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2022-01-12
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:
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!
Here's how I did it.
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.
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.
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 |
Moving on to the Getting Started [7], I'll need to grab some software before I can actually Get Started.
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`.
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.
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.
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
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.
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:
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"}
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
The final bit of required software is the Tanzu CLI, which can be downloaded from the project on GitHub [14].
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
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.
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
*Now* I can point my local browser to my VM and see the UI:
And then I can click the button at the bottom left to save my eyes before selecting the option to deploy on vSphere.
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.
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.
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:
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.
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.
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.
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.
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]).
cp tce-mgmt.yaml tce-work.yaml vi tce-work.yaml
I only need to change 2 of the parameters in this file:
`CLUSTER_NAME`: from `tce-mgmt` to `tce-work`
`VSPHERE_CONTROL_PLANE_ENDPOINT`: from `192.168.1.60` to `192.168.1.61`
I *could* change a few others if I wanted to
(Optional) `CONTROL_PLANE_MACHINE_COUNT` to deploy an increased number of control plane nodes (must but an odd integer)
(Optional) `WORKER_MACHINE_COUNT` to add worker nodes
(Optional) `NAMESPACE` to deploy the cluster in a specific Kubernetes namespace
(Optional) `OS_NAME` and `OS_VERSION` to use a different machine image for the workload cluster
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>
ℹ
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:
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.
Excellent, I've got a Tanzu management cluster and a Tanzu workload cluster. What now?
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
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-mgmt-admin@tce-mgmt tce-mgmt tce-mgmt-admin
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!
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.
I can check out the sample deployment that William put together here [19], and then deploy it with:
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:
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.
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.
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:
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:
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
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].
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:
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`:
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:
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
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.
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.
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.
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:
`phpipam-db` for the database back-end
`phpipam-www` for the web front-end
`phpipam-cron` for the local cron jobs, which will be largely but not completely replaced by:
`phpipam-agent` for my remote scan agent
I'll use each container's original `docker-compose` configuration and adapt that into something I can deploy on Kubernetes.
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:
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
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"
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"
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:
I'll click the **New phpipam installation** option to proceed to the next step:
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:
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:
To create a new scan agent, I go to **Menu > Administration > Server management > Scan agents**.
And click the button to create a new one:
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`.
Now I can create a new subnet within the `Lab` section by clicking the **Subnets** menu, selecting the `Lab` section, and clicking **+ Add subnet**.
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.
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).
Woah, it actually works!
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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