Sam McGeown
Sam has been working in the IT industry for nearly 20 years now, and is currently working for VMware as a Senior Technical Marketing Manger in the Cloud Management Business Unit (CMBU) focussed on Automation. Previously, he has worked as consultant for VMware PSO, specializing in cloud automation and network virtualization. His technical experience includes design, development and implementation of cloud solutions, network function virtualisation and the software defined datacentre. Sam specialises in automation of network virtualisation for cloud infrastructure, enabling public cloud solutions for service providers and private or hybrid cloud solutions for the enterprise.
Sam holds multiple high level industry certifications, including the VMware Certified Design Expert (VCDX) for Cloud Management and Automation. He is also a proud member of the vExpert community, holding the vExpert accolade from 2013-present, as well as being selected for the vExpert NSX, vExpert VSAN and vExpert Cloud sub-programs.
As more services go live on my Kubernetes clusters and more people start relying on them, I get nervous. For the most part, I try and keep my applications and configurations stateless - relying on ConfigMaps for example to store application configuration. This means with a handful of YAML files in my Git repository I can restore everything to working order. Sometimes though, there’s no choice but to use a PersistentVolume to provide some data persistance where you can’t capture it in a config file.
If you’re anything like me, your home lab is constantly changing, evolving, breaking, rebuilding. For the last year or so I’ve been running all my home kubernetes workloads on a Raspberry Pi cluster - and it’s been working really well!
I’ve been through several iterations - for example firstly running on SD cards (tl;dr - it’s bad, they wear out really fast with Kubernetes on board!), then PxE booting them from my Synology to it’s now current state of booting directly from SSDs.
In the most recent round of vExpert sub-program applications, I was asked to help review applications for the vExpert Cloud Management track. As part of the CMBU and a long-standing vExpert it made sense for me to help out, and I was happy to do so. I reviewed ~60 of the applications that were in my area - automation. The experience was an eye-opener. What follows is a distillation of what (not) to do when you’re writing your application.
Since I started learning Kubernetes the Certified Kubernetes Administrator (CKA) exam has been a target for me, but it’s always seemed to be out of reach. The whole Kubernetes ecosystem is a vast and nebulous beast, with new projects rising to the fore all the time, and old projects fading from favour. The size and rapid development that make the field so interesting and powerful, are the same properties that make the learning curve so steep, and the entry bar so high.
Up until recently I’ve been running a Windows Server Core VM with Active Directory, DNS and Certificate Services deployed to provide some core features in my home lab. However, I’ve also been conscious that running a lab on old hardware doesn’t exactly have much in the way of green credentials. So, in an effort to reduce my carbon footprint (and electricity bill) I’ve been looking for ways to shut down my lab when it’s not in use.
I’ve posted previously about moving to Hugo as a publishing platform for this blog, this post is a bit more about how I’m managing the publishing using GitLab’s CI/CD Pipelines.
Firstly, I need to mention that I’m using three different repositories for my code base, and why. The three repositories are:
definit-hugo - this contains the hugo site configuration definit-content - this contains the site content - markdown files, images etc definit-theme - this contains the VMware Clarity-based theme I use for my site definit-content and definit-theme are git submodules in the definit-hugo project, mapped into the /content and /themes folders respectively.