Operations | Monitoring | ITSM | DevOps | Cloud

Optimizing SQL queries is always fun—except when it isn’t. If you’re a MySQL veteran and have read the title, you already know where this is heading 😉. In that case, allow me to regale the uninitiated reader. This is the story of an (apparently) smart optimization to a SQL query that backfired spectacularly—and how we finally fixed it. It started off with a customer noticing that a SQL query was running slowly in their environment.

Performance monitoring is great because it lets you see whether your application is fast or slow, and which parts need speeding up. For Node developers, those “parts” are most often endpoints handling incoming requests. Since the introduction of our performance monitoring offering in July 2020, Node devs have been able to use the Sentry SDK, @sentry/node, to measure the total time it takes to process each request, but we made some significant improvements since then.

Traditional database and application monitoring used to mean talking about a single server, in a single data center, in a single location. Many monitoring tools were—and still are—built around this single data center, single node idea. And while we’ve progressed to cloud-native applications, our tools haven’t quite caught on.

For decades, Microsoft SQL has been a leading relational database solution within Windows-based environments. The extension of Microsoft SQL support to Linux servers in 2017 made the platform even more popular. There’s a good chance that, no matter which types of infrastructure or servers you manage, there are Microsoft SQL databases residing somewhere on them. That’s why it’s critical to understand the fundamentals of Microsoft SQL monitoring.