Back in 1994, during my M.Sc. in Computer Science, my research topic for my thesis was exam timetabling. Initially, I explored various heuristic algorithms to address the graph colouring problem. However, as you add more complex constraints for optimisation, it became evident that traditional heuristics weren’t quite cutting it. This led me to a shift towards genetic algorithms. At that time, they stood out as the superior strategy for tackling such multifaceted optimization challenges, offering a more dynamic and effective solution.

I started my career as a C++ developer. At the time, it was more or less considered the ‘default’ choice for software development. PERL was the new kid on the block for web application development. Python was just a scripting language pretending to be object-orientated and with a quirky way to delimit code blocks using indentation. JavaScript was brand spanking new, uncool, but the idea of running code in a browser was at least somewhat interesting.

In 2013 I wrote a blog post titled “Technical debt considered useful” in response to what I saw as an increasing trend by colleagues working in agile teams to see tech debt as a strictly “bad thing”. More recently, the DevOps movement (which is entirely positive for the software industry at large) has prompted some to adopt the idea that tech debt must be avoided at all costs. A post titled “Technical Debt - The Anti-DevOps Culture” inspired me to return to this topic - after all, a lot can change in 7 years.

I’ve always thought this lesson to be especially relevant to open source startups.

Introduction This is (hopefully) the first in a series of posts detailing my adventures with Spring Boot microservices on Kubernetes. My focus will be mostly on architecting, developing, monitoring, and maintaining microservices on Kubernetes and not so much on the administration or InfraOps challenges of maintaining a Kubernetes cluster. You shouldn’t be maintaining your own production Kubernetes cluster anyway - OpenShift is a great option for an on-premise cluster, and AWS, Google and Azure, along with many others, have great public cloud Kubernetes-based container platforms available.

Introduction This is what the Asterisk site says about it: “Asterisk is a free and open-source framework for building communications applications. Asterisk turns an ordinary computer into a communications server. Asterisk powers IP PBX systems, VoIP gateways, conference servers and is used by small businesses, large businesses, call centres, carriers and governments worldwide. " A large number of Asterisk installations seem to be PBX (private branch exchange) related for small to medium companies and some commercial PBX solutions such as SwitchVox are customised Asterisk appliances with a user-friendly GUI.

Introduction JavaCV is a Java wrapper to a number of computer vision libraries including OpenCV, OpenKinect and others. In this article we’ll look at using JavaCV with OpenCV to do real-time face and hand detection on a video stream. Face detection (as opposed to face recognition) has become mainstream with everything from Facebook to low-budget digital cameras supporting it. Hand detection and gesture recognition is somewhat less mature and I was hard pressed to find good open source implementations of this.

I have debt: a mortgage on my home and some credit card debt. Is debt a “bad thing”? Well, yes. In the sense that I would much rather not have to pay off my mortgage every month. If I didn’t have a mortgage I’d have an extra bit of cash left every month that I can do far better things with. But was my mortgage useful to me? Hell, yeah! Without it, I probably wouldn’t own my own home now and if I rented something comparable, the rent would in all likelihood be more than what it costs me to service my mortgage at the moment.