Essays on software development with a focus on quality and production engineering. Mostly.
A good philosophy to live by at work is to “always be quitting”. No, don’t be constantly thinking of leaving your job 😱. But act as if you might leave on short notice 😎. Counterintuitively, this will make you a better engineer and open up growth opportunities. A thread 👇. So what does it mean to always be quitting? It means “making yourself replaceable”; “deprecating yourself”; “automating yourself out of your job”.
Companies grow, and with them do the software projects that support them. It should be no surprise that larger programs require longer build times. And, if I had to guess, you have seen how those build times eventually grow to unbearable levels, reducing productivity and degrading quality. In this post, I examine how we can leverage the common techniques we use for production services—namely SLIs and SLOs—to keep build times on track.
Last week, I was first-time on-call for a part of Azure Storage. My previous background as an SRE at Google helped me remain calm despite my inexperience. And as we have more first-time on-callers joining soon, I couldn’t resist writing some advice for them. Let’s start! 🧵
Monorepos are an interesting beast. If mended properly, they enable a level of uniformity and code quality that is hard to achieve otherwise. If left unattended, however, they become unmanageable monsters of tangled dependencies, slow builds, and frustrating developer experiences. Whether you have a good or bad experience directly depends on the level of engineering support behind the monorepo. Simply put, monorepos require dedicated teams and tools to run nicely. In this post, I will look at how almost-perfect caching plays a key role in keeping build times manageable under such an environment.
After a very active month of development since the 0.5 announcement, it is time to welcome EndBASIC 0.6! This new 0.6 release is super-exciting for three reasons: preliminary GPIO support in the standard library specifically tailored to the Raspberry Pi; multidimensional array support in the language; and availability of binary releases for the most common platforms. You can dive right in by: visiting https://endbasic.jmmv.dev/ for an interactive session, reading more about the project at https://github.
Say you want to copy a large collection of files to a file server on your same network. What’s the fastest way to do this initial copy? Physically attaching the drive to the server? Maybe, but will the file systems be compatible? What about using the network? If so, which protocol? Read on for more details and how tar plus Netcat delivered the best results.
One thing that bothers me quite a lot about various language implementations is that the core of their interpreter isn’t clearly separate from their standard library. This makes it hard to embed those interpreters into other programs because it’s not obvious how to limit their side-effects and because the interpreter dependency can be heavy. In this post, we will see how EndBASIC’s design tries hard to keep the core as small as possible, and we will see some examples on how to use EndBASIC from Rust and vice versa.