A couple of years ago, I wrote that The Builder pattern is a finite state machine!. A state machine consists of states and transitions between them. As a developer, I want to make illegal states unrepresentable, i.e., users of my API can’t create non-existent transitions. My hypothesis is that only a static typing system allows this at compile-time. Dynamic typing systems rely on runtime validation. In this blog post, I will show that it holds true, with a caveat.
How The Heck Does Shazam Work? (An Interactive Exploration)
Explore how Shazam and song identification work through interactive visualizations — spectrograms, constellation maps, hash fingerprints, and time-offset matching.
OpenData Timeseries: Prometheus-compatible metrics on object storage | OpenData
An MIT-licensed, Prometheus-compatible timeseries database built on SlateDB, bringing the operating model and cost structure of object-store-native systems to the Prometheus and Grafana ecosystem.
Proxy Server — The Control Layer Between Clients and Servers
In most modern systems, clients rarely communicate directly with backend servers. Instead, an intermediate component is introduced to manage communication, e...
A system reveals its real shape when it starts changing. Why compatibility, rollback safety, mixed versions, delayed consumers, and boundary behavior matter far more in production than they do on a whiteboard.
Why Elixir + Phoenix Are Ideal for Building Scalable, Fault-Tolerant AI Gateways – ModelRiver Blog
A deep technical breakdown of why Elixir and the Phoenix framework — with OTP supervision trees, Oban job queues, Phoenix Channels, ETS caching, and Cloak encryption — are uniquely suited for building production AI gateways and orchestration layers.
MCP co-creator David Soria Parra on What Breaks MCP at Scale
What MCP needs to work in production: context management, scalable infrastructure, and solutions to real-world scaling issues like those handled by Uber and Duolingo.
Switching higher-order streams to first-order streams
I discuss streams. It's a pretext to learn about higher-order streams, like `flatten` and to introduce a new stream: `switch`! It's very useful, and will have no secret for you.
Caching in System Design: How Systems Stay Fast as They Scale
Most systems don’t fail because of complex algorithms. They slow down because the same work is repeated too many times.A database receives thousands of identica...
How Traefik Turns Kubernetes Changes Into Live Routing Updates
Let’s explore Traefik’s internal architecture and see how it integrates with Kubernetes to monitor changes and update request routing dynamically.
A simplified view of the main components involved in the routing of requests When the server starts, it initializes a set of entry points. Each entry point is a listening endpoint through which traffic enters Traefik. In simplified terms, an entry point contains:
A listener that accepts incoming connections, A handler that processes requests and writes responses. The next important components are the configuration watcher and the providers. A provider monitors a specific configuration source, for example: Kubernetes or Docker, and feeds the configuration watcher. The configuration watcher maintains a set of callbacks and calls them when a new configuration arrives. One of the callbacks updates the current handler through the handler switcher.
The 36 Signals We Use to Predict Deployment Failures Before They Happen
Most teams use one signal to judge deploy risk: how big is this PR? It's intuitive. A 50-line change feels safer than a 2,000-line change. But it's also wrong — or at least deeply incomplete. Some of the highest-risk PRs ever merged into production...
Back on April 4, the social media site Bluesky suffered a pretty big outage. I was delighted to discover that one of their engineers, Jim Calabro, published a public writeup about it: April 2026 Ou…
An AI agent implements a feature. The code compiles. The tests pass. It still misses the point. The wrong kind of correct. Most of our software tooling is optim
From Custom to Open: Scalable Network Probing and HTTP/3 Readiness with Prometheus
At Slack, we recently unified fragmented probing into a standardized system that improves reliability, simplifies operations, and enables better measurement of network performance at scale.
Aegis: a fully open-source FPGA, from the silicon up
Aegis is a fully open-source FPGA, from the silicon up. Open-source FPGA efforts have made huge strides: projects like Project IceStorm and Apicula reverse-engineer proprietary bitstream formats, O…
For some types of embedded systems — especially those that are safety-critical — it’s considered bad form to dynamically allocate memory during operation. While you can usually ar…
Kiki bills itself as the “array programming system of unknown origin.” We thought it reminded us of APL which, all by itself, isn’t a bad thing. The announcement post is decidedly…