Systems | Development | Analytics | API | Testing

Your Playwright test clicks Next page, waits for the item list, and times out. Now you’re digging through a trace to find out whether the page broke or an API call failed. Traditional browser-testing workflows focus on clicks, page state and UI assertions. Those checks tell you whether a user journey works, but investigating a failure also means understanding the APIs behind the page.

Jared Lynskey recently wrote a sponsored post, trying out Patch with his app, maru. This article is a follow up about using it in production on Fly.io, including any problems he encountered. Last month I moved maru’s over-the-air updates from my own expo-updates server to Codemagic Patch. Everything in that post ran against Patch’s local evaluation stack on my laptop. The section on production was a plan, with a note to myself to replace it once it had actually happened.

How much does it actually cost to self-host over-the-air (OTA) updates? Especially for an app with many millions of users. It’s a useful number to know if you’ve got a growing Expo Updates bill. This article prices an extreme case of 100 million monthly active users (MAU). Here is the monthly cost of hosting Codemagic Patch on DigitalOcean at a few sizes: You can host Patch on any Linux compatible machine, such as an EC2 on AWS or a machine on Fly.io.

Change one field in a.proto from double to string, and nothing complains. The code compiles, the deploy goes green, and a service still built from the old contract keeps answering with a double. Here’s what Go’s protobuf runtime does when a client on the new contract reads that answer: No error. risk_score comes back empty, and the nine bytes of the double are tucked away as unknown fields.

A readiness check should make a release safer. During one release validation, ours kept Kraken’s traffic replays stuck in Initializing until they timed out. The operator was asking Kubernetes for EndpointSlices. Its installed permissions did not allow that request. The code needed a real cluster, the generated permissions, and a replay trying to start before that mistake became obvious. Kraken put those pieces together during release validation.

Replay a GraphQL recording at the server that produced it, and every request comes back 200 OK. Here is one of those 200s, from a Session query whose recorded token has expired: A GraphQL server reports most failures inside a successful HTTP response, so any check that stops at the status code passes this request. And that is the second way GraphQL hides from URL-shaped tooling.