Metric exploration often begins with a simple question, but answering that question can require deep familiarity with metric names, tag structures, and query syntax. Experienced users spend time refining queries through trial and error, and newer users struggle to get started. As a result, teams face delays in troubleshooting and analysis. Valuable observability data, including metrics that are difficult to discover and query, also goes underused.
Natural Language Queries (NLQ) for Datadog metrics changes how users interact with their data. Instead of constructing queries manually, you can describe what you want in plain language and immediately generate a working query and visualization. With NLQ, teams can move from question to insight more quickly and make metrics easier to access for a broader set of users.
In this post, we’ll show how NLQ helps you:
Explore metrics by using plain EnglishAutomatically translate questions into metric queriesRefine and iterate on queries without rebuilding them
Explore metrics by using plain English
