Tech

I bought a Brother MFC-L2710DW multi-function laser printer and scanner. I bought it in Germany. When I turned on the machine for the first time it asked me to pick my country. The only options were Germany and Austria.

Include the current application environment in your prompts.

Give yourself an alert about the current Kubernetes namespace when launching a Bash shell or Rails console.

Running Python, Ruby, and Perl from one Bash script to detect the CD-ROM drive tray status using Linux ioctl.

The Sun Ultra 24 is objectively one of the most beautiful enterprise workstations ever created. I picked one up last year but its hardware is rather dated and needs an upgrade to keep it as a daily driver. Let’s do it. Background The Sun Ultra 24 was one of the last workstations from Sun Microsystems. In their final years of making workstations they started offering x86-based systems with AMD Opteron or Intel Core 2 64-bit CPUs.

In this guide we’ll setup cloudflare and Pi-hole together with docker-compose to create a portable and reproducible secure DNS solution.

Take a look at your monthly invoice from your ISP. If you have a line item for equipment rentals, you’re being ripped off.

In my previous post Generating static data with Elixir comprehensions I showed how you can use comprehensions to generate static data in your Elixir application. That static data was stored as a Map in a module attribute and accessible with a function that returns the Map itself. When building your application, you probably know how the static data will be accessed. Elixir has various ways of accessing data in a List, Keyword, or Map, and there are big differences in performance based on the size of tha data set.

A common requirement in software is to have a static data resource in your application or library. These are typically resources that changes so infrequently that releasing a new version for a data change is fine. Of course you can build these data by hand, but this is error-prone and makes rebuilding the static data more labour intensive. These problems are exacerbated by larger data sets. As good lazy (i.e. efficient) developers we can use code to solve these problems.

When I start a new project or get setup to contribute to an existing one, the first thing on my mind is: show me the Dockerfile. Why? One of the main purposes of Docker is packaging an application with its dependencies into a portable image that can be run on most any host, thus simplifying deployments. Yet when it comes to development of these applications, Docker is often not part of the picture.