Bare-Metal K8s Cluster with Raspberry Pi – Part 3

This is a continuation from the post series Bare-metal K8s cluster with Raspberry Pi – Part 1 & Part 2 here

Another option of running bare-metal K8s cluster in the Raspberry Pi I tried and tested was with Micro K8s which we discuss in this post.

Micro K8s are Lightweight upstream K8s. They are smallest, simplest, pure production K8s. For clusters, laptops, IoT and Edge, on Intel and ARM.

MicroK8s is a CNCF certified upstream Kubernetes deployment that runs entirely on your workstation or edge device. Being a snap it runs all Kubernetes services natively (i.e. no virtual machines) while packing the entire set of libraries and binaries needed. Installation is limited by how fast you can download a couple of hundred megabytes and the removal of MicroK8s leaves nothing behind.

And to give a context on snap, Snaps are app packages for desktop, cloud and IoT that are easy to install, secure, cross‐platform and dependency‐free. Snaps are discover able and install able from the Snap Store, the app store for Linux with an audience of millions.

A snap is a bundle of an app and its dependencies that works without modification across Linux distributions.

We are going to use the same components list as described in the Part 1 of this series.

Each Pi is going to need an Ubuntu server image and you’ll need to be able to SSH into them. Please follow this link here will help us to reach to this stage

Kubernetes Cluster Preparation with SSH connection to the Pi from your terminal

Installing MicroK8s
Follow this section for each of your Pis. Once completed you will have MicroK8s installed and running everywhere.

SSH to your first Pi and install the MicroK8s snap:

sudo snap install microk8s --classic

As MicroK8s is a snap and as such it will be automatically updated to newer releases of the package, which is following closely upstream Kubernetes releases, so we don’t need to worry about the K8s version we’re installing

sudo snap install microk8s --classic --channel=1.15/stable
Channels are made up of a track (or series) and an expected level of stability, based on MicroK8s releases (Stable, Candidate, Beta, Edge). For more information about which releases are available, run:

snap info microk8s

Cheat Sheet for MicroK8s
Before going further here is a quick intro to the MicroK8s command line:

  • microk8s.start – start all enabled Kubernetes services
  • microk8s.inspect – status of services
  • microk8s.stop – stop all Kubernetes services
  • microk8s.enable dns – enable Kubernetes add-ons,“kubedns”
  • microk8s.kubectl cluster-info – status of the cluster:

MicroK8s is easy to use and comes with plenty of Kubernetes add-ons you can enable or disable.

Master node and leaf nodes
Now that you have MicroK8s installed on all boards, pick one which has to be the master node of your cluster.

On the chosen Master node, run the following command:

sudo microk8s.add-node
This command will generate a connection string in the form of :/.

Adding a node
Now, you need to run the join command from another Pi you want to add to the cluster:

microk8s.join 10.55.60.14:25000/JHpbBYMIevZSAMnmjMHmFwanrOYCWZLu
You should be able to see the new node in a few seconds on the master with the following command:

microk8s.kubectl get node

For each new node, you need to run the microk8s.add-node command on the master, copy the output, then run microk8s.join on the leaf.

Removing nodes
To remove a node, run the following command on the master:

sudo microk8s remove-node
The name of nodes are available on the master by running the microk8s.kubectl get node

Alternatively, you can leave the cluster from a leaf node by running:

sudo microk8s.leave

Once Pis are setup with MicroK8s, adding and removing nodes is easy and you can scale up or down as you go.

Voila..!!
If you follow this series, you are now in control of your Kubernetes cluster. One with native kubernetes and docker and the other one with more easier to install and manage MicroK8s

This completes the 3 part series for K8s in Raspberry Pi. In a new follow-up blog post we can see how we can use kubectl & helm charts to deploy a Nginx service, Prometheus and few other services from the DevOps tools set to the cluster.

Bare-Metal K8s Cluster with Raspberry Pi – Part 1

There are multiple ways we can use a Kubernetes cluster to deploy our applications. Most of us opt to use any Kubernetes service from a public cloud provider. GKE, EKS, AKS are the most prominent ones. Deploying a Kubernetes cluster on a public cloud provider is relatively easy, but what if you want a private bare-metal K8s cluster. Being worked extensively in the data center and started my career as a Sys Admin, I personally prefer a piece of tangible hardware to get the feel of building it. This blog post walk you through the steps I took in order to have a bare-metal K8s cluster to play with.

K8s is an open source container orchestration platform that helps manage distributed, containerized applications at a massive scale. Born at Google as Borg, version 1.0 was released in July 2015. It has continued to evolve and mature and is now offered as a PaaS service by all of the major cloud vendors.

Google has been running containerized workloads in production for more than a decade. Whether it’s service jobs like web front-ends and stateful servers, infrastructure systems like Bigtable and Spanner, or batch frameworks like MapReduce and Millwheel, virtually everything at Google runs as a container.

You can find the paper here.

Kubernetes traces its lineage directly from Borg. Many of the developers at Google working on Kubernetes were formerly developers on the Borg project. We’ve incorporated the best ideas from Borg in Kubernetes, and have tried to address some pain points that users identified with Borg over the years.

More than just enabling a containerized application to scale, Kubernetes has release-management features that enable updates with near-zero downtime, version rollback, and clusters that can ‘self-heal’ when there is a problem. Load balancing, auto-scaling and SSL can easily be implemented. Helm, a plugin for Kubernetes, has revolutionized the world of server management by making multi-node data stores like Redis and MongoDB incredibly easy to deploy. Kubernetes enables you to have the flexibility to move your workload where it is best suited. This compliments the hybrid cloud story and in my career it has become more apparent that my customers see this as well to help them resolve issues like; cost, availability and compliance. In parallel software vendors are starting to embrace containers as a standard deployment model leading to a recent increase in requests for container solutions.

As you can see in the workflow comparison below, there is greater room for error when deploying on-premises. Public clouds provide the automation and reduces the risk of error as less steps are required. But as mentioned above, private cloud provides you more options when you have unique requirements.

Pros:

  • Using Kubernetes and its huge ecosystem can improve your productivity
  • Kubernetes and a cloud-native tech stack attracts talent
  • Kubernetes is a future proof solution
  • Kubernetes helps to make your application run more stable
  • Kubernetes can be cheaper than its alternatives

Cons:

  • Kubernetes can be an overkill for simple applications
  • Kubernetes is very complex and can reduce productivity
  • The transition to Kubernetes can be cumbersome
  • Kubernetes can be more expensive than its alternatives

Pre-requisites:

Compute:

3 x Raspberry Pi 4 Model B with 2 GB RAM
1 x Raspberry Pi 3 Model B+ with 1 GB RAM

Storage:

4 x 16GB High Speed Sand-disk Micro-SD Cards

Network:

1 x Network Switch – for local LAN for k8s internal connectivity
1 x Network Router – for Wifi (My default ISP router was used here) only master node had internet connectivity once completed the setup
4 x Ethernet Cables
1 x Keyboard, HDMI, Mouse (for initial setup only)

Initial Raspberry Pi Configuration:

Flash Raspbian to the Micro-SD Cards

Download image from the below link,

Raspbian OS

I have used BalenaEtcher to flash image onto micro-SD card

Perform Initial Setup on Boot on startup screen, we need to connect keyboard, monitor and mouse for this setup.

Choose Country, Language, Timezone
Define new password for user ‘pi’
Connect to WiFi or skip if using ethernet
Skip update software (We will perform this activity manually later).
Choose restart later

Configure Additional Settings Click the Raspberry Pi icon (top left of screen) > Preferences > Raspberry Pi Configuration

System

Configure Hostname
Boot: To CLI

Interfaces
SSH: Enable

Choose restart later

Configure Static Network Perform one of the following:
Define Static IP on Raspberry Pi: Right Click the arrow logo top right of screen and select ‘Wireless & Wired Network Settings’

Define Static IP on DHCP Server: Configure your DHCP server to define a static IP on the Raspberry Pi Mac Address.

Reboot and Test SSH
Username: pi

Password: Defined in step 2 above

From the terminal ssh pi@[IP Address]

Repeat steps for all of the Raspberry Pis.

Kubernetes Cluster Preparation with SSH connection to the Pi from your terminal. I am using a 12 years old Lenovo laptop running MX Linux. Open a terminal and establish ssh connection to the Pi

Perform Updates

apt-get update: Updates the package indexes
apt-get upgrade: Performs the upgrades

Configure Net.IP4.IP configuration Edit sudo vi /etc/sysctl.conf, uncomment net.ipv4.ip_forward = 1 and add net.ipv4.ip_nonlocal_bind=1.
Note: This is required to allow for traffic forwarding, for example Node Ports from containers to/from non-cluster devices.

Install Docker

curl -sSL get.docker.com | sh

Grant privilege for user pi to execute docker commands

sudo usermod pi -aG docker

Disable Swap

sudo systemctl disable dphys-swapfile.service
sudo reboot

We can verify this with the top command, on the top left corner next to MiB Swap should be 0.0.

As we completed the initial steps to create our K8s bare-metal cluster, we can see how we build the cluster in Part 2 of this blog post