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

Last year, I came agross a Linux kernel feature called TCG_TPM2_HMAC. It claims to detect or prevent active and passive interposer attackers.
It all sounds really great. We should care about interposer adversaries. It’s great to use the TPM features that were invented to help us with these problems.

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.

This blog post describes an alternative, straightforward approach to collaborative text editing, without Conflict-free Replicated Data Types (CRDTs) or Operational Transformation (OT). By making text editing flexible and easy to DIY, I hope that the approach will let you create rich collaborative apps that are challenging to build on top of a black-box CRDT/OT library.

This post can be considered an advanced Zig tutorial. I will be covering some of the more unique
aspects of the language, but won't be explaining the easy part. If you haven't read the Zig
Language Reference, you might start there. Additionally,
we will also learn the foundational trick for implementing relational model.

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!

Macros, iterators, patterns, error handling and match make Rust almost perfect

I want to try to catalog the bits that I wish someone had just told me before working with a Postgres database. Hopefully, this makes things easier for the next person going on a journey similar to mine.

Commentary on software, robotics, and computer vision.

In this post, we are going to take a deep dive into pointer tagging, where metadata is encoded into a word-sized pointer. Doing so allows us to keep a compact representation that can be passed around in machine registers. This is very common in implementing dynamic programming languages, but can really be used anywhere that additional runtime information is needed about a pointer. We will look at a handful of different ways these pointers can be encoded and see how the compiler can optimize them for different hardware.

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.

The underlying problem we are facing here with all these examples is the same: having the same set of bits which can mean two different things and needing some way to distinguish those two meanings. Failure to do so leads to ambiguity at best and serious defects at worst. That's why you see so much emphasis in modern systems on type safety and on strict domain separation between different meanings.

We're Sequin, an open source message stream built on Postgres. We think Sequin's cool, but you don't need to adopt the project to get started with streaming in Postgres. In fact, you can turn Postgres into a basic queue/stream pretty easily. Below, we share what we've learned so you