Weekend Deployment, Upskilling

I’ve got a weekend to myself, it’s not uncommon, but this weekend the wife has gone away to watch Foo Fighters. I’m not jealous, I’m not fond of crowds and I don’t like travelling to London (or down South in general). When I win the lottery and can afford to have private gigs for my family then all will be cool.

So yes, on a weekend when I am on my own I can be a bit of a sad nut, especially on weekends like this one when I will be starting a week of on-call for work. I often find on-call quite traumatic, particularly as I can be a bit of a “Sev 1 Magnet” as my colleagues would describe me. This is another story, which I will discuss at some later date.

To try and keep myself distracted in these times of heightened anxiety, maintaining my sanity and avoiding exacerbating an existing health concern I like to use the time to upskill.

Now that I’ve had my early morning walk and exercise, I have decided to learn Kubernetes properly. I’ve dabbled with Docker quite a bit now and some of the tooling around it but I’ve not had the opportunity to use K8s.

Being a firm believer of implementing Infrastructure and Configuration as Code, I’ve decided I’m going to apply the rigour of everything I do being committed to a git repository as either Ansible or Terraform code, sat beneath the Kubernetes deployment YAML.

Obviously this may take a few weekends for me to progress but I’m that much of a sad nut when I’ve got a weekend to myself.

The command center, Dreadfort

First thing is first, time to test the deployment of Minikube and Kubectl in my Vagrant environment using Ansible, before deploying to my “Production” environment and getting started.

It sounds like overkill, I know, but without this kind of rigour mistakes might be made that costs me more in time. As we all know, operations time is expensive and my time is valuable to me.

I hope to share some of my code as a “playground” repository soon that demonstrates the process of going from “code + public cloud provider” to “functioning Kubernetes Cluster”.