e", GitTreeState:"clean",
  BuildDate:"2021-12-16T08:38:33Z", GoVersion:"go1.16.12", Compiler:"gc",
  Platform:"linux/amd64"}

`kind` binary

It's not strictly a requirement, but having the `kind` executable available will be handy for troubleshooting during the bootstrap process in case anything goes sideways. It can be installed in basically the same was as `kubectl`:

curl -sLo ./kind https://kind.sigs.k8s.io/dl/v0.11.1/kind-linux-amd64 
sudo install -o root -g root -m 0755 kind /usr/local/bin/kind
kind version
kind v0.11.1 go1.16.5 linux/amd64 

Tanzu CLI

The final bit of required software is the Tanzu CLI, which can be downloaded from the project on GitHub [14].

[14] project on GitHub

curl -H "Accept: application/vnd.github.v3.raw" \ 
  -L https://api.github.com/repos/vmware-tanzu/community-edition/contents/hack/get-tce-release.sh | \
  bash -s v0.9.1 linux

And then unpack it and run the installer:

tar xf tce-linux-amd64-v0.9.1.tar.gz 
cd tce-linux-amd64-v0.9.1
./install.sh

I can then verify the installation is working correctly:

tanzu version 
version: v0.2.1 
buildDate: 2021-09-29
sha: ceaa474

Cluster creation

Okay, now it's time for the good stuff - creating some shiny new Tanzu clusters! The Tanzu CLI really does make this very easy to accomplish.

Management cluster

I need to create a Management cluster first and I'd like to do that with the UI, so that's as simple as:

tanzu management-cluster create --ui 

I should then be able to access the UI by pointing a web browser at `http://127.0.0.1:8080`... but I'm running this on a VM without a GUI, so I'll need to back up and tell it to bind on `0.0.0.0:8080` so the web installer will be accessible across the network. I can also include `--browser none` so that the installer doesn't bother with trying to launch a browser locally.

tanzu management-cluster create --ui --bind 0.0.0.0:8080 --browser none 

Validating the pre-requisites...
Serving kickstart UI at http://[::]:8080

Image: The Tanzu Installer UI

And then I can click the button at the bottom left to save my eyes before selecting the option to deploy on vSphere.

Image: Configuring the IaaS Provider

I'll plug in the FQDN of my vCenter and provide a username and password to use to connect to it, then hit the **Connect** button. That will prompt me to accept the vCenter's certificate thumbprint, and then I'll be able to select the virtual datacenter that I want to use. Finally, I'll paste in the SSH public key I'll use for interacting with the cluster.

I click **Next** and move on to the Management Cluster Settings.

Image: Configuring the Management Cluster

This is for a lab environment that's fairly memory-constrained, so I'll pick the single-node *Development* setup with a *small* instance type. I'll name the cluster `tce-mgmt` and stick with the default `kube-vip` control plane endpoint provider. I plug in the control plane endpoint IP that I'll use for connecting to the cluster and select the *small* instance type for the worker node type.

I don't have an NSX Advanced Load Balancer or any Metadata to configure so I'll skip past those steps and move on to configuring the Resources.

Image: Configuring Resources

Here I pick to place the Tanzu-related resources in a VM folder named `Tanzu`, to store their data on my single host's single datastore, and to deploy to the one-host `physical-cluster` cluster.

Now for the Kubernetes Networking Settings:

Image: Configuring Kubernetes Networking

This bit is actually pretty easy. For Network Name, I select the vSphere network where the `192.168.1.0/24` network I identified earlier lives, `d-Home-Mgmt`. I leave the service and pod CIDR ranges as default.

I disable the Identity Management option and then pick the `k8s-node` template I had imported to vSphere earlier.

Image: Configuring the OS Image

I skip the Tanzu Mission Control piece (since I'm still waiting on access to TMC Starter [15]) and click the **Review Configuration** button at the bottom of the screen to review my selections.

Image: Reviewing the configuration

[15] TMC Starter

See the option at the bottom to copy the CLI command? I'll need to use that since clicking the friendly **Deploy** button doesn't seem to work while connected to the web server remotely.

tanzu management-cluster create \ 
  --file /home/john/.config/tanzu/tkg/clusterconfigs/dr94t3m2on.yaml -v 6

In fact, I'm going to copy that file into my working directory and give it a more descriptive name so that I can re-use it in the future.

cp ~/.config/tanzu/tkg/clusterconfigs/dr94t3m2on.yaml \ 
  ~/projects/tanzu-homelab/tce-mgmt.yaml

Now I can run the install command:

tanzu management-cluster create --file ./tce-mgmt.yaml -v 6 

After a moment or two of verifying prerequisites, I'm met with a polite offer to enable Tanzu Kubernetes Grid Service in vSphere:

vSphere 7.0 Environment Detected.
You have connected to a vSphere 7.0 environment which does not have vSphere with Tanzu enabled. vSphere with Tanzu includes
an integrated Tanzu Kubernetes Grid Service which turns a vSphere cluster into a platform for running Kubernetes workloads in dedicated
resource pools. Configuring Tanzu Kubernetes Grid Service is done through vSphere HTML5 client.
Tanzu Kubernetes Grid Service is the preferred way to consume Tanzu Kubernetes Grid in vSphere 7.0 environments. Alternatively you may
deploy a non-integrated Tanzu Kubernetes Grid instance on vSphere 7.0.
Note: To skip the prompts and directly deploy a non-integrated Tanzu Kubernetes Grid instance on vSphere 7.0, you can set the 'DEPLOY_TKG_ON_VSPHERE7' configuration variable to 'true'
Do you want to configure vSphere with Tanzu? [y/N]: n
Would you like to deploy a non-integrated Tanzu Kubernetes Grid management cluster on vSphere 7.0? [y/N]: y

That's not what I'm after in this case, though, so I'll answer with a `n` and a `y` to confirm that I want the non-integrated TKG deployment.

And now I go get coffee as it'll take 10-15 minutes for the deployment to complete.

Image: Coffee break!

Okay, I'm back - and so is my shell prompt! The deployment completed successfully:

Waiting for additional components to be up and running...
Waiting for packages to be up and running...
Context set for management cluster tce-mgmt as 'tce-mgmt-admin@tce-mgmt'.
Management cluster created!

You can now create your first workload cluster by running the following:
  tanzu cluster create [name] -f [file]

Some addons might be getting installed! Check their status by running the following:
  kubectl get apps -A

I can run that last command to go ahead and verify that the addon installation has completed:

kubectl get apps -A 
NAMESPACE    NAME                   DESCRIPTION           SINCE-DEPLOY   AGE 
tkg-system   antrea                 Reconcile succeeded   26s            6m49s
tkg-system   metrics-server         Reconcile succeeded   36s            6m49s
tkg-system   tanzu-addons-manager   Reconcile succeeded   22s            8m54s
tkg-system   vsphere-cpi            Reconcile succeeded   19s            6m50s
tkg-system   vsphere-csi            Reconcile succeeded   36s            6m50s

And I can use the Tanzu CLI to get some other details about the new management cluster:

tanzu management-cluster get tce-mgmt 
  NAME      NAMESPACE   STATUS   CONTROLPLANE  WORKERS  KUBERNETES        ROLES 
  tce-mgmt  tkg-system  running  1/1           1/1      v1.21.2+vmware.1  management

Details:
NAME                                                         READY  SEVERITY  REASON  SINCE  MESSAGE
/tce-mgmt                                                    True                     40m
├─ClusterInfrastructure - VSphereCluster/tce-mgmt            True                     41m
├─ControlPlane - KubeadmControlPlane/tce-mgmt-control-plane  True                     40m
│ └─Machine/tce-mgmt-control-plane-xtdnx                     True                     40m
└─Workers
  └─MachineDeployment/tce-mgmt-md-0
    └─Machine/tce-mgmt-md-0-745b858d44-4c9vv                 True                     40m

Providers:
  NAMESPACE                          NAME                    TYPE                    PROVIDERNAME  VERSION  WATCHNAMESPACE
  capi-kubeadm-bootstrap-system      bootstrap-kubeadm       BootstrapProvider       kubeadm       v0.3.23
  capi-kubeadm-control-plane-system  control-plane-kubeadm   ControlPlaneProvider    kubeadm       v0.3.23
  capi-system                        cluster-api             CoreProvider            cluster-api   v0.3.23
  capv-system                        infrastructure-vsphere  InfrastructureProvider  vsphere       v0.7.10 

Excellent! Things are looking good so I can move on to create the cluster which will actually run my workloads.

Workload cluster

I won't use the UI for this but will instead take a copy of my `tce-mgmt.yaml` file and adapt it to suit the workload needs (as described here [16]).

[16] here

cp tce-mgmt.yaml tce-work.yaml 
vi tce-work.yaml

I only need to change 2 of the parameters in this file:

I *could* change a few others if I wanted to

After saving my changes to the `tce-work.yaml` file, I'm ready to deploy the cluster:

tanzu cluster create --file tce-work.yaml 
Validating configuration...  
Warning: Pinniped configuration not found. Skipping pinniped configuration in workload cluster. Please refer to the documentation to check if you can configure pinniped on workload cluster manually
Creating workload cluster 'tce-work'...
Waiting for cluster to be initialized...
Waiting for cluster nodes to be available...
Waiting for addons installation...
Waiting for packages to be up and running...
Workload cluster 'tce-work' created 

Right on! I'll use `tanzu cluster get` to check out the workload cluster:

tanzu cluster get tce-work 
  NAME      NAMESPACE  STATUS   CONTROLPLANE  WORKERS  KUBERNETES        ROLES 
  tce-work  default    running  1/1           1/1      v1.21.2+vmware.1  <none>
â„ą
Details:
NAME                                                         READY  SEVERITY  REASON  SINCE  MESSAGE
/tce-work                                                    True                     9m31s
├─ClusterInfrastructure - VSphereCluster/tce-work            True                     10m
├─ControlPlane - KubeadmControlPlane/tce-work-control-plane  True                     9m31s
│ └─Machine/tce-work-control-plane-8km9m                     True                     9m31s
└─Workers
  └─MachineDeployment/tce-work-md-0
    └─Machine/tce-work-md-0-687444b744-cck4x                 True                     8m31s 

I can also go into vCenter and take a look at the VMs which constitute the two clusters:

Image: Cluster VMs

I've highlighted the two Control Plane nodes. They got their IP addresses assigned by DHCP, but VMware says [17] that I need to create reservations for them to make sure they don't change. So I'll do just that.

Image: DHCP reservations on Google Wifi

[17] VMware says

Excellent, I've got a Tanzu management cluster and a Tanzu workload cluster. What now?

Working with Tanzu

If I run `kubectl get nodes` right now, I'll only get information about the management cluster:

kubectl get nodes 
NAME                             STATUS   ROLES                  AGE   VERSION 
tce-mgmt-control-plane-xtdnx     Ready    control-plane,master   18h   v1.21.2+vmware.1
tce-mgmt-md-0-745b858d44-4c9vv   Ready    <none>                 17h   v1.21.2+vmware.1

Setting the right context

To be able to deploy stuff to the workload cluster, I need to tell `kubectl` how to talk to it. And to do that, I'll first need to use `tanzu` to capture the cluster's kubeconfig:

tanzu cluster kubeconfig get tce-work --admin 
Credentials of cluster 'tce-work' have been saved 
You can now access the cluster by running 'kubectl config use-context tce-work-admin@tce-work'

I can now run `kubectl config get-contexts` and see that I have access to contexts on both management and workload clusters:

kubectl config get-contexts 
CURRENT   NAME                      CLUSTER    AUTHINFO         NAMESPACE 

          tce-work-admin@tce-work   tce-work   tce-work-admin

And I can switch to the `tce-work` cluster like so:

kubectl config use-context tce-work-admin@tce-work 
Switched to context "tce-work-admin@tce-work". 
kubectl get nodes 
NAME                             STATUS   ROLES                  AGE   VERSION 
tce-work-control-plane-8km9m     Ready    control-plane,master   17h   v1.21.2+vmware.1
tce-work-md-0-687444b744-cck4x   Ready    <none>                 17h   v1.21.2+vmware.1

There they are!

Deploying the `yelb` demo app

Before I move on to deploying actually *useful* workloads, I'll start with deploying a quick demo application as described in William Lam's post on Interesting Kubernetes application demos [18]. `yelb` is a web app which consists of a UI front end, application server, database server, and Redis caching service so it's a great little demo to make sure Kubernetes is working correctly.

[18] Interesting Kubernetes application demos

I can check out the sample deployment that William put together here [19], and then deploy it with:

[19] here

kubectl create ns yelb 
namespace/yelb created 
kubectl apply -f https://raw.githubusercontent.com/lamw/vmware-k8s-app-demo/master/yelb.yaml 
service/redis-server created 
service/yelb-db created
service/yelb-appserver created
service/yelb-ui created
deployment.apps/yelb-ui created
deployment.apps/redis-server created
deployment.apps/yelb-db created
deployment.apps/yelb-appserver created

kubectl -n yelb get pods 
NAME                             READY   STATUS    RESTARTS   AGE 
redis-server-74556bbcb7-r9jqc    1/1     Running   0          10s
yelb-appserver-d584bb889-2jspg   1/1     Running   0          10s
yelb-db-694586cd78-wb8tt         1/1     Running   0          10s
yelb-ui-8f54fd88c-k2dw9          1/1     Running   0          10s

Once the app is running, I can point my web browser at it to see it in action. But what IP do I use?

kubectl -n yelb get svc/yelb-ui 
NAME             TYPE        CLUSTER-IP       EXTERNAL-IP   PORT(S)        AGE 
yelb-ui          NodePort    100.71.228.116   <none>        80:30001/TCP   84s

This demo is using a `NodePort` type service to expose the front end, which means it will be accessible on port `30001` on the node it's running on. I can find that IP by:

kubectl -n yelb describe pod $(kubectl -n yelb get pods | grep yelb-ui | awk '{print $1}') | grep "Node:" 
Node:         tce-work-md-0-687444b744-cck4x/192.168.1.145 

So I can point my browser at `http://192.168.1.145:30001` and see the demo:

Image: yelb demo page

After marveling at my own magnificence for a few minutes, I'm ready to move on to something more interesting - but first, I'll just delete the `yelb` namespace to clean up the work I just did:

kubectl delete ns yelb 
namespace "yelb" deleted 

Now let's move on and try to deploy `yelb` behind a `LoadBalancer` service so it will get its own IP. William has a deployment spec [20] for that too.

[20] deployment spec

kubectl create ns yelb 
namespace/yelb created 
kubectl apply -f https://raw.githubusercontent.com/lamw/vmware-k8s-app-demo/master/yelb-lb.yaml 
service/redis-server created 
service/yelb-db created
service/yelb-appserver created
service/yelb-ui created
deployment.apps/yelb-ui created
deployment.apps/redis-server created
deployment.apps/yelb-db created
deployment.apps/yelb-appserver created
kubectl -n yelb get pods 
NAME                             READY   STATUS    RESTARTS   AGE 
redis-server-74556bbcb7-q6l62    1/1     Running   0          7s
yelb-appserver-d584bb889-p5qgd   1/1     Running   0          7s
yelb-db-694586cd78-hjtn4         1/1     Running   0          7s
yelb-ui-8f54fd88c-pm9qw          1/1     Running   0          7s

And I can take a look at that service...

kubectl -n yelb get svc/yelb-ui 
NAME      TYPE           CLUSTER-IP       EXTERNAL-IP   PORT(S)        AGE 
yelb-ui   LoadBalancer   100.67.177.185   <pending>     80:32339/TCP   15s

Wait a minute. That external IP is *still* `<pending>`. What gives? Oh yeah I need to actually deploy and configure a load balancer before I can balance anything. That's up next.

Deploying `kube-vip` as a load balancer

Fortunately, William Lam wrote up some tips [21] for handling that too. It's based on work by Scott Rosenberg [22]. The quick-and-dirty steps needed to make this work are:

[21] wrote up some tips

[22] based on work by Scott Rosenberg

git clone https://github.com/vrabbi/tkgm-customizations.git 
cd tkgm-customizations/carvel-packages/kube-vip-package
kubectl apply -n tanzu-package-repo-global -f metadata.yml
kubectl apply -n tanzu-package-repo-global -f package.yaml
cat << EOF > values.yaml 
vip_range: 192.168.1.64-192.168.1.80
EOF
tanzu package install kubevip -p kubevip.terasky.com -v 0.3.9 -f values.yaml 

Now I can check out the `yelb-ui` service again:

kubectl -n yelb get svc/yelb-ui 
NAME      TYPE           CLUSTER-IP       EXTERNAL-IP    PORT(S)        AGE 
yelb-ui   LoadBalancer   100.67.177.185   192.168.1.65   80:32339/TCP   4h35m

And it's got an IP! I can point my browser to `http://192.168.1.65` now and see:

Image: Successful LoadBalancer test!

I'll keep the `kube-vip` load balancer since it'll come in handy, but I have no further use for `yelb`:

kubectl delete ns yelb 
namespace "yelb" deleted 

Persistent Volume Claims, Storage Classes, and Storage Policies

At some point, I'm going to want to make sure that data from my Tanzu workloads stick around persistently - and for that, I'll need to define some storage stuff [23].

[23] define some storage stuff

First up, I'll add a new tag called `tkg-storage-local` to the `nuchost-local` vSphere datastore that I want to use for storing Tanzu volumes:

Image: Tag (and corresponding category) applied

Then I create a new vSphere Storage Policy called `tkg-storage-policy` which states that data covered by the policy should be placed on the datastore(s) tagged with `tkg-storage-local`:

Image: My Tanzu storage policy

So that's the vSphere side of things sorted; now to map that back to the Kubernetes side. For that, I'll need to define a Storage Class tied to the vSphere Storage profile so I drop these details into a new file called `vsphere-sc.yaml`:

kind: StorageClass
apiVersion: storage.k8s.io/v1
metadata:
  name: vsphere
provisioner: csi.vsphere.vmware.com
parameters:
  storagePolicyName: tkg-storage-policy

And then apply it with :

kubectl apply -f vsphere-sc.yaml 
storageclass.storage.k8s.io/vsphere created 

I can test that I can create a Persistent Volume Claim against the new `vsphere` Storage Class by putting this in a new file called `vsphere-pvc.yaml`:

apiVersion: v1
kind: PersistentVolumeClaim
metadata:
  labels:
    name: vsphere-demo-1
  name: vsphere-demo-1
spec:
  accessModes:
    - ReadWriteOnce
  storageClassName: vsphere
  resources:
    requests:
      storage: 5Gi

And applying it:

kubectl apply -f demo-pvc.yaml 
persistentvolumeclaim/vsphere-demo-1 created 

I can see the new claim, and confirm that its status is `Bound`:

kubectl get pvc 
NAME             STATUS   VOLUME                                     CAPACITY   ACCESS MODES   STORAGECLASS   AGE 
vsphere-demo-1   Bound    pvc-36cc7c01-a1b3-4c1c-ba0d-dff3fd47f93b   5Gi        RWO            vsphere        4m25s

And for bonus points, I can see that the container volume was created on the vSphere side:

Image: Container Volume in vSphere

So that's storage sorted. I'll clean up my test volume before moving on:

kubectl delete -f demo-pvc.yaml 
persistentvolumeclaim "vsphere-demo-1" deleted 

A real workload - phpIPAM

Demos are all well and good, but how about a real-world deployment to tie it all together? I've been using a phpIPAM instance for assigning static IP addresses for my vRealize Automation deployments [24], but have *only* been using it to monitor IP usage within the network ranges to which vRA will provision machines. I recently decided that I'd like to expand phpIPAM's scope so it can keep an eye on *all* the network ranges within the environment. That's not a big ask in my little self-contained homelab [25], but having a single system scanning all the ranges of a large production network probably wouldn't scale too well.

[24] phpIPAM instance for assigning static IP addresses for my vRealize Automation deployments

[25] my little self-contained homelab

Fortunately the phpIPAM project provides a remote scanning agent [26] which can be used for keeping an eye on networks and reporting back to the main phpIPAM server. With this, I could deploy an agent to each region (or multiple agents to a region!) and divide up the network into chunks that each agent would be responsible for scanning. But that's a pretty lightweight task for a single server to manage, and who wants to deal with configuring multiple instances of the same thing? Not this guy.

[26] remote scanning agent

So I set to work exploring some containerization options, and I found phpipam-docker [27]. That would easily replicate my existing setup in a trio of containers (one for the web front-end, one for the database back-end, and one with `cron` jobs to run scans at regular intervals)... but doesn't provide a remote scan capability. I also found a dockerized phpipam-agent [28], but this one didn't quite meet my needs. It did provide me a base to work off of though so a few days of tinkering [29] resulted in me publishing my first Docker image [30]. I've still some work to do before this application stack is fully ready for production but it's at a point where I think it's worth doing a test deploy.

[27] phpipam-docker

[28] dockerized phpipam-agent

[29] tinkering

[30] Docker image

To start, I'll create a new namespace to keep things tidy:

kubectl create ns ipam 
namespace/ipam created 

I'm going to wind up with four pods:

I'll use each container's original `docker-compose` configuration and adapt that into something I can deploy on Kubernetes.

phpipam-db

The phpIPAM database will live inside a MariaDB container. Here's the relevant bit from `docker-compose`:

services:
  phpipam-db:
    image: mariadb:latest
    ports:
      - "3306:3306"
    environment:
      - MYSQL_ROOT_PASSWORD=VMware1!VMWare1!
    volumes:
      - phpipam-db-data:/var/lib/mysql

So it will need a `Service` exposing the container's port `3306` so that other pods can connect to the database. For my immediate demo, using `type: ClusterIP` will be sufficient since all the connections will be coming from within the cluster. When I do this for real, it will need to be `type: LoadBalancer` so that the agent running on a different cluster can connect. And it will need a `PersistentVolumeClaim` so it can store the database data at `/var/lib/mysql`. It will also get passed an environment variable to set the initial `root` password on the database instance (which will be used later during the phpIPAM install to create the initial `phpipam` database).

It might look like this on the Kubernetes side:

# phpipam-db.yaml
apiVersion: v1
kind: Service
metadata:
  name: phpipam-db
  labels:
    app: phpipam-db
  namespace: ipam
spec:
  type: ClusterIP
  ports:
  - name: mysql
    port: 3306
    protocol: TCP
    targetPort: 3306
  selector:
    app: phpipam-db
---
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
  labels:
    name: phpipam-db
  name: phpipam-db-pvc
  namespace: ipam
spec:
  accessModes:
    - ReadWriteOnce
  storageClassName: vsphere
  resources:
    requests:
      storage: 5Gi
---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: phpipam-db
  namespace: ipam
spec:
  selector:
    matchLabels:
      app: phpipam-db
  replicas: 1
  template:
    metadata:
      labels:
        app: phpipam-db
    spec:
      containers:
      - name: phpipam-db
        image: mariadb:latest
        env:
        - name: MYSQL_ROOT_PASSWORD
          value: "VMware1!VMware1!"
        ports:
        - name: mysql
          containerPort: 3306
        volumeMounts:
        - name: phpipam-db-vol
          mountPath: /var/lib/mysql
      volumes:
      - name: phpipam-db-vol
        persistentVolumeClaim:
          claimName: phpipam-db-pvc

Moving on:

phpipam-www

This is the `docker-compose` excerpt for the web component:

services:
  phpipam-web:
    image: phpipam/phpipam-www:1.5x
    ports:
      - "80:80"
    environment:
      - TZ=UTC
      - IPAM_DATABASE_HOST=phpipam-db
      - IPAM_DATABASE_PASS=VMware1!
      - IPAM_DATABASE_WEBHOST=%
    volumes:
      - phpipam-logo:/phpipam/css/images/logo

Based on that, I can see that my `phpipam-www` pod will need a container running the `phpipam/phpipam-www:1.5x` image, a `Service` of type `LoadBalancer` to expose the web interface on port `80`, a `PersistentVolumeClaim` mounted to `/phpipam/css/images/logo`, and some environment variables passed in to configure the thing. Note that the `IPAM_DATABASE_PASS` variable defines the password used for the `phpipam` user on the database (not the `root` user referenced earlier), and the `IPAM_DATABASE_WEBHOST=%` variable will define which hosts that `phpipam` database user will be able to connect from; setting it to `%` will make sure that my remote agent can connect to the database even if I don't know where the agent will be running.

Here's how I'd adapt that into a structure that Kubernetes will understand:

# phpipam-www.yaml
apiVersion: v1
kind: Service
metadata:
  name: phpipam-www
  labels:
    app: phpipam-www
  namespace: ipam
spec:
  type: LoadBalancer
  ports:
  - name: http
    port: 80
    protocol: TCP
    targetPort: 80
  selector:
    app: phpipam-www
---
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
  labels:
    name: phpipam-www
  name: phpipam-www-pvc
  namespace: ipam
spec:
  accessModes:
    - ReadWriteOnce
  storageClassName: vsphere
  resources:
    requests:
      storage: 100Mi
---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: phpipam-www
  namespace: ipam
spec:
  selector:
    matchLabels:
      app: phpipam-www
  replicas: 1
  template:
    metadata:
      labels:
        app: phpipam-www
    spec:
      containers: 
      - name: phpipam-www
        image: phpipam/phpipam-www:1.5x
        env:
        - name: TZ
          value: "UTC"
        - name: IPAM_DATABASE_HOST
          value: "phpipam-db"
        - name: IPAM_DATABASE_PASS
          value: "VMware1!"
        - name: IPAM_DATABASE_WEBHOST
          value: "%"
        ports:
        - containerPort: 80
        volumeMounts:
        - name: phpipam-www-vol
          mountPath: /phpipam/css/images/logo
      volumes:
      - name: phpipam-www-vol
        persistentVolumeClaim:
          claimName: phpipam-www-pvc

phpipam-cron

This container has a pretty simple configuration in `docker-compose`:

services:
  phpipam-cron:
    image: phpipam/phpipam-cron:1.5x
    environment:
      - TZ=UTC
      - IPAM_DATABASE_HOST=phpipam-db
      - IPAM_DATABASE_PASS=VMware1!
      - SCAN_INTERVAL=1h

No exposed ports, no need for persistence - just a base image and a few variables to tell it how to connect to the database and how often to run the scans:

# phpipam-cron.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
  name: phpipam-cron
  namespace: ipam
spec:
  selector:
    matchLabels:
      app: phpipam-cron
  replicas: 1
  template:
    metadata:
      labels:
        app: phpipam-cron
    spec:
      containers:
      - name: phpipam-cron
        image: phpipam/phpipam-cron:1.5x
        env:
        - name: IPAM_DATABASE_HOST
          value: "phpipam-db"
        - name: IPAM_DATABASE_PASS
          value: "VMWare1!"
        - name: SCAN_INTERVAL
          value: "1h"
        - name: TZ
          value: "UTC"

phpipam-agent

And finally, my remote scan agent. Here's the `docker-compose`:

services:
  phpipam-agent:
    container_name: phpipam-agent
    restart: unless-stopped
    image: ghcr.io/jbowdre/phpipam-agent:latest
    environment:
      - IPAM_DATABASE_HOST=phpipam-db
      - IPAM_DATABASE_NAME=phpipam
      - IPAM_DATABASE_USER=phpipam
      - IPAM_DATABASE_PASS=VMware1!
      - IPAM_DATABASE_PORT=3306
      - IPAM_AGENT_KEY=
      - IPAM_SCAN_INTERVAL=5m
      - IPAM_RESET_AUTODISCOVER=true
      - IPAM_REMOVE_DHCP=true
      - TZ=UTC

It's got a few additional variables to make it extra-configurable, but still no need for persistence or network exposure. That `IPAM_AGENT_KEY` variable will need to get populated the appropriate key generated within the new phpIPAM deployment, but we can deal with that later.

For now, here's how I'd tell Kubernetes about it:

# phpipam-agent.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
  name: phpipam-agent
  namespace: ipam
spec:
  selector:
    matchLabels:
      app: phpipam-agent
  replicas: 1
  template:
    metadata:
      labels:
        app: phpipam-agent
    spec:
      containers:
      - name: phpipam-agent
        image: ghcr.io/jbowdre/phpipam-agent:latest
        env:
        - name: IPAM_DATABASE_HOST
          value: "phpipam-db"
        - name: IPAM_DATABASE_NAME
          value: "phpipam"
        - name: IPAM_DATABASE_USER
          value: "phpipam"
        - name: IPAM_DATABASE_PASS
          value: "VMware1!"
        - name: IPAM_DATABASE_PORT
          value: "3306"
        - name: IPAM_AGENT_KEY
          value: ""
        - name: IPAM_SCAN_INTERVAL
          value: "5m"
        - name: IPAM_RESET_AUTODISCOVER
          value: "true"
        - name: IPAM_REMOVE_DHCP
          value: "true"
        - name: TZ
          value: "UTC"

Deployment and configuration of phpIPAM

I can now go ahead and start deploying these containers, starting with the database one (upon which all the others rely):

kubectl apply -f phpipam-db.yaml 
service/phpipam-db created 
persistentvolumeclaim/phpipam-db-pvc created
deployment.apps/phpipam-db created

And the web server:

kubectl apply -f phpipam-www.yaml 
service/phpipam-www created 
persistentvolumeclaim/phpipam-www-pvc created
deployment.apps/phpipam-www created

And the cron runner:

kubectl apply -f phpipam-cron.yaml 
deployment.apps/phpipam-cron created 

I'll hold off on the agent container for now since I'll need to adjust the configuration slightly after getting phpIPAM set up, but I will go ahead and check out my work so far:

kubectl -n ipam get all 
NAME                                READY   STATUS    RESTARTS   AGE 
pod/phpipam-cron-6c994897c4-6rsnp   1/1     Running   0          4m30s
pod/phpipam-db-5f4c47d4b9-sb5bd     1/1     Running   0          16m
pod/phpipam-www-769c95c68d-94klg    1/1     Running   0          5m59s
NAME                  TYPE           CLUSTER-IP       EXTERNAL-IP    PORT(S)        AGE
service/phpipam-db    ClusterIP      100.66.194.69    <none>         3306/TCP       16m
service/phpipam-www   LoadBalancer   100.65.232.238   192.168.1.64   80:31400/TCP   5m59s
NAME                           READY   UP-TO-DATE   AVAILABLE   AGE
deployment.apps/phpipam-cron   1/1     1            1           4m30s
deployment.apps/phpipam-db     1/1     1            1           16m
deployment.apps/phpipam-www    1/1     1            1           5m59s
NAME                                      DESIRED   CURRENT   READY   AGE
replicaset.apps/phpipam-cron-6c994897c4   1         1         1       4m30s
replicaset.apps/phpipam-db-5f4c47d4b9     1         1         1       16m
replicaset.apps/phpipam-www-769c95c68d    1         1         1       5m59s 

And I can point my browser to the `EXTERNAL-IP` associated with the `phpipam-www` service to see the initial setup page:

Image: phpIPAM installation page

I'll click the **New phpipam installation** option to proceed to the next step:

Image: Database initialization options

I'm all for easy so I'll opt for **Automatic database installation**, which will prompt me for the credentials of an account with rights to create a new database within the MariaDB instance. I'll enter `root` and the password I used for the `MYSQL_ROOT_PASSWORD` variable above:

Image: Automatic database install

I click the **Install database** button and I'm then met with a happy success message saying that the `phpipam` database was successfully created.

And that eventually gets me to the post-install screen, where I set an admin password and proceed to log in:

Image: We made it to the post-install!

To create a new scan agent, I go to **Menu > Administration > Server management > Scan agents**.

Image: Scan agents screen

And click the button to create a new one:

Image: Creating a new agent

I'll copy the agent code and plug it into my `phpipam-agent.yaml` file:

        - name: IPAM_AGENT_KEY
          value: "4DC5GLo-F_35cy7BEPnGn7HivtjP_o-v"

And then deploy that:

kubectl apply -f phpipam-agent.yaml 
deployment.apps/phpipam-agent created 

The scan agent isn't going to do anything until it's assigned to a subnet though, so now I head to **Administration > IP related management > Sections**. phpIPAM comes with a few default sections and ranges and such defined so I'll delete those and create a new one that I'll call `Lab`.

Image: Section management

Now I can create a new subnet within the `Lab` section by clicking the **Subnets** menu, selecting the `Lab` section, and clicking **+ Add subnet**.

Image: Empty subnets menu

I'll define the new subnet as `192.168.1.0/24`. Once I enable the option to *Check hosts status*, I'll then be able to specify my new `remote-agent` as the scanner for this subnet.

Image: Creating a new subnet

Image: A new (but empty) subnet

It shows the scanner associated with the subnet, but no data yet. I'll need to wait a few minutes for the first scan to kick off (at the five-minute interval I defined in the configuration).

Image: GIF which says 'Five Minutes Later!'

Image: Newly discovered IPs!

Woah, it actually works!

Conclusion

I still need to do more work to the containerized phpIPAM stack ready for production, but I'm feeling pretty good for having deployed a functional demo of it at this point! And working on this was a nice excuse to get a bit more familiar with Tanzu Community Edition specifically, Kubernetes in general, and Docker (I learned a ton while assembling the `phpipam-agent` image!). I find I always learn more about a new-to-me technology when I have an actual project to do rather than just going through the motions of a lab exercise. Maybe my notes will be useful to you, too.

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