Raspberry Pi Cluster Emulation With Docker Compose

Not long after the first Raspberry Pi was released in 2012, several set out to build them into low-cost clusters, often for their research and testing purposes. Interns at  DataStax built a multi-datacenter, 32 nodes  Cassenda fault-tolerance demo, complete with a big red button to simulate the failure of an entire datacenter.  David Guill built a  40-node Raspberry Pi Cluster that was intended to be part of his MSCE thesis.  Balena, built " The Beast", a 120 node Raspberry Pi cluster, for scaled testing of their online platform. And on the extreme end of the spectrum, Oracle built a  1060 node Raspberry Pi Cluster, which they introduced at Oracle OpenWorld 2019.

Innovation with the Raspberry Pi continues as they are turned into everything from wi-fi extenders, security cameras, and even bigger clusters. While the main value of these clusters is inherent in their size and low cost, their popularity makes them an increasingly common development platform. Since the Raspberry Pi uses an ARM processor, this can make development problematic for those of us who work exclusively in the cloud. While commercial solutions exist, we will be building our own emulated cluster using a fully open source stack hosted on Google Compute Engine.

Use Cases

Other than learning from the experience, Dockerizing an emulated Raspberry Pi enables us to do three things. One, it turns into software that would otherwise be a hardware-only device that nobody has to remember to carry around (I’m always losing the peripheral cables). Two, it enables Docker to do for the Pi what Docker does best for everything else: it makes software portable, easy to manage, and easy to replicate. And three, it takes up no physical space. If we can build one Raspberry Pi with Docker, we can build many. If we can build many, we can network them all together. While we may encounter some limitations, this build will emulate a cluster of Raspberry Pi 1s that’s logically equivalent to a simple, multi-node physical cluster.

#cloud #tutorial #docker #kubernetes #cloud native

What is GEEK

Buddha Community

Raspberry Pi Cluster Emulation With Docker Compose

Tools and Images to Build a Raspberry Pi n8n server

n8n-pi

Tools and Images to Build a Raspberry Pi n8n server

Introduction

The purpose of this project is to create a Raspberry Pi image preconfigured with n8n so that it runs out of the box.

What is n8n?

n8n is a no-code/low code environment used to connect and automate different systems and services. It is programmed using a series of connected nodes that receive, transform, and then transmit date from and to other nodes. Each node represents a service or system allowing these different entities to interact. All of this is done using a WebUI.

Why n8n-pi?

Whevever a new technology is released, two common barriers often prevent potential users from trying out the technology:

  1. System costs
  2. Installation & configuration challenges

The n8n-pi project eliminates these two roadblocks by preconfiguring a working system that runs on easily available, low cost hardware. For as little as $40 and a few minutes, they can have a full n8n system up and running.

Thanks!

This project would not be possible if it was not for the help of the following:

Documentation

All documentation for this project can be found at http://n8n-pi.tephlon.xyz.

Download Details:

Author: TephlonDude

GitHub: https://github.com/TephlonDude/n8n-pi

#pi #raspberry pi #raspberry #raspberry-pi

Adnan Malik

1599279212

How to Emulate a Raspberry Pi Cluster with Docker Compose

This guide discusses everything needed to build a simple, scalable, and fully binary compatible Raspberry Pi cluster using QEMU, Docker, Docker Compose, and Ansible.

Introduction

The Raspberry Pi is no longer just a low-cost platform for students to learn computing, it’s now a legitimate research and development platform that’s used for IoT, networking, distributed systems, and software development. It’s even used administratively in production environments.

Not long after the first Raspberry Pi was released in 2012, several set out to build them into low-cost clusters, often for research and testing purposes. Interns at DataStax built a multi-datacenter, 32 nodes Cassenda fault-tolerance demo, complete with a big red button to simulate the failure of an entire datacenter. David Guill built a 40-node Raspberry Pi Cluster that was intended to be part of his MSCE thesis. Balena, built “The Beast”, a 120 node Raspberry Pi cluster, for scaled testing of their online platform. And on the extreme end of the spectrum, Oracle built a 1060 node Raspberry Pi Cluster, which they introduced at Oracle OpenWorld 2019.

#docker #serverless #raspberry-pi

TensorFlow Lite Object Detection using Raspberry Pi and Pi Camera

I have not created the Object Detection model, I have just merely cloned Google’s Tensor Flow Lite model and followed their Raspberry Pi Tutorial which they talked about in the Readme! You don’t need to use this article if you understand everything from the Readme. I merely talk about what I did!

Prerequisites:

  • I have used a Raspberry Pi 3 Model B and PI Camera Board (3D printed a case for camera board). **I had this connected before starting and did not include this in the 90 minutes **(plenty of YouTube videos showing how to do this depending on what Pi model you have. I used a video like this a while ago!)

  • I have used my Apple Macbook which is Linux at heart and so is the Raspberry Pi. By using Apple you don’t need to install any applications to interact with the Raspberry Pi, but on Windows you do (I will explain where to go in the article if you use windows)

#raspberry-pi #object-detection #raspberry-pi-camera #tensorflow-lite #tensorflow #tensorflow lite object detection using raspberry pi and pi camera

Building 28-Core Raspberry Pi Cluster from Scratch: Release The Kraken

Octo_pains_

In October 2018, more than a year after  building my first cluster Octopi, I had officially outgrown the cluster. I started noticing the performance bottlenecks started when I tried to run Wordpress on it, where a single page load of a newly installed Wordpress blog takes about 10 seconds! Nevertheless, all that was unsurprising given the measly single-core 700MHz processor on each node.

At that point in time, I’ve graduated from university then and secured a job as a Data Scientist + Full-Stack Engineer at a startup and I thought to myself:

What better a time to build myself a new cluster?

Kraken

The second cluster was named Kraken.

The kraken (/ˈkrɑːkən/)[1] is a legendary cephalopod-like sea monster of gigantic size in Scandinavian folklore. (Wikipedia)

The Kraken is basically a much bigger and monstrous octopus, hence the name, symbolizing an evolution of the first cluster. It was built out of 7 Raspberry Pi 3Bs powered by a single USB charger.

With my first pay check, I had initially intended to finally build a cluster of 8 nodes but once again I was unable to realize this cursed idea. The maximum number of ports on a consumer-grade network switch was 8, enough for 7 nodes and a cable to the router.

| Item        | TP-Link 8-port Switch | TP-Link 16-Port Smart Switch |
|-------------|-----------------------|------------------------------|
| Cost (SGD)* | S$26.46               | S$195.03                     |
| Cost (USD)  | $18.99                | $139.97                      |
* SGD/USD exchange rate is 0.71770 as of the time of writing

An alternative was to use commercial-grade network switches with 16 ports but that was obviously was out of the question (and budget).

#raspberry-pi #docker #docker-swarm #cluster-build #hardware #hackernoon-top-story #diy #kubernetes

August  Murray

August Murray

1617922140

Pi-hole on Raspberry Pi using Docker & Docker Compose

I need to start this article with some simple disclaimers: I love Raspberry Pi, I love Docker, I don’t love networking that much (spoiler alert: I suck at it).

  • I love Raspberry Pi because it is a tiny, fully functioning computer that gives me goosebumps. It is one of those things that makes you feel like Mr. Robot. It is relatively cheap, it is accessible, and there are tons of guides online to do pretty much anything you can imagine.
  • I love Docker because it is a simple way of running various pieces of software in a standardized way: you pull the Docker image for your platform, you run the image with a single command and that’s it! You can glue things together, you can add your own images, you can share your configuration, you can run the same setup on different machines, and you can destroy things easily once you don’t need them anymore. I am not saying it is the simplest software ever, but it is relatively easy to play around with.
  • I don’t love networking much, simply because I suck at it. I have a basic understanding of high-level concepts about many parts of it, but they don’t always translate to how things work in real life. I roughly know how computers communicate over a network, but I quickly get lost when I need to debug a bad connection for example. The good thing is that it means I’ll aim to keep this guide as simple as possible so that I can understand it as well.

So, since we are done with the disclaimers, let’s touch on the basics a bit before we get on with the guide. If you know all the tools and technologies mentioned above, feel free to skip that part.

#raspberry-pi #software-development #advertising #docker #privacy