The other option is to use the deployment manifest resources with the kubectl apply command.
There are environment variables that you can use to point it to multiple clusters and tweak other bits of the configuration.
The main variable you may wish to tweak is CLUSTERS. This allows you to specify a comma separated list of Kubernetes API server URLs. Use this to get the dashboard view populated with multiple clusters you have access to.
The tool only requires read-only access to the cluster, so keep this in mind if you’re deploying it manually.
If you’re using the Helm chart, specify rbac.create = true to create the read-only ClusterRole and ClusterRoleBinding automatically.
There are plenty of nifty features for a simple operational view. You can filter, move the cluster sections around, and change themes.
It’s even got an old school CRT style theme you can enable, though I’m not sure the flicker and scan line effect are my cup of tea!
There is something magical about building your own infrastructure from scratch. And when I say scratch, I mean using bare metal. This is a run through of my multipurpose FreeNAS server build process.
After scratching the itch recently with my Raspberry Pi Kubernetes Cluster, I got a hankering to do it again, and this build was soon in the works.
Part of my motivation came from my desire to reduce our reliance on cloud technology at home. Don’t get me wrong, I am an advocate for using the cloud where it makes sense. My day job revolves around designing and managing various clients’ cloud infrastructure.
At home, this was more about taking control of our own data.
I’ll skip to the juicy specifications part if you would like to know what hardware I used right away.
These are the final specifications I decided on. Scroll down to see the details about each area.
I also made an initial mistake here in my build buying a Gigabyte B450M DS3H motherboard. The product specs seem to indicate that it supports ECC, and so did a review I found on Anandtech. In reality the Gigabyte board does not support the ECC feature. Rather it ‘supports’ ECC memory by allowing the system to boot with ECC RAM installed, but you don’t get the actual error checking and correction!
I figured this out after booting it up with Fedora Rawhide as well as a couple of uBuntu Server distributions and running the edac-utils package. In all cases edac-utils failed to find ECC support / or any memory controller.
The Asus board I settled on supports ECC and edac-utils confirmed this.
The motherboard also has an excellent EFI BIOS. I found it easy to get to the ECC and Virtualization settings.
I used 4 x Western Digital 3TB Red hard drives for the RAIDZ1 main storage pool.
The SSD storage pool consists of 2 x Crucial MX500 250GB SSD SATA drives in a mirror configuration. This configuration is for running Virtual Machines and the NFS storage for my Kubernetes cluster.
The crossing out of APUs also meant I would need a discrete graphic card for console / direct access, and to install the OS initially. I settled on a cheap PCI Express Graphics card off Ebay for this.
Having chosen a beefy six core Ryzen 2600 CPU, I decided I didn’t need to get a fancy graphics card for live media encoding. (Plex does much better with this). If media encoding speed and efficiency is important to you, then consider something like an nVIDIA or AMD card.
For me, the six core CPU does a fine job at encoding media for home and remote streaming over Plex.
I wanted to use this system to server file storage for my home PCs and equipment. Besides this, I also wanted to export and share storage to my Raspberry Pi Kubernetes cluster, which runs on it’s own, dedicated network.
The simple solution for me here was multihoming the server onto the two networks. So I would need two network interface cards, with at least 1Gbit/s capability.
The motherboard already has an Intel NIC onboard, so I added two more ports with an Intel Pro Dual Port Gigabit PCI Express x4 card.
I’ll detail the highlights of my configuration for each service the multipurpose FreeNAS Server build hosts.
Main System Setup
The boot device is the 120GB M.2 nVME SSD. I installed FreeNAS 11.3 using a bootable USB drive.
I created two Storage Pools. Both are encrypted. Besides the obvious protection encryption provides, this also makes it easier to recycle drives later on if I need to.
Storage Pool 1
4 x Western Digital Red 3TB drives, configured with RAIDZ1. (1 disk’s worth of storage is effectively lost for parity, giving roughly 8-9 TB of usable space).
Deduplication turned off
Storage Pool 2
2 x Crucial MX500 250GB SSD drives, configured in a Mirror (1 disk mirrors the other, providing a backup if one fails).
Deduplication turned off
The network is set to use the onboard NIC to connect to my main home LAN. One of the ports on the Intel dual port NIC connects to my Raspberry Pi Kubernetes Cluster network and assigned a static IP address on that network.
My home network’s storage shares are simple Windows SMB Shares.
I created a dedicated user in FreeNAS which I configured in the SMB share configuration ACLs to give access.
Windows machines then simply mount the network location / path as mapped drives.
I also enabled Shadow Copies. FreeNAS supports this to enable Windows to use Shadow Copies.
I setup a dedicated uBuntu Server 18.04 LTS Virtual Machine using FreeNAS’ built-in VM support (bhyve). Before doing this, I enabled virtualization support in the motherboard BIOS settings. (SVM Mode = Enabled).
I used the standard installation method for Pi-Hole. I made sure the VM was using a static IP address and was bridged to my home network. Then I reconfigured my home DHCP server to dish out the Pi-hole’s IP address as the primary DNS server to all clients.
For the DNS upstream servers that Pi-hole uses, I chose to use the Quad9 (filtered, DNSSEC) ones, and enabled DNSSEC.
NextCloud has a readily available plugin for FreeNAS. However, out of the box you get no SSL. You’ll need to setup your networking at home to allow remote access. Additionally, you’ll need to get an SSL certificate. I used Let’s Encrypt.
Plex was a simple setup. Simply install the Plex FreeNAS plugin from the main Plugins page and follow the wizard. It will install and configure a jail to run Plex.
To mount your media, you need to stop the Plex jail and edit it to add your media location on your storage. Here is an example of my mount point. It basically mounts the media directory I use to keep all my media into the Plex Jail’s filesystem.
NFS Storage for Kubernetes
Lastly, I setup an NFS share / export for my Raspberry Pi Kubernetes Cluster to use for Persistent Volumes to attach to pods.
The key points here were that I allowed the two network ranges I wanted to have access to this storage from. (10.0.0.0/8 is my Kubernetes cluster network). I also configured a Mapall user of ‘root’, which allows the storage to be writeable when mounted by pods/containers in Kubernetes. (Or any other clients that mount this storage).
I was happy with this level of access for this particular NFS storage share from these two networks.
I modified the deployment manifest to point it to my FreeNAS machine’s IP address and NFS share path.
With that done, pods can now request persistent storage with a Persistent Volume Claim (PVC). The NFS client provisioner will create a directory for the pod (named after the pod itself) on the NFS mount and mount that to your pod.
So far the multipurpose FreeNAS server build has been very stable. It has been happily serving our home media streaming, storage, and shared storage needs.
It’s also providing persistent storage for my Kubernetes lab environment which is great, as I prefer not to use the not-so-durable microSD cards on the Raspberry Pi’s themselves for storage.
The disk configuration size seems fine for our needs. At the moment we’re only using ~20% of the total storage, so there is plenty of room to grow.
I’m also happy with the ability to run custom VMs or Jails for additional services, though I might need to add another 16GB of ECC RAM in the future to support more as ZFS does well with plenty of memory.
In this post I’ll explain how I created an AWS EC2 Spot Instance Termination Simulator to run on any EC2 instance.
It can signal typical monitoring scripts, applications, interrupt handlers, and more, just like a real Spot Termination signal would do.
Looking around, there aren’t really any straight forward ways of testing this behaviour.
The obvious way is to change the price you bid for spot instances to the threshold of the current market price. This is so that if there is a slight increase in demand your spot instance(s) will be terminated.
The problem with that approach is of course that you can’t easily predict when the price will move, or by how much.
How EC2 Spot Instance Termination warnings work
When your spot instance bid price is surpassed by the current market price, a Termination Notice becomes available on one of the instance’s metadata endpoints. For example, http://169.254.169.254/latest/meta-data/spot/termination-time.
There is one other, newer endpoint at http://169.254.169.254/latest/meta-data/spot/instance-action that could also be used.
At this point the endpoint returns an HTTP 200 response. A timestamp of when a shutdown signal is going to be sent to your instance’s OS is also returned.
In the case of the newer endpoint, a JSON string is returned with an action and time. Usually the endpoint usually simply returns a 404 not found response.
The tools out there tend to monitor this endpoint to warn and action in case of a Spot Termination notice being received.
The two minute warning feature was added by Amazon back in 2015, announced in this blog post.
The service is a NodePort service, exposing the port on the host it runs on.
List the service and the pod (and find the kubernetes node the pod is running on):
kubectl get svc ec2-spot-termination-simulator
kubectl get pod spot-term-simulator-xxxxxx -o wide
Take note of the NodePort the service is listening on for the Kubernetes node. E.g. port 30626.
docker run -p 30626:80 -e PORT=80 shoganator/ec2-spot-termination-simulator
Proxying the EC2 metadata service
Perform some trickery to proxy traffic destined to 169.254.169.254 on port 80 to localhost (where the container runs). This is so that the fake service can take the place of the real one.
SSH onto the Kubernetes node and run:
sudo ifconfig lo:0 169.254.169.254 up
sudo socat TCP4-LISTEN:80,fork TCP4:127.0.0.1:30626
Create an alias for the localhost interface at 169.254.169.254, effectively taking over the EC2 metadata service and sending that to 127.0.0.1 instead.
Forward TCP port 80 traffic (usually destined to the EC2 metadata service) to 127.0.0.1 on the NodePort 30626. This is where the ec2-spot-termination-simulator pod is running on this host. Substitute this with the correct port in your case.
As a result, it should return a 200 OK response with a timestamp from the fake service. This is the same as the real one would.
Looking at how the kube-spot-termination-notice-handler service works specifically:
This service runs as a DaemonSet, meaning one instance per host. The instance on the node you set the simualtor up on should immediately drain the node. The instance won’t actually be terminated as this was of course just a simulated termination.
If you’re not running on Kubernetes and are using a different spot termination handler, don’t worry. The system you’re using to monitor the EC2 instance metadata endpoint should still take action at this point.
The proxied web service is now returning a legitimate looking termination time notice on http://169.254.169.254/latest/meta-data/spot/termination-time.
This is the third post in this series and the focus will be on completing the Raspberry Pi Kubernetes cluster by adding a worker node. You’ll also setup a software based load-balancer implementation designed for bare metal Kubernetes Clusters by leveraging MetalLB.
Here are some handy links to other parts in this blog post series:
By now you should have 1 x Pi running as the dedicated Pi network router, DHCP, DNS and jumpbox, as well as 1 x Pi running as the cluster Master Node.
Of course it’s always best to have more than 1 x Master node, but as this is just an experimental/fun setup, one is just fine. The same applies to the Worker nodes, although in my case I added two workers with each Pi 4 having 4GB RAM.
Joining a Worker Node to the Cluster
Start off by completing the setup steps as per the Common Setup section in Part 2 with your new Pi.
Once your new Worker Pi is ready and on the network with it’s own static DHCP lease, join it to the cluster (currently only the Master Node) by using the kubeadm join command you noted down when you first initialised your cluster in Part 2.
After a few moments, SSH back to your master node and run kubectl get nodes. You should see the new worker node added and after it pulls down and starts the weave net CNI image it’s status will change to Ready.
Setting up MetalLB
The problem with a ‘bare metal’ Kubernetes cluster (or any self-installed, manually configured k8s cluster for that matter) is that it doesn’t have any load-balancer implementation to handle LoadBalancer service types.
When you run Kubernetes on top of a cloud hosting platform like AWS or Azure, they are backed natively by load-balancer implementations that work seamlessly with those cloud platform’s load-balancer services. E.g. classic application or elastic load balancers with AWS.
However, with a Raspberry Pi cluster, you don’t have anything fancy like that to provide LoadBalancer services for your applications you run.
MetalLB provides a software based implementation that can work on a Pi cluster.
Install version 0.8.3 of MetalLB by applying the following manifest with kubectl:
Update the addresses section to use whichever range of IP addresses you would like to assign for use with MetalLB. Note, I only used 10 addresses as below for mine.
Apply the configuration:
kubectl apply -f ./metallb-config.yaml
Setup Helm in the Pi Cluster
First of all you’ll need an ARM compatible version of Helm. Download it and move it to a directory that is in your system PATH. I’m using my Kubernetes master node as a convenient location to use kubectl and helm commands from, so I did this on my master node.
Note: it uses a custom image from jessestuart/tiller (as this is ARM compatible). The command also replaces the older api spec for the deployment with the apps/v1 version, as the older beta one is no longer applicable with Kubernetes 1.16.
Deploy an Ingress Controller with Helm
Now that you have something to fulfill LoadBalancer service types (MetalLB), and you have Helm configured, you can deploy an NGINX Ingress Controller with a LoadBalancer service type for your Pi cluster.
If you list out your new ingress controller pods though you might find a problem with them running. They’ll likely be trying to use x86 architecture images instead of ARM. I manually patched my NGINX Ingress Controller deployment to point it at an ARM compatible docker image.
kubectl set image deployment/nginx-ingress-controller nginx-ingress-controller=quay.io/kubernetes-ingress-controller/nginx-ingress-controller-arm:0.26.1
After a few moments the new pods should now show as running:
Now to test everything, you can grab the external IP that should have been assigned to your NGINX ingress controller LoadBalancer service and test the default NGINX backend HTTP endpoint that returns a simple 404 message.
List the service and get the EXTERNAL-IP (this should sit in the range you configured MetalLB with):
kubectl get service --selector=app=nginx-ingress
Curl the NGINX Ingress Controller LoadBalancer service endpoint with a simple GET request:
curl -i http://10.23.220.88
You’ll see the default 404 not found response which indicates that the controller did indeed receive your request from the LoadBalancer service and directed it appropriately down to the default backend pod.
At this point you’ve configured:
A Raspberry Pi Kubernetes network Router / DHCP / DNS server / jumpbox
Kubernetes master node running the master components for the cluster
Kubernetes worker nodes
MetalLB load-balancer implementation for your cluster
Helm client and Tiller agent for ARM in your cluster
NGINX ingress controller
In part 1, recall you setup some iptables rules on the Router Pi as an optional step?
These PREROUTING AND POSTROUTING rules were to forward packets destined for the Router Pi’s external IP address to be forwarded to a specific IP address in the Kubernetes network. In actual fact, the example I provided was what I used to forward traffic from the Pi router all the way to my NGINX Ingress Controller load balancer service.
Revisit this section if you’d like to achieve something similar (access services inside your cluster from outside the network), and replace the 10.23.220.88 IP address in the example I provided with the IP address of your own ingress controller service backed by MetalLB in your cluster.
Also remember that at this point you can add as many worker nodes to the cluster as you like using the kubeadm join command used earlier.
The Kubernetes Master node is one that runs what are known as the master processes: The kube-apiserver, kube-controller-manager and kube-scheduler.
In this post we’ll go through some common setup that all nodes (masters and workers) in your cluster should get, and then on top of that, the specific setup that will finally configure a single node in the cluster to be the master.
If you would like to jump to the other partes in this series, here are the links:
By now you should have some sort of stack or collection of Raspberry Pis going. As mentioned in the previous post, I used a Raspberry Pi 3 for my router/dhcp server for the Kubernetes Pi Cluster network, and Raspberry Pi 4’s with 4GB RAM each for the master and worker nodes. Here is how my stack looks now:
This setup will be used for both masters and workers in the cluster.
Start by writing the official Raspbian Buster Lite image to your microSD card. (I used the 26th September 2019 version), though as you’ll see next I also updated the Pi’s firmware and OS using the rpi-update command.
After attaching your Pi (master) to the network switch, it should pick up an IP address from the DHCP server you setup in part 1.
SSH into the Pi and complete the basic setup such as setting a hostname and ensuring it gets a static IP address lease from DHCP by editing your dnsmasq configuration (as per part 1).
Note: As the new Pi is running on a different network behind your Pi Router, you can either SSH into your Pi Router (like a bastion host or jump box) and then SSH into the new Master Pi node from there.
Now update it:
After the update completes, reboot the Pi.
sudo reboot now
SSH back into the Pi, then download and install Docker. I used version 19.03 here, though at the moment it is not ‘officially’ supported.
curl -sSL get.docker.com | sh && sudo usermod pi -aG docker && newgrp docker
Kubernetes nodes should have swap disabled, so do that next. Additionally, you’ll enable control groups (cgroups) for resource isolation.
Installing kubeadm and other Kubernetes components
Next you’ll install the kubeadm tool (helps us create our cluster quickly), as well as a bunch of other components required, such as the kubelet (the main node agent that registers nodes with the API server among other things), kubectl and the kubernetes cni (to provision container networking).
Next up, install the legacy iptables package and setup networking so that it traverses future iptables rules.
Note: when I built my cluster initially I discovered problems with iptables later on, where the kube-proxy and kubelet services had trouble populating all their required iptables rules using the pre-installed version of iptables. Switching to legacy iptables fixed this.
The error I ran into (hopefully those searching it will come across this post too) was:
proxier.go:1423] Failed to execute iptables-restore: exit status 2 (iptables-restore v1.6.0: Couldn't load target `KUBE-MARK-DROP':No such file or directory
Setup iptables and change it to the legacy version:
Lastly to finish off the common (master or worker) node setup, reboot.
sudo reboot now
Master Node Setup
Now you can configure this Pi as a master Kubernetes node. SSH back in after the reboot and pull down the various node component docker images, then initialise it.
Important: Make sure you change the 10.0.0.50 IP address in the below code snippet to match whatever IP address you reserved for this master node in your dnsmasq leases configuration. This is the IP address that the master API server will advertise out with.
Note: In my setup I am using 192.168.0.0./16 as the pod CIDR (overlay network). This is specifically to keep it separate from my internal Pi network of 10.0.0.0/8.
sudo kubeadm config images pull -v3
sudo kubeadm init --token-ttl=0 --apiserver-advertise-address=10.0.0.50 --pod-network-cidr=192.168.0.0/16
# capture text and run as normal user. e.g.:
# mkdir -p $HOME/.kube
# sudo cp -i /etc/kubernetes/admin.conf $HOME/.kube/config
# sudo chown $(id -u):$(id -g) $HOME/.kube/config
Once the kubeadm commands complete, the init command will output a bunch of commands to run. Copy and enter them afterwards to setup the kubectl configuration under $HOME/.kube/config.
You’ll also see a kubeadm join command/token. Take note of that and keep it safe. You’ll use this to join other workers to the cluster later on.
You’ll setup Weave Net next. At a high level, Weave Net creates a virtual container network that connects your containers that are scheduled across (potentially) many different hosts and enables their automatic discovery across these hosts too.
Kubernetes has a pluggable architecture for container networking, and Weave Net is one implementation of this.
Note: the command below assumes you’re using an overlay/container network of 192.168.0.0/16. Change this if you’re not using this range.
After a few moments waiting for your node to pull down the weave net container images, check that the weave container(s) are running and that the master node is showing as ready. Here is how that should look…
kubectl -n kube-system get pods
kubectl get nodes
pi@korben:~ $ kubectl -n kube-system get pods | grep weave
weave-net-cfxhr 2/2 Running 20 10d
weave-net-chlgh 2/2 Running 17 23d
weave-net-rxlg8 2/2 Running 13 23d
pi@korben:~ $ kubectl get nodes
NAME STATUS ROLES AGE VERSION
korben Ready master 23d v1.16.2
That is pretty much it for the master node setup. You now have a single master node running the Kubernetes master components / API server, and have even used to successfully provision and configure container networking.
As a result of deploying Weave Net, you now have a DaemonSet that will ensure that any new node that joins the cluster will automatically get the Weave Net CNI. All other nodes in the cluster will automatically update to ‘know’ about the new node and subsequently containers in the cluster will be able to talk to each other over the overlay network.
To make the setup as portable as possible, and also slightly seggregated from my home network, I used the 1 x Raspberry Pi 3 device I had as a router between my home network and my Kubernetes Layer 2 Network (effectively the devices on the 8 port Netgear Switch).
Here is a network diagram that shows the setup.
Building the Raspberry Pi Cluster Router
Of course you’ll need an OS on the microSD card for each Raspberry Pi you’re going to be using. I used the latest Raspbian Buster Lite image from the official Raspbian Downloads page (September 26).
This is a minimal image and is exactly what we need. You’ll need to write it to your microSD card. There are plenty tutorials out there on doing this, so I won’t cover it here.
One piece of advice though, would be to create a file called “ssh” on the imaged card filesystem after writing the image. This enables you to SSH on directly without the need to connect up a screen and setup the SSH daemon yourself. Basically just login to your home network DHCP server and look for the device once it boots then SSH to it’s automatically assigned IP address.
Also, it would be wise to reserve an IP address on your home network’s DHCP service for your Pi Router. Grab the MAC address of your Pi and add it to your home network DHCP service’s reserved IP addresses. I set mine to 192.168.2.30 on my WiFi network.
List the wlan interface’s MAC address with:
Setting Hostname and Changing the Default Password
On the Router Raspberry Pi, run the following command to change the hostname to something other than “raspberry” and change the default password too:
Setting up the Pi Router
Now the rest of the guide deserves much credit to this blog post, however, I did change a few things on my setup, as the routing was not configured 100% correctly to allow external access to services on the internal Kubernetes network.
I needed to add a couple of iptables rules in order to be able to access my Ingress Controller from my home network. More on that later though.
You need to configure the WiFi interface (wlan0) and the Ethernet Interface (eth0) for each “side” of the network.
Edit the dhcpd.conf file and add an eth0 configuration right at the bottom, then save.
Of course replace the above DNS servers with whichever you prefer to use. I’ve used Cloudflare and OpenDNS ones here.
Next, setup your WiFi interface to connect to your home WiFi. WiFi connection details get saved to /etc/wpa_supplicant/wpa_supplicant.conf but it is best to use the built-in configuration tool (raspi-config) to do the WiFi setup.
Go to Network Options and enter your WiFi details. Save/Finish afterwards.
Create a new /etc/dnsmasq.conf file with the below command:
The script is the main dnsmasq configuration that sets DHCP up over the eth0 interface (for the 10.0.0.0/8 network side) and configures some nameservers for DNS as well as a few other bits.
Edit the service file for dnsmasq (/etc/init.d/dnsmasq) to prevent issues with start-up order of dnsmasq and dhcpcd:
sudo nano /etc/init.d/dnsmasq
Change the top of the file to look like this:
# Hack to wait until dhcpcd is ready
### BEGIN INIT INFO
# Provides: dnsmasq
# Required-Start: $network $remote_fs $syslog $dhcpcd
# Required-Stop: $network $remote_fs $syslog
# Default-Start: 2 3 4 5
# Default-Stop: 0 1 6
# Description: DHCP and DNS server
### END INIT INFO
The lines changed above are the sleep 10 command and the Required-Start addition of $dhcpcd.
At this point its a good idea to reboot.
sudo reboot now
After the reboot, check that dnsmasq is running.
sudo systemctl status dnsmasq
First of all, enable IP forwarding. Edit the /etc/sysctl.conf file and uncomment this line:
This enables us to use NAT rules with iptables.
Now you’ll configuring some POSTROUTING and FORWARD rules in iptables to allow your Raspberry Pi devices on the 10.0.0.0/8 network to access the internet via your Pi Router’s wlan0 interface.
sudo iptables -t nat -A POSTROUTING -o wlan0 -j MASQUERADE
sudo iptables -A FORWARD -i wlan0 -o eth0 -m state --state RELATED,ESTABLISHED -j ACCEPT
sudo iptables -A FORWARD -i eth0 -o wlan0 -j ACCEPT
This is optional, and you might only need to do this later on once you start running services in your Kubernetes Pi Cluster.
Forward Traffic from your home network to a Service or Node IP in your Cluster Network:
The above assumes a couple of things that you should change accordingly (if you use this optional step):
You have a Service running in the Kubnernetes network, listening on port 80 (http) on IP 10.23.220.88
You setup your Pi Router to use 10.0.0.1 as the eth0 device IP (as per above in this post), and your wlan0 interface is the connection that your Pi router is using to connect to your home network (WiFi).
You actually want to forward traffic hitting your Pi Router (from the WiFi wlan0 interface) through the 10.0.0.1eth0 interface and into a service IP on the 10.0.0.0/8 network. (In my example above I have an nginx Ingress Controller running on 10.23.220.88).
Persisting your iptables rules across reboots
Persist all of your iptables rules by installing iptables-persistent:
sudo apt install iptables-persistent
The above will run a wizard after installation and you’ll get the option to save your IPv4 rules. Choose Yes, then reboot afterwards.
After reboot, run sudo iptables -L -n -v to check that the rules persisted after reboot.
Note: if you ever update your Pi Router’s iptables rules and want to re-save the new set of rules to persist across reboots, you’ll need to re-save them using the iptables-persistent package.
sudo dpkg-reconfigure iptables-persistent
Adding new Pi devices to your network in future
Whenever you add an additional Raspberry Pi device to the 8 port switch / Kubernetes network in the future, make sure you edit /etc/dnsmasq.conf to update the list of MAC addresses assigned to 10.0.0.x IP addresses.
You’ll want to set the new Pi’s eth0 MAC address up in the list of pre-defined DHCP leases.
You can also view the /var/lib/misc/dnsmasq.leases file to see the current dnsmasq DHCP leases.
This is handy when adding a new, un-configured Pi to the network – you can pick up the auto-assigned IP address here, and then SSH to that for initial configuration.
That is pretty much the setup and configuration for the Pi Router complete. As mentioned above, much credit for this configuration goes to this guide on downey.io.
I ended up modifying the iptables rules for service traffic forwarding from my home network side into some Kubernetes LoadBalancer services I ended up running later on which I covered above in the Optional Steps section.
At this point you should have your Pi Router connected to your home network via WiFi, and have the Ethernet port plugged into your network switch. Make sure the switch is not connected back to your home network via an Ethernet cable or you’ll run into some strange network loop issues.
You should now be able to plug in new Pi’s to the network switch, and they should get automatically assigned DHCP addresses on the 10.0.0.0/8 network.
Updating your dnsmasq.conf file with the new Pi’s ethernet MAC addresses means that they can get statically leases IP addresses too, which you’ll need for your Kubernetes nodes once you start adding them (see Part 2 coming next).