Saving £500 on a new Apple Mac Mini with 32GB RAM

mac mini internals

I purchased a new Apple Mac Mini recently and didn’t want to fall victim to Apple’s “RAM Tax”.

I used Apple’s site to configure a Mac Mini with a quad core processor, 32GB RAM, and a 512GB SSD.

I was shocked to see they added £600.00 to the price of a base model with 8GB RAM. They’re effectively charging all of this money for 24GB of extra RAM. This memory is nothing special, it’s pretty standard 2666MHz DDR4 SODIMM modules. The same stuff that is used in generic laptops.

I decided to cut back my order to the base model with 8GB of RAM. I ordered a Crucial 32GB Kit (2 x 16GB DDR4-2666 SODIMM modules running at 1.2 volts with a CAS latency of 19ns). This kit cost me just over £100.00 online.

The Crucial 2 x 16GB DDR4-2666 SODIMM kit

In total I saved around £500.00 for the trouble of about 30 minutes of work to open up the Mac Mini and replace the RAM modules myself.

The Teardown Process

Use the iFixit Guide

You can use my photos and brief explanations below if you would like to follow the steps I took to replace the RAM, but honestly, you’re better off following iFixit’s excellent guide here.

Follow along Here

If you want to compare or follow along in my format, then read on…

Get a good tool kit with hex screw drivers. I used iFixit’s basic kit.

iFixit basic tool kit

Flip the Mac Mini upside down.

Pry open the back cover, carefully with a plastic prying tool

Undo the 6 x hex screws on the metal plate under the black plastic cover. Be careful to remember the positions of these, as there are 2 x different types. 3 x short screws, and 3 x longer.

opening the mac mini

Very carefully, move the cover to the side, revealing the WiFi antenna connector. Unscrew the small hex screw holding the metal tab on the cable. Use a plastic levering tool to carefully pop the antenna connector off.

Next, unscrew 4 x screws that hold the blower fan to the exhaust port. You can see one of the screws in the photo below. Two of the screws are angled at a 45 degree orientation, so carefully undo those, and use tweezers to catch them as they come out.

Carefully lift the blower fan up, and disconnect it’s cable using a plastic pick or prying tool. The trick is to lift from underneat the back of the cable’s connector and it’ll pop off.

mac mini blower fan removal

Next, disconnect the main power cable at the top right of the photo below. This requires a little bit of wiggling to loosen and lift it as evenly as possible.

Now disconnect the LED cable (two pin). It’s very delicate, so do this as carefully as possible.

There are two main hex screws to remove from the motherboard central area now. You can see them removed below near the middle (where the brass/gold coloured rings are).

With everything disconnected, carefully push the inner motherboard and it’s tray out, using your thumbs on the fan’s exhaust port. You should ideally position your thumbs on the screw hole areas of the fan exhaust port. It’ll pop out, then just very carefully push it all the way out.

The RAM area is protected by a metal ‘cage’. Unscrew it’s 4 x hex screws and slowly lift the cage off the RAM retainer clips.

Carefully push the RAM module retainer clips to the side (they have a rubber grommet type covering over them), and the existing SODIMM modules will pop loose.

mac mini SODIMM RAM modules and slots

Remove the old modules and replace with your new ones. Make sure you align the modules in the correct orientation. The slots are keyed, so pay attention to that. Push them down toward the board once aligned and the retainer clips will snap shut and lock them in place.

Replace the RAM ‘cage’ with it’s 4 x hex screws.

Reverse the steps you took above to insert the motherboard tray back into the chassis and re-attach all the cables and connectors in the correct order.

Make sure you didn’t miss any screws or cables when reconnecting everything.

Finally boot up and enjoy your cheap RAM upgrade.

Ingest CloudWatch Logs to a Splunk HEC with Lambda and Serverless

cloudwatch logs to splunk HEC via Lambda

I recently came across a scenario requiring CloudWatch log ingestion to a private Splunk HEC (HTTP Event Collector).

The first and preferred method of ingesting CloudWatch Logs into Splunk is by using AWS Firehose. The problem here though is that Firehose only seems to support an endpoint that is open to the public.

This is a problem if you have a Splunk HEC that is only available inside of a VPC and there is no option to proxy public connections back to it.

The next thing I looked at was the Splunk AWS Lambda function template to ingest CloudWatch logs from Log Group events. I had a quick look and it seems pretty out of date, with synchronous functions and libraries in use.

So, I decided to put together a small AWS Lambda Serverless project to improve on what is currently out there.

You can find the code over on Github.

The new version has:

  • async / await, and for promised that wrap the synchronous libraries like zlib.
  • A module that handles identification of Log Group names based on a custom regex pattern. If events come from log groups that don’t match the naming convention, then they get rejected. The idea is that you can write another small function that auto-subscribes Log Groups.
  • Secrets Manager integration for loading the Splunk HEC token from Secrets Manager. (Or fall back to a simple environment variable if you like).
  • Serverless framework wrapper. Pass in your Security Group ID, Subnet IDs and tags, and let serverless CLI deploy the function for you.
  • Lambda VPC support by default. You should deploy this Lambda function in a VPC. You could change that, but my idea here is that most enterprises would be running their own internal Splunk inside of their corporate / VPC network. Change it by removing the VPC section in serverless.yml if you do happen to have a public facing Splunk.

You deploy it using Serverless framework, passing in your VPC details and a few other options for customisation.

serverless deploy --stage test \
  --iamRole arn:aws:iam::123456789012:role/lambda-vpc-execution-role \
  --securityGroupId sg-12345 \
  --privateSubnetA subnet-123 \
  --privateSubnetB subnet-456 \
  --privateSubnetC subnet-789 \
  --splunkHecUrl https://your-splunk-hec:8088/services/collector \
  --secretManagerItemName your/secretmanager/entry/here

Once configured, it’ll pick up any log events coming in from Log Groups you’ve ‘subscribed’ it to (Lambda CloudWatch Logs Triggers).

add your lambda CloudWatch logs triggers and enabled them for automatic ingestion of these to Splunk

These events get enriched with extra metadata defined in the function. The metadata is derived by default from the naming convention used in the CloudWatch Log Groups. Take a close look at the included Regex pattern to ensure you name your Log Groups appropriately. Finally, they’re sent to your Splunk HEC for ingestion.

For an automated Log Group ingestion story, write another small helper function that:

  • Looks for Log Groups that are not yet subscribed as CloudWatch Logs Triggers.
  • Adds them to your CloudWatch to Splunk HEC function as a trigger and enables it.

In the future I might add this ‘automatic trigger adding function’ to the Github repository, so stay tuned!

Synchronizing tmux Panes in a Window

Splitting a tmux session window into multiple panes can do wonders for productivity. Here you’ll see how easy synchronizing tmux panes is.

But, what if you would like to use this feature to automate a workflow across many machines?

You’ll be glad to know it is possible to synchronize panes in a tmux window.
This allows you to execute a series of commands or particular workflow across many machines.

synchronize panes in tmux

First of all, if you haven’t already, split your window into the panes you need. The commands for this of course (assuming CTRL + B is prefix for tmux commands) are:

Split vertical: CTRL + B, %Split horizontal: CTRL + B, “

You may wish at this point to connect each pane to the relevant machine you want in each.

Synchronize the panes by entering tmux command mode with:

CTRL + B, :

Now type:

setw synchronize-panes on

Hit enter and you’ll immediately notice all the panes are now synchronized. At this point you can go wild and execute whichever workflow you want to automate across the subjects.

You can toggle the synchronization off again by entering command mode once more and typing:

:setw synchronize-panes off

You can also use the same command to toggle synchronization on/off by omitting the on/off parameter on the end. Synchronizing tmux Panes is toggled when omitting this parameter.

:setw synchronize-panes

Multipurpose FreeNAS Server Build

multipurpose freenas server build

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.

The intial hardware
Note: I got this Gigabyte B450 motherboard, but soon found out it did not support ECC.

Final specifications:

These are the final specifications I decided on. Scroll down to see the details about each area.

The Goals

The final home server build would need to meet many requirements:

  • It should provide a resilient, large shared storage pool for network file storage across multiple Windows PCs at home.
  • Support NFS storage for sharing persistent volumes to my Raspberry Pi Kubernetes Cluster.
  • It should be able to run Plex for home and remote media streaming.
  • It must be able to run Nextcloud for home and remote mobile file storage.
  • Run services in Virtual Machines, Jails, or Docker containers. For example, I like to run Pi-hole as a DNS server for all my home equipment and devices.

The Decision Process

I started out my search looking at two products. Unraid and FreeNAS.

I have had experience running FreeNAS in the past for home lab setups. I never really used it seriously with the goal of making it reliable though.

This time around, all my files would be at stake, so I did a fair bit of research into the features and offerings of both products.

Unraid performed quite well for me. But, what pushed me away from it was the fact that it is a paid for, closed source, commercial product.

Unraid does make it super easy to bundle storage together and expand that storage in future if need be. However FreeNAS’ use of ZFS and it’s various other features were what won me over.

The Build Details

Having settled on FreeNAS, I went about researching which hardware I would need. My goal here was to not spend too much money, but at the same time not cheap out and compromise on reliability.

CPU, Motherboard, RAM

ECC (Error Checking and Correction) RAM is very important for ZFS, so this is basically what my build hinged on.

I found that AMD Ryzen CPUs support ECC, and so do most Ryzen compatible motherboards.

Importantly, in my research I found that Ryzen APU CPUs do not support ECC. Make sure you do not get an APU if ECC is important to you.

Additionally, many others report much better stability running FreeNAS on AMD Ryzen Generation 2 chips and above. With this in mind, I decided I would use at least an AMD Ryzen 2xxx CPU.

On the ECC topic, I only found evidence of single bit error correction working on AMD Ryzen systems.

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.

checking ECC support with edac-utils
Checking ECC support with edac-utils

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.

the Asus Prime X470-Pro EFI BIOS

Storage

I used 4 x Western Digital 3TB Red hard drives for the RAIDZ1 main storage pool.

Western Digital 3TB Red hard drives

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.

Graphics Card

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.

A cheap AMD Radeon HD 6450 1GB DVI DisplayPort PCI-Express Graphics Card I used for the FreeNAS build.

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.

Network

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.

Intel dual port NIC

Configuration Highlights

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.

FreeNAS Configuration

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.

FreeNAS storage pool configuration
  • 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
    • Compression enabled
  • 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
    • Compression enabled

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.

Windows Shares

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.

FreeNAS Windows SMB share

Pi-hole Configuration

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.

pi-hole upstream DNS configuration with DNSSEC

NextCloud

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.

I detailed my full process in this blog post.

Plex

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.

Plex jail mount point

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.

NFS shares for Kubernetes in FreeNAS

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.

Next, I installed the NFS External-storage provisioner for Kubernetes on my Pi Cluster. I needed to use the ARM specific deployment manifest as Pi’s of course have ARM CPUs.

I modified the deployment manifest to point it to my FreeNAS machine’s IP address and NFS share path.

The kubernetes nfs client provisioner manifest configured for NFS storage provisioning.

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.

Final Thoughts

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.

Install and configure Nextcloud plugin on FreeNAS with SSL

Install and configure Nextcloud plugin on FreeNAS with SSL

The FreeNAS Nextcloud plugin installation works great with automatic configuration thanks to a recent pull request. But, you don’t get SSL enabled by default. This is critical, especially for a system exposed to the internet.

In this post you’ll see how to:

  • Install the Nextcloud plugin in a FreeNAS BSD jail
  • Add an extra NAT port for SSL to the jail
  • Configure NGINX inside the jail by adding a customised configuration with SSL enabled
  • Apply a free SSL certificate using Lets Encrypt and DNS-01 challenge validation
  • Look at some options for setting up home networking for public access

Start off by Installing the Nextcloud Plugin in a jail. Choose NAT for networking mode. It defaults to port 8282:80 (http).

the Nextcloud jail in the FreeNAS UI

Stop the jail once it’s running and edit it. Add another NAT rule to point 8443 to 443 for SSL.

the extra port 8443 - 443 NAT rule to add

The reason for selecting port 8443 for Nextcloud is because the FreeNAS web UI listens on port 443 for SSL too.

An alternative could be to use DHCP instead of NAT for the jail. I chose NAT for my setup as I prefer using one internal IP address for everything I run on the FreeNAS server.

Shell into the Nextcloud jail, and rename the default nginx configuration.

mv /usr/local/etc/nginx/conf.d/nextcloud.conf /usr/local/etc/nginx/conf.d/nextcloud.conf.old

NGINX will load all .conf files in this directory. Hence the reason you’ll create a new configuration for your SSL setup here.

ee /usr/local/etc/nginx/conf.d/nextcloud.conf /usr/local/etc/nginx/conf.d/nextcloud-ssl.conf

Populate it with the contents of the gist below, but replace server_name, ssl_certificate, and ssl_certificate_key with your own hostname.

Generate a free SSL certificate with Lets Encrypt

To configure the Nextcloud plugin on FreeNAS with SSL you don’t need to break the bank on SSL certificate costs from traditional CAs. Lets Encrypt it free, but you’ll need to renew your certificate every three months.

DNS-01 challenge certificate generation for Lets Encrypt is a great way to get SSL certificates without a public web server.

It entails creating a TXT/SPF record on the domain you own, with a value set to a code that certbot gives you during the certbot request process.

Install certbot if you don’t already have it installed. On a debian based system:

sudo apt-get install certbot

Request a certificate for your desired hostname using certbot with dns as the preferred challenge.

sudo certbot -d yournextcloud.example.net --manual --preferred-challenges dns certonly

Follow the prompts until you receive a code to setup your own TXT record with. Go to your DNS provider control panel and create it with the code you’re given as the value.

After creating the record, finish the certificate request. Lets Encrypt will confirm the DNS TXT record and issue you a certificate. You’ll get a chain file called fullchain.pem, along with a private key file called privkey.pem.

Upload the SSL certificate files to Nextcloud

Upload both to your Nextcloud Jail. Use SCP to copy them up, renaming them as follows:

  • /etc/ssl/nginx/yournextcloud.example.net.crt (certificate chain file)
  • /etc/ssl/nginx/yournextcloud.example.net.key (private key file)

Rename them as per your chosen hostname to keep things organised, and so that they match your nextcloud-ssl.conf file entries.

Port forwarding / NAT setup

This is the part that comes down to your own network setup. I use a double NAT setup, so I NAT traffic from my external router interface, through to another internal router.

From my internal router, I port forward / NAT from the internal router interface through to my FreeNAS box on port 8443.

From there, the Nextcloud jail does NAT to take the TCP traffic from 8443 to 443 inside the jail (where NGINX is listening on 443).

This is how my NAT and port forwarding chain looks:

Public_IP:29123 (WAN interface) -> Internal_IP:29123 (Internal router LAN interface) -> Internal_IP:8443 (FreeNAS LAN interface) -> Internal_IP:443 (Nextcloud Jail)

If you’re lucky enough to have a static IP address then you can point your DNS host record to your static IP. Otherwise you’ll neee to use some form of dynamic DNS service.

At this point you should have everything in place.

Final steps

Using a shell in the Nextcloud jail, restart nginx with service nginx restart. If all goes well you’ll see nginx started in the output of that command.

If not, you’re likely to have an NGINX configuration syntax error.

The logs are usually good about pinpointing these, so read them to see where you might have missed something obvious in the nextcloud-ssl.conf file. Adjust any errors and restart again.

The default credentials that for Nextcloud are in the home directory of the jail (/root). To retrieve them:

cat /root/ncuser
cat /root/ncpassword

Test logging in, and get started with personalising your Nextcloud system and adding some users.

Now you can enjoy the Nextcloud plugin on FreeNAS with SSL enabled.

Building a Pi Kubernetes Cluster – Part 3 – Worker Nodes and MetalLB

Building a Raspberry Pi Kubernetes Cluster - part 3 - worker nodes featured image

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.

E.g.

sudo kubeadm join 10.0.0.50:6443 --token kjx8lp.wfr7n4ie33r7dqx2 \
     --discovery-token-ca-cert-hash sha256:25a997a1b37fb34ed70ff4889ced6b91aefbee6fb18e1a32f8b4c8240db01ec3

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.

kubernetes worker node added to cluster

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:

kubectl apply -f https://gist.githubusercontent.com/Shogan/d418190a950a1d6788f9b168216f6fe1/raw/ca4418c7167a64c77511ba44b2c7736b56bdad48/metallb.yaml

Make sure the MetalLB pods are now up and running in the metallb-system namespace that was created.

metallb pods running

Now you will create a ConfigMap that will contain the settings your MetalLB setup will use for the cluster load-balancer services.

Create a file called metallb-config.yaml with the following content:

apiVersion: v1
kind: ConfigMap
metadata:
  namespace: metallb-system
  name: config
data:
  config: |
    address-pools:
    - name: default
      protocol: layer2
      addresses:
      - 10.23.220.88-10.23.220.98

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.

Install Helm Client

export HELM_VERSION=v2.9.1
wget https://kubernetes-helm.storage.googleapis.com/helm-$HELM_VERSION-linux-arm.tar.gz
tar xvzf helm-$HELM_VERSION-linux-arm.tar.gz
sudo mv linux-arm/helm /usr/bin/helm

Install Helm Tiller in the Cluster

Use the following command to initialise the tiller component in your Pi cluster.

helm init --tiller-image=jessestuart/tiller --service-account tiller --override spec.selector.matchLabels.'name'='tiller',spec.selector.matchLabels.'app'='helm' --output yaml | sed 's@apiVersion: extensions/v1beta1@apiVersion: apps/v1@' | kubectl apply -f -

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.

helm install --name nginx-ingress stable/nginx-ingress --set rbac.create=true --set controller.service.type=LoadBalancer

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:

new nginx ingress pods running with ARM image

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.

the nginx default backend 404 response

Concluding

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.