8 posts tagged with "architecture"

Curling IO's admin panel should feel instant when a club manager is working through a season setup. Toggle a setting, save a discount, move between product sections: the page should respond without a full reload.

Version 2 works, but every form submission reloads the page. Version 3's admin is a single Lustre server component running on the BEAM. One WebSocket connection, one long-lived Erlang process per session. Every interaction goes over that WebSocket and comes back as a DOM patch. The page never reloads, and there's no client-side JavaScript framework.

Fair warning: this post contains some opinions that are going to be controversial and may not age well. Here be dragons.

AI coding agents like Claude Code, OpenAI Codex, and Google Gemini can write code, run it, read the errors, and try again. That loop is the whole game. The faster and more informative that loop is, the more useful the agent becomes. After building Curling IO Version 3 in Gleam alongside AI coding agents, I'm convinced Gleam is the best language for this workflow. Agents don't write better Gleam - there's less training data. But Gleam's compiler lets agents self-correct without waiting for a human.

While writing the previous post about our per-test SQLite databases, I was describing how each test gets its own in-memory database, no shared connections, no shared state. And I thought: wait, if nothing is shared, can we just run them all at the same time?

Turns out we could, and our server test suite went from ~4 seconds to ~0.85 seconds for around 800 tests. Zero code changes to the tests themselves. One 25-line Erlang module.

Curling IO's tests don't need a shared test database, cleanup hooks, or transaction tricks. Each test gets its own database, so a test can pass alone or in the full suite for the same reason: nothing else can touch its data.

That falls out of one Version 3 choice: SQLite runs in-process. Each test gets a completely independent in-memory SQLite database, cloned from a template in microseconds using SQLite's backup API.

Version 3 should be cheaper to operate, easier to restore, and still fast during peak registration and live scoring. That pushed us toward a choice we didn't expect: SQLite.

We assumed PostgreSQL at first. After a decade running Postgres in production, we knew the tooling, the failure modes, and the operational playbook. Then we compared self-hosting Postgres with Litestream-backed SQLite and changed our minds.

When a curler asks for a login email, the page should respond immediately. They shouldn't wait on Postmark, and we shouldn't run a separate worker fleet just to send a message in the background.

Curling IO Version 3 runs background jobs inside the same BEAM runtime as the web app. No Redis. No separate worker. No additional deployment. The queue is durable because pending jobs live in SQLite, not memory.

English and French support has to be boring. A club in Quebec shouldn't find a half-translated registration page, and a national organization like Curling Canada shouldn't need a support ticket to catch a missing label.

Curling IO has been bilingual since Version 2, but after a decade of maintaining around 10,000 YAML translation keys, we've hit the limits of what that approach can catch: missing keys, missing translations, and unused keys that accumulate silently over time. Version 3 keeps the bilingual experience and makes more of those mistakes impossible to ship.

The next version of Curling IO should feel familiar: the same registrations, schedules, scoring, and club admin workflows, just faster and harder to break. The work is mostly under the surface, but the payoff is practical: fewer slowdowns at peak registration, better reliability during live events, and a platform we can keep improving for a long time.

This series explains what changes, what doesn't, and why we're making the bet.