You probably use many tools to get through the day. Do you ever wonder what tools get other people through their days? In our Tools This Engineer Uses series, we explore the routines, systems, and tools your peers rely on to solve problems and accomplish goals. Liz Krane, Sentry’s new Developer Advocate, is no stranger to meetups. She created and continues to run Learn Teach Code, the second-largest tech meetup in Southern California with over 9,500 members.

Welcome to our Sentry for Good blog post series, where we share the stories of organizations making a difference in the world while also positively influencing the broader developer ecosystem. In this post, we highlight Sentry customer and non-profit Code for America.

June and July are traditionally slow months. The sun is out, and there’s too much work reflecting off all our monitors for any of us to get much work done. For us, it’s doubly slow as we’re putting all of our efforts towards a big launch later this year. Still, some great stuff came out.

Welcome to our series of blog posts about things Sentry does that perhaps we shouldn’t do. Don’t get us wrong — we don’t regret our decisions. We’re sharing our notes in case you also choose the path less traveled. In this post, we’re giving context to everything that needed to happen before we introduced Snuba, our new storage and query service for event data.

Welcome to our series of blog posts about all the nitty-gritty details that go into building a great debug experience at scale. Today, we’re looking at the shortcomings of source maps. Other than Python, JavaScript is the oldest platform that Sentry properly supports, which makes sense considering many Python services (including Sentry itself) have a JavaScript front-end. As the popularity of transpiling grew, the need for tools to debug transpiled code in production became obvious.

In our Sentry for Data series, we explain precisely why Sentry is the perfect tool for your data team. The present post focuses on how we optimized Airflow for deeper insights into what goes wrong when our data pipelines break. Data enables Sentry’s go-to-market teams by generating high-quality leads and tailored marketing campaigns. Of course, data is also used to steer the business by influencing how we think about Sentry pricing, future opportunities, and feature roadmap.

Errors suck. And you don’t want to spend too much of your time fixing them, dealing with them, investigating them, etc. In our Workflow blog post series, we look at how to optimize your, well, workflow, from crash to resolution. At this point in our workflow (check out the first and second posts in this series), we’ve minimized the impact of errors on the development process by creating infrastructure and culture equipped to handle unexpected issues.

You probably use many tools to get through the day. Do you ever wonder what tools get other people through their days? In our Tools This Engineer Uses series, we explore the routines, systems, and tools your peers rely on to solve problems and accomplish goals.

Errors are expensive; they steal resources allocated for other things and potentially negatively impact revenue and user sentiment. And, for teams comprised of volunteers working in their spare time, errors can take weeks to triage and resolve. So, despite what Google might tell you, Sentry for Good is not merely a solution to your pet’s pesky pheromone problems (although it is clearly also that, if PetSmart’s Google results are any indication).

Welcome to our series of blog posts about all the nitty-gritty details that go into building a great debug experience at scale. Today, we’re looking at Symbolicator, the service that processes all native crash reports and minidumps at Sentry.