Robot Framework VS Sentry

Fixing a bug is incomplete without preventing its recurrence. Root cause analysis (RCA), coupled with regression testing and documentation, ensures long-term reliability. Antony Marceles, Founder of Pumex Computing, emphasizes, “Fixing a bug is only part of the solution, preventing it from happening again is the real goal.” Marceles’ team uses regression tests via Robot Framework and code reviews with Gerrit to maintain quality, documenting fixes in Confluence to share insights. A 2023 Forrester report found that teams with strong RCA practices reduce recurring bugs by 35%.

Documentation is your best friend. It provides comprehensive guides, examples, and API references to help you navigate the library effectively. Here you can access it, as well as the Robot Framework documentation.

The Robot Framework is an acceptance testing tool that is easy to write and manage due to its key-driven approach. Let us learn more about the Robot Framework to enable acceptance testing.

Well, I work with software quality and despite not having a strong foundation in automation, one fine day I decided to make a change. I have been working with Robot Framework for a few months - and that's when I got a taste of the power of python. Some time later, I dabbled a little with Cypress and Playwright, always using javascript.

Robot Framework

I've used Lua/Busted in a data-heavy environment (telemetry from hospital ventilators). I've also used robot: https://robotframework.org/

I can't say whether any of these will work, but maybe one of: PyAutoGui pytest-qt Robot Framework + plugins

Sentry – error tracking with real context

Error monitoring is configured (Sentry, Rollbar, or similar).

Tembo integrates with observability tools like Sentry, Datadog, and New Relic to detect performance regressions, query slowdowns, and recurring exceptions. When it finds issues, it analyzes recent commits, traces the root cause, and opens pull requests with fixes or optimizations — often before anyone notices the problem.

This way, the primitive allows you to choose the layer in your application for throwing and catching. One of our key ideas was to define integration with Sentry logging "at the top":

Sentry error tracking that saves you from rage-pushing to prod

Sentry could tell me where my code broke. But if I was waiting for #query to appear and it never did, I didn’t just want a stack trace—I wanted to see what was there instead.

I don't believe it's a fork, but https://gitlab.com/glitchtip/glitchtip-backend is MIT and aims to be the actual Open Source replacement for Sentry

Given that it's almost been 2 years since the FSL change[1], I would imagine it's possible to set up a rolling mirror into https://gitlab.com/glitchtip/sentry-open-source/sentry that serves as an easier "what is actually open right now?" browser.

I just realized while typing that out: a snapshot of the source code actually doesn't help anyone know if a particular commit is Apache 2 since the change is dependent upon an accounting record on GitHub

That was the advantage of the BuSL 1.1 scheme, that those cut-over dates were embedded in the file https://github.com/getsentry/sentry/blob/22.7.0/LICENSE#L19 and https://github.com/getsentry/sentry/blob/22.8.0/LICENSE#L19 is open in 10 days

1: https://github.com/getsentry/sentry/commit/d4d89e2fa93ad99f1... is Nov 17, 2023 -05:00

I tried a few open source bug trackers, but from what I found they look either very old (https://www.bugzilla.org/) or super heavy (https://sentry.io). Bugsink provides a nice middle ground so I encourage you to give it a try.

For production JS (both browser and server), consider an error-tracking tool (like Sentry). These capture exceptions with stack traces from real users, so you can debug live issues remotely.

Use distributed tracing: Tools like Sentry, Datadog, and New Relic are serverless-friendly.