Operations | Monitoring | ITSM | DevOps | Cloud

November 2022

How We Made JavaScript Stack Traces Awesome

Sentry helps every developer diagnose, fix, and optimize the performance of their code, and we need to deliver high quality stack traces in order to do so. You might have noticed a significant improvement in Sentry JavaScript stack traces recently. In this blog post, we want to explain why source maps are insufficient for solving this problem, the challenges we faced, and how we eventually pulled it off by parsing JavaScript.

Bringing Codecov into the Sentry Family: Where Code Coverage Meets Application Monitoring

Today Codecov is joining the Sentry family. Codecov began as a code coverage reporting tool in 2014 and has since emerged as a market leader in the test analytics space. Codecov makes coverage actionable for over two dozen test frameworks, and has helped over a million software developers improve their approach to testing, coverage, and code reliability. You might be asking, what do test analytics have to do with application monitoring?

Measuring application performance in Swift using transactions

So you’re building a mobile app that’s performing big data requests; or crunching big data. But now you’re asking yourself: With Sentry’s Custom Instrumentation you can keep an eye on those big data-handling functions. Let’s see how you can implement them in your Storyboard and SwiftUI projects.

Solve code-level bottlenecks with Profiling for Node.js

Profiling is an important tool in every developer’s toolkit because it provides a granular view into the execution of your program from your production environment. This is an important concept, as performance bottlenecks can often be very hard or even impossible to reproduce locally due to external constraints or loads only seen in a production environment.

Solve code-level bottlenecks with Profiling for Python

Profiling is an important tool in every developer’s toolkit because it provides a granular view into the execution of your program from your production environment. This is an important concept, as performance bottlenecks can often be very hard or even impossible to reproduce locally due to external constraints or loads only seen in a production environment. Python is one of the most popular programming languages available, and it is one of the core technologies we use at Sentry.

How we run our Python tests in hundreds of environments really fast

Not in a reading mood? You also can watch the talk I gave at DjangoCon 2022. One of Sentries core company values is “for every developer”. We want to support every developer out there with our tools. But not every developer uses the newest or widely adopted tech stack, so we also try to support older versions of libraries and frameworks.

How Sentry uncovered an N+1 issue in djangoproject.com

Sentry recently launched Performance Issues, a feature to help developers discover and fix common performance problems in their projects. We tested this project internally and with alpha users, so when we finally turned it on for all Sentry users, we were delighted (and dismayed) to hear from Carlton Gibson, current Django fellow and great human, that Sentry had.

A New Era of Sentry

Today we are releasing Dynamic Sampling, available to all new customers, and opt-in for existing customers. This goes beyond a new feature however and is an overhaul to the way we package Sentry’s Performance Monitoring product. We are saying goodbye to the days of static, magic number sampling configured within the SDK and moving to a world of flexibility.

Set up Performance Monitoring With Tonal

We’re drowning in dashboards with no clues or clear steps to help us take action on our app’s performance. But as our eyes glaze over, we’re missing bugs and slowdowns sometimes weeks too late. Join our interactive co-working session with Max Lapides, Senior Manager of Mobile Software Engineering at Tonal, and learn how to customize performance monitoring in real time with our latest product updates.