[community workshop] Pedro makes coffee with Juju

:desert_island: Join another community session, this friday we will look into a project making coffee :coffee: with Juju! :juju:

@pedroleaoc takes us on an adventure through hardware, open-source IoT - to brew coffee!

We will see some Kubernetes, clouds and the “Barista” K8s operator charm to control coffee machines!

WHEN: Friday October 29:th 2021, Time: 09:00AM UTC.

Link to google meeting: https://meet.google.com/hfr-yzhq-rps

This is what we’ll cover:

In this technical session, you will see and learn about:

  • Open source, cloud native coffee making
  • Programming an ESP8266 microcontrollers to hack appliances machine
  • Using Juju and Charmed Operators
  • Developing an interactive user interface with Flutter, Ubuntu Core, Ubuntu Frame and Raspberry Pis
  • Cloud Native observability with Prometheus, Grafana and MicroK8s
  • How to scale device and server applications using Kubernetes

Ideally prepare BEFORE the workshop to be more up to speed.

  1. Setup your juju client and connect to a cloud. Here are instructions for two public clouds:

    AWS -> Juju | About credentials Google -> https://juju.is/docs/olm/google-gce#heading--using-environment-variables

  2. Create a Ubuntu one account: https://login.ubuntu.com/ which is needed to deploy publicly available charms from charmstore.io

Using your own private cloud (lxd, vshpere, maas or openstack) is of course cool.

Please ping in the thread if you intend to join so that I know if I got a crowd or not!



This is aimed at total beginners at both Juju and electronics. You are more than welcome to pop by and ask questions about cloud infrastructure or installing a new outlet :slight_smile:


This is so cool, I’ll definetely attend!

I have some NodeMCU boards with ESP8266 that I’ve used mainly with MicroPython, what kind of firmware will be used in the workshop?

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Hey Juliana, for this project, I used Arduino because I know the libraries quite well. For a next version of this, I would definitely look into MicroPython or EdgeX Foundry.