Operations | Monitoring | ITSM | DevOps | Cloud

If you've ever had to debug a Flutter app after an error report that just says “Null check operator used on a null value,” you already know: context is everything. And context can be hard to come by when you’re juggling native code, Dart, async stack traces, and platform channels. With v9 of our Flutter SDK, we’re introducing some features to help you get even more visibility into what’s going wrong, with the insights to make it better. Here’s what’s new.

It’s one thing to debug your game during development, but once your game is in production, visibility into errors and failures in real gameplay is harder to achieve. And when something does go wrong, players are more likely to ragequit than submit a bug ticket.

Sentry’s auto-instrumentation, using BrowserTracing, is convenient. You can get interesting insights about your frontend application out-of-the-box, such as whether slow and failing API calls are hurting your user experience (summarized in Network Requests), or how your website stacks up against industry standards for performance (summarized in Web Vitals).

Unless you’ve been living under a rock, “MCP” is probably a term you’ve heard thrown around in the AI space. Each of the editors and LLM providers have been racing to add and enhance their MCP support. Sentry was fortunate enough to be included in Anthropics release announcements for MCP.

You push a release that touches the checkout flow. Now you’re glued to dashboards and checking Slack, hoping you didn’t introduce a regression that breaks the payment path. You can’t tell if you’ve just shipped a blocker that’s stalling every cart—or some edge case quietly making users bail.

This is a guest post from Armin Ulrich, a fullstack developer, and founder of placid.app. He also created the MadeWith* network where he shares his projects and allows other developers to share theirs. There are many things I would rather do at 9pm than tracking down a mission-critical bug, but sometimes you don’t have a choice. Let me tell you the story about a slow query that led to a cascading failure–and how it could have been worse.

App hangs are the worst kind of bug: they don’t crash, they don’t log, and unless you're actively profiling, good luck catching them in the debugger. Maybe the main thread is blocked because it’s decoding a massive image with UIImage(data:). Maybe a background task is holding a lock or waiting on a DispatchGroup that never finishes. Maybe an async flow is stuck waiting on a continuation that never resumes.

You’re looking at an error in Sentry—a failed payment in your Flask backend or an unexpected null in your Node API. You’ve got the stack trace. The request details. Even the full trace. What you don’t have: the logs your app emitted right before everything went sideways. With Sentry Logs (now in open beta), you can send application logs straight to Sentry and see them automatically connected to the errors and traces you already use.

More code is being shipped today than ever before, accelerated by AI powered code gen tools. We’re in a golden age for builders. But here’s the thing: software still breaks in production. From a recent study by Microsoft, AI models struggle to debug software. It’s because most of these code gen tools lack the one thing every good developer relies on: context. To debug anything, you need context. Having AI tools doesn't change that.

So you're building an MCP server for your project or service, to allow AI chatbots and agents to interact with it? Great! You've decided to build it using Cloudflare Workers, have written the code, shipped it, and the first users are getting onboard: you're officially running it in production. That's when problems start. I'm not here to dissuade you from shooting your shot, but let's make sure you've got your bases covered in production when something inevitably goes wrong.