Operations | Monitoring | ITSM | DevOps | Cloud

A disappearing “Submit” button. A modal stuck half-offscreen. It's not a crash or a performance regression. Just broken UX. Frustrating enough to make users rage-quit or leave a 1-star review. Error and performance monitoring catch the technical stuff: crashes, bottlenecks, slow APIs. But they won’t tell you when a layout breaks, or a UI flow subtly unravels after a redesign.

You did it. You added the latest AI agent into your product. Shipped it. Went to sleep. Woke up to find it returning a blank string, taking five seconds longer than yesterday, or confidently outputting lies in perfect JSON. Naturally, you check your logs. You see a prompt. You see a response. And you see nothing helpful. Surprise. Prompt in and response out is not observability. It is vibes.

Writing code is easier than ever. We want to make deleting code just as easy – introducing Reaper for iOS and Android. Reaper was an Emerge Tools product that helped companies like Duolingo delete 1% of their iOS codebase. And just like with Emerge Tools’ Launch Booster, we’re making Reaper open-source for anyone to use. In this post, we’ll explain what Reaper is, why you should care about dead code, and how Reaper works on both platforms.

Monitoring production systems often feels like searching for a moving needle in a constantly shifting haystack. At Sentry, our goal was to empower customers to move beyond traditional threshold and percentage-based alerting. We aimed to help them detect subtle and complex anomalies in their systems in near real-time. This post will detail how our AI/ML team developed a time series anomaly detection system using Matrix Profile and Meta’s Prophet.

AI is changing how we build software — but debugging code still comes down to having context. One minute the model’s performance is cruising. The next, you’re hit with a KeyError from a tool you forgot existed, triggered by a model that silently timed out, and a retrieval call that returns... nothing, or 11 “Let me try this a different way" messages before failure. You’re stitching together LLM calls, agents, vector stores, and custom logic. Then hoping it holds up in prod.

You deploy a fix late Friday and spend the weekend refreshing dashboards, hoping nothing breaks. You shouldn’t have to babysit a dashboard to know when something’s wrong. With the latest updates to Insights, you can now create alerts directly from any chart. Whether it’s a spike in 4xx errors after a deploy, a jump in P95 latency for an API endpoint, or a drop in throughput for a background job, you can set up alerts with just two clicks.

If your legal department is anything like ours, you’re being inundated with requests from the business to use more and more AI tools. Whether it's developers wanting to use coding agents like Cursor, to security implementing AI-driven investigations, to sales and marketing leveraging AI for call insights and competitive research, we've seen a shift in what teams are trying and buying.

You write code. Open a PR. CI runs. PR merges. Prod’s on fire by 5pm. Maybe you skipped writing some tests. (It's tedious, sometimes unclear, and easy to ignore when you're racing to ship—until something breaks and you realize a test could’ve saved your Friday night.) Maybe the PR review was more of a drive-by from a teammate who barely had time to skim the diff. But reviews and tests matter.

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.