Sentry is an open source company, and it’s important to us to financially support our non-commercial colleagues in the community as we continue to enjoy commercial success. We’ve given money forever, but last year we really got organized and gave $154,999.89 to 108 recipients. Two points make a line, and this year we are back with a continuation of the industry-leading open source funding program we put in place last year.

In the first three parts of this series around improving performance in your Django applications, we focused on database, code optimization, and frontend optimization. In part 4, we will focus on ways to improve the speed of the Django applications.

Sentry Alerts ping you on Slack, Microsoft Teams, or Pager Duty when something goes needs your attention. However, too many alerts can turn your notification channel into an endless noise feed. I spoke with dozens of Sentry customers in the past 6 months, and something I heard over and over again was “Sentry can get noisy at times” and “There are days I can’t keep up with Sentry notifications because we get so many of them”. Does this sound familiar?

Profilers measure the performance of a program at runtime by adding instrumentation to collect information about the frequency and duration of function calls. They are crucial tools for understanding the real-world performance characteristics of code and are often the first step in optimizing a program. Apple and Google have first party profiling tools, but they are only usable for local debugging during development.

Forethought is a leading AI company providing customer service solutions that transform the customer experience. As a high-growth startup with a fast-expanding engineering org., teams had to deal with compounding complexity, leading to challenges measuring the impact and health of their services. Forethought’s core engineering team maintains common services between other internal teams, infrastructure, data, and tools and, as they added more engineers, the original team split into five.

The following guest post addresses how to improve your services’ performance with Sentry and other application profilers for Unity. Learn more about Sentry’s Profiling product or try it out now if you’re already a Sentry user. We’re making intentional investments in performance monitoring to give relevant context to help you solve what’s urgent faster.

Exceptions are the outcomes you do not usually expect in your application. But as a developer, expecting the unexpected is essential to capture exceptions and handle them appropriately. Exception handling is not only applicable to web development projects but also to Unity applications. This article brings everything you need to know as a beginner to Unity exception handling, including methods to handle exceptions, when to use them, and how to manage exceptions easier using distributed logging.

The following guest post addresses how to improve your services’s performance with Sentry and other application profilers for Python. Check out this post to learn more about application profiling and Sentry’s upcoming mobile application profiling offering. We’re making intentional investments in performance monitoring to make sure we give you all the context to help you solve what’s urgent faster.

The monitoring, tooling, and observability space is crowded. It’s hard to keep track of what most tools in this category originally set out to do— but if we had to guess… they were probably built to support monolithic architectures with complex systems, to give Ops and IT a way to minimize the impact of an outage.

Thanks to the power of open source tooling and cloud services, shipping an application to production has never been that easy, In this blog post, we are going to go from bootstrapping a Next.js application to deploying it on Vercel. We will use Github Action to handle the Continuous Integration and Sentry to monitor the application once it is deployed to be warned of any problems as soon as it arrives.