Build performance has always been important to me, but my pain tolerance has always varied widely depending on the project. The projects I have worked on which require the JVM, such as Jenkins or JRuby/Gradle, anything under 30 seconds seems amazing. For small Node and Ruby projects, anything over a few seconds feels atrocious. Since I’ve been hacking with Rust lately, I haven’t been able to figure out what constitutes “acceptable.” For my relatively small project, incremental compilation was very quick, but for some reason linking the project would talk almost 10 seconds. That seemed pretty unacceptable.

If the people I know tweet enough about something, eventually I’m bound to breakdown and just buy the thing. It happened with the Intel NUC, and now it’s happened with Yubikey. The Yubikey is a USB-based security device that can do a lot of things, but in my case I just need it to act as a security key for a number of websites such as GitHub, Google, and Twitter. Much to my dismay it did not work exactly as I expected right out of the box on my openSUSE-based laptop.

People will sometimes look at my screen covered in terminal windows overflowing with text: “how do read all that?” These moments remind me how inscrutable backend development can appear to the outsider. Today I would like to introduce a tool that I hope makes a some parts a little more easy to understand: Kafkakitty

This year I have been struggling to learn Rust, but I am now pleased to share that I’m finally understanding the language. Earlier I lamented the challenges of adopting Rust. Between semantically important apostrophes and angle-brackets a plenty, I was struggling to read and write basic Rust. I can easily read Ada, C, Python, JavaScript, Java, and Ruby. Something about the syntax of Rust remained difficult to process. The code looked jarring and dissonant, I could read snippets but translating entire functions or modules into a workable mental model was not feasible. Over the past month however, I believe I have made some progress up the learning curve. I can now write some Rust!

This week we launched the Scribd tech blog, on which I published today’s article: We’re building the largest library in history. I frequently have to remind myself that I have been here less than a year, and we have undergone incredible positive change, with more coming in 2020.

I have a love/hate relationship with containers. We have used containers for production services in the Jenkins project’s infrastructure for six or seven years, where they have been very useful. I run some desktop applications in containers. There are even a few Kubernetes clusters which show the tell-tale signs of my usage. Containers are great. Not a week goes by however when some oddity in containers, or the tools around them, throws a wrench into the gears and causes me great frustration. This week was one of those weeks: we suddenly had problems building our Docker containers in one of our Kubernetes environments.

A number of years ago I was building out a product with a small team, like most teams I’ve worked with, an irreverent sense of humor emerged. One of my colleagues quite enjoyed using the term “bro” ironically; he certainly was the type of person who wouldn’t come within earshot of any group of people who might use the term with any level of seriousness. As the product started to take shape, we found ourselves in need of fake users in our test system. I’m not sure who created this first user, but the user’s fullName was set to “Test Bro.” Shortly thereafter another user was added: “Broam Chomsky.”

TLS certificates have the largest “complexity/importance” scores imaginable. Everything about them is error prone and seemingly over-engineered from top to bottom, yet they are one of the most important pieces of security and authentication in our software architectures. From an engineering management standpoint, I am finding myself adopting the rule of: estimates for any project involving certificates should be multiplied tenfold. If the project involves the Java Virtual Machine (JVM) and the Java Key Store (JKS), multiply by another ten I suppose. For my own future convenience, in this blog post I would like to outline how to add a root certificate to a Java Key Store in Red Hat-derived environments.

Over the course of my professional career I have witnessed the transition from free and open source software being something useful engineers do, to a multi-billion dollar industry with companies jumping into the frenzy. During this time I have also gone from an open source user, to contributor, to a board member. Helping to steward a few small projects, but mainly focusing on the Jenkins project. Along the way I have interacted with businesses in each role, forming opinions of their businesses. Getting a sense of their cultural values by watching and listening as their employees interact with the project, or their executives make public statements about Jenkins or open source software in general. By night I am open source contributor, but by day I am now what enterprise sales people refer to as the “buyer.” One with opinions formed by years of interactions with these companies whose products we evaluate.

Running untrusted CI/CD workloads in Jenkins is perhaps my favorite security discussion. Throwing Docker into the mix makes things even interesting, and in some cases less secure. Today I implemented a pattern which I have discussed with colleagues but hadn’t yet had the opportunity to try: a multi-Kubernetes cluster for Jenkins. In short, running a Jenkins master in a cluster which acts as the control pane for it and many other services, while running all of its workloads in an entirely separate Kubernetes cluster. For those who know the joy of managing Kubernetes this may seem like madness, but it does offer a number of security benefits which I would like to outline.