When you build software for embedded devices (your Wi-Fi router or home automation setup on your Raspberry Pi), there is always the question how to build these images and how to update them.

There are thousands of options in NixOS, but as users, we usually only interact with a select few of them. Despite that, a huge amount of those options does influence the final result in some way. Have you ever wondered which of them were actually relevant for your specific system?

Some reflections on trusting trust, and how deep the rabbit hole goes.

Poettering said that he does have a vision for how all of the security-related pieces of systemd are meant to fit together. He wanted to use his talk to explain ""how the individual security-related parts of systemd actually fit together and why they exist in the first place"".

[...] hard-learned patterns to write more defensive Rust code, learned throughout years of shipping Rust code to production. I’m not talking about design patterns here, but rather small idioms, which are rarely documented, but make a big difference in the overall code quality.

Achieving high-performance asynchronous Rust projects transcends mere usage of the async/await syntax; it fundamentally relies on a deep understanding of the underlying task scheduling, lock optimization, and architecture design principles.

Rex Wangs blog

This is a tutorial on how to build a digital implementation of a 2nd-order, continuously-variable filter (i.e. one where you can change the parameters runtime) that has dynamic behaviour that mimics an analogue filter.

In this deep dive post, I’ll explain how I used the interning design pattern in Rust to compress this data set by a factor of two thousand! We’ll investigate how to best structure the interner itself, how to tune our data schema to work well with it, and likewise how serialization can best leverage interning.

In a previous post, I’ve shown how to use the rayon framework in Rust to automatically parallelize a loop computation across multiple CPU cores.
In this post, I’ll first explain which profiling tools I used to chase optimizations, before diving into how I built a faster replacement of Rayon for my use case. In the next post, I’ll describe the other optimizations that made my code much faster. Spoiler alert: copying some data sped up my code!

Discrepancies in how browsers and libraries handle HTTP cookies, and the problems caused by such things.

Explore the In Our Time archive.

In a previous article, I described how to set use Nix and Niv to configure an Elixir dev environment. This setup can be simplified by using Nix flakes instead of Niv.

In this article we build off what we’ve already learned about io_uring and extend that to build an async echo server.

JTAG for Reverse Engineers