Operations | Monitoring | ITSM | DevOps | Cloud

For a while, tracing in Sentry was... fine. You could open up a slow transaction, poke around, find the N+1, and feel like a hero. But if you wanted to answer more complex questions - like why your payment API was getting slower in Europe, or which CDN was silently tanking your image loads - things got harder. We didn't really build it to help with answering broad questions.

You remember that first time spinning up a Laravel app? Routes, auth, ORM, queues, all wired up without much effort. It’s one of the reasons Laravel feels productive out of the box. But when something starts slowing down, an Eloquent query drags, a job takes forever, or cache misses creep up, it’s not always obvious where to look. Laravel gives you the tools, but connecting the dots between them is usually on you.

Today I'm thrilled to announce that Emerge Tools is joining Sentry. Emerge builds best-in-class mobile tooling trusted by some of the most important brands in the world. You’ve probably seen the work of the team through their relentless efforts to improve mobile builds, efforts we’ve always admired here at Sentry. It was no surprise that when we finally met Emerge founders Josh and Noah we found that we shared a similar view of the world and hit it off instantly.

When your checkout flow breaks, customers disappear faster than most ‘cutting-edge’ JS metaframeworks. Thankfully, setting up observability for your critical paths—like a customer checkout—is painless with Sentry. Let's walk through how we instrumented, monitored, and fixed a major issue, with minimal effort.

Debugging is an ever-present pain for all developers, and that will continue despite, or maybe even thanks to, the rise of AI-written code. Tools like Sentry have been around for a while to help us engineers track and debug issues, but it’s tempting to make that process even faster and easier with some shiny new AI tools. Sure, I could just copy-paste the exception’s stack trace from Sentry into ChatGPT, but what if I really wanted something smart?

Downtime only shows up at the most inconvenient moments — like right after a 'quick deploy' or during the five minutes you dared to step away. Maybe it’s a traffic spike hammering one endpoint and taking the rest down with it. Maybe it’s that 'small change' you confidently shipped straight to prod. Either way, users can’t reach your site, and now you’re debugging live in production.

When something slows down in prod, it’s too easy to fall into old habits. Throw in a few more logs, ship some metrics, try to reproduce the issue locally, and maybe reach for perf or py-spy if you’re feeling ambitious. Traces can help, but they usually stop just short of explaining why things are slow, especially when it’s deep in the stack.

Blockchain, IoT, Big Data. If you’ve been around in tech for a while, you know that these kinds of buzzwords come and go: they make a splash going in and fizzle out over time. Seeing many of them come and go over the years has made me skeptical. What are they trying to sell us this time? Some might call it getting grumpy; others might call it becoming an enterprise architect. So you’ll have to forgive me for thinking AI agents seemed like just another buzzword.

More people will build and ship applications in the next year than in the 10 years previous. As more applications make their way into “launched”, by developers of all experience levels, making sense of “what broke”, “why”, and clear paths to fixing it is going to become more and more important. This is why it made sense for Sentry to be one of the first platforms launching Vercel’s new Observability Marketplace category.

PHP apps can be deceptively simple — until something starts slowing down. Maybe it’s a page load that takes a few seconds too long, or maybe your server costs are creeping up without a clear reason. That’s where performance monitoring comes in. In this guide, we’ll walk through how to monitor and improve the performance of a PHP application. You’ll learn how to use profiling and tracing to identify bottlenecks in your code, and how to optimize your app.