Operations | Monitoring | ITSM | DevOps | Cloud

What do the Snapchat, Airbnb, and Spotify iOS apps have in common? They all use order files to speed up their iOS app launch times. Order files re-order your binary to improve how symbols are loaded into memory. No code changes are necessary, but generating an optimized order file can be cumbersome, so it’s mostly done by larger teams or teams willing to pay for a service like Emerge Tools’ Launch Booster. It just so happens that Emerge Tools is now part of Sentry.

Tired of trying to guess if that half-baked LLM suggestion is really going to fix the issue with your code? Meet Seer—our new AI agent that taps into all the issue context from Sentry and your codebase to not just guess, but root cause gnarly issues and propose merge-ready fixes specific to your application. Code gen tools are great fun—and useful. But even a recent Microsoft study confirmed what you already know: AI struggles with debugging.

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.