Datadog Automatic APM instrumentation is generally sufficient for most customers, but as soon as it’s not there can be a pretty significant engineering burden. An engineer will have to go into the codebase, find where the changes need to be made, refer to documentation to ensure they are using the correct pattern, and so on.

Datadog dashboards don’t fail from missing metrics—they fail from rushed design and legacy thinking. Using the Datadog MCP Server + AI assistants, we validate metrics and context before writing JSON, then build dashboards faster. Real cloud cost example from our environment.

A clean recap of December’s NoBS Datadog Office Hour, covering real Datadog production issues, troubleshooting questions, and the answers shared live by our engineers.

A practical, engineer-first guide to migrating to Datadog — including tagging, Agents, dashboards, logs, APM, synthetics, SLOs, validation, and cost control.

A wise man named Ice Cube once said “chickity-check yourself, before you wreck yourself.” If you’re not a fan of wrecking yourself, we’ve got something for you—the Reality Check, a brutally honest report of what’s going on in your Datadog and how to fix it…

Datadog Synthetic Monitoring is a powerful way to test uptime, API performance, and user flows — but without best practices, costs and SLOs can spiral fast. Here are practical tips on how to set up Datadog Synthetic tests the right way.

We got a flood of real-world questions during our App Builder webinar—way more than we could tackle live. This post dives into the details, clears up confusion, and gives straight answers to the things you actually wanted to know.

I’ve spent a good amount of time recently working in the App Builder, understanding its capabilities, and how some of it works. While there are a lot of examples in the form of blueprints that are provided by Datadog, figuring out how some more of the functionality really works has been tricky, since the documentation is still a work in progress. So, I did some of the hard parts, so you don’t have to!

Messy tagging slows down troubleshooting, clutters dashboards, and makes alerts unreliable. In Part 2, we’re tackling the biggest mistakes—over-tagging, inconsistent naming, and skipping Unified Service Tagging—plus how to fix them.

We received a lot of great questions in our webinar. Hopefully, this post helps answer those questions and provide even more detail than we could cover.

Woah now, hold on a second - get your mouse away from that “New Dashboard” button, we’ve got a few things to talk about first. Clearly you’re well on your way to using Datadog.