James Read's Code, Containers & Cloud blog

I aggressively use Prometheus in my day-to-day life, not just for regular technical and application metrics, but for everything I can get an exporter for.

I have a Prometheus exporter for my Gmail inbox (personal and work), for my Google calendar (mostly work), all my websites I’ve written export prometheus metrics, I monitor my servers CPU and Memory usage with Prometheus metrics, but also their Hard Drive SMART status. I even have a Prometheus exporter for my fledgling weight loss program. Domain expiry, GitHub stars, virtual machine status, even databases and the watch status of my media library!

Sometimes you need to write a HTML webpage that is based on some sort of data file, like YAML files. Rather than having a server-side script generate the HTML, you can generate the HTML page statically, making it easier to host and cache.

I thought about writing a tool myself to do this, but thankfully, I found Gomplate. It is a powerful Go-based template renderer that allows you to generate dynamic content from various data sources, including YAML files. With Gomplate, you can easily transform your YAML data into HTML pages, making it a great tool for generating pretty HTML from YAML.

This week was totally normal and routine for me, I’m sitting here on a Friday thinking that it’s been the same as many other weeks I’ve had in my life as a Tech Seller at Red Hat. Enjoyable, busy, varied, etc. However, I am noticing a change in how I go about my week - that change is that more and more of my colleagues are using AI.

On the one hand this is fantastic, the democratisation of AI, led by services like ChatGPT mean that anyone without any technical background or grounding in the principles of AI doesn’t have to worry about HOW any of those services work, they use use them.

I’ve been working at Red Hat for for 13 years, so people will often come to me ask for guidance of where to get started with their Red Hat certification journey. So many people have heard of the RHCE - the Red Hat Certified Engineer exam, which remains one of the most respected IT certifications in the industry, let alone just Linux certifications.

Many of these same people have years of Linux experience, but maybe haven’t taken a Red Hat certification before, or in a long time, and are looking for recommended next steps. While going straight for RHCE might sound alluring at first, aiming so high is probably an overly ambitious target to start with. If you think this might be you, then continue reading for some tips!

This is a blog post written as a summary of notes, following my learnings from an AI course I completed back in 2019 that I feel is still incredibly relevant in 2024]({{ rel ‘../how-useful-way-my-ai-short-course-from-2019/’ }}).

AI is a huge field with an expansive history extending over the last century, it might be easy to be fooled into thinking thay AI was just something we found in the last 5 years. However, the recent surge of interest cannot be ignored - popularized by easy and cheap access to incredibly sophisticated models like ChatGPT.

In 2019 I could see that AI was a technology gaining increasing interest and relevance, and I was keen to get ahead of the hype and start learning more. At the time I was feeling like my day to day routine was getting a bit boring, and too familiar, and I wanted to make sure I had a solid grasp of what I thought would become a fundamental building block of technology for the future, and I decided to take a course on the topic of AI.

I am so sick and tried of changing task management systems, I will just be using plain .txt files from now on.

In the last 10 years, I have tried so many different systems for organising my work and my personal life and yet I’ve not been able to keep using one of them after a few weeks or months. After all this time I think I’ve finally come to the realisation that they all suffer from the same inadequacies. Before anybody recommends me their favourite, here is a list of apps I’ve tried; RememberTheMilk (~2011), Trello, Google Keep (~2015), Google Tasks (~2022), Todoist (~2018 I think, but again in ~2023), and of course, because I am developer with a hammer (ie: the ability to write code), I had to write my own - wacky-tracky. I have probably had the most all around success with TaskWarrior (until recently).

It can be a real effort to bring yourself to write articles to maintain a healthy blog, and sometimes the simple articles are best. Therefore, I just want to take a quick few moments to talk about a tool that I just cannot live without now-a-days, when writing Go code, I am always live-reloading with Air in the background.

It’s really valuable for developers to be able to get fast feedback on the code that they are writing. Many of use will use one monitor for the code in web applications, for example, and another monitor for the web browser to quickly glance to the side, and refresh the page. However with non-web applications, it can be a little more tedious to compile, re-run tests, and run the application once again. Of course it isn’t difficult - most developers of microservices and similar will have a terminal window open on that second monitor, and they’ll hit Up on the keyboard to get the last command, make, ./myapp, etc.

A fault domain (or failure domain) is essentially a set of resources, or components that share a common point of failure. One example of this is an Azure Availability Zone, or your own single Data Center. Typical points of failure for a fault domain are power (with no backup generator), or cooling, or a datacenter is served by a single network connection. The term “fault domain” could theoretically be applied to smaller areas of an application architecture, like a single network, or a rack of servers, but this article considers a fault domain more from a cloud architecture definition.

Google Photos, the free, easy to use, on-for-many-android-users service has been the single Photo backup strategy for many of those who have used it, since it was released in 2015. I, for one, was amazed to discover that I have uploaded photos dating as far back as 2005, totalling over 80Gb. Initially, Google photos seemed like that ultimate, hassle-free, cloud backup service that would never be replaced…. However, as time went on, I found myself growing increasingly concern about cloud services that “own” my personal data. and I’ve just now managed to clear my data out of Google Photos.