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NOTE: This guide is a fork of the awesome The Open Guide to Amazon Web Services. Formatting, layout, and conduct is either directly used as is or heavily inspired from said guide.
There's not much documentation that dive deep into Datadog usage beyond the official docs. While these docs are a great starting point, they lack detail when you go off the golden path.
This guide is by and for engineers who use Datadog. It aims to be a useful, living reference that consolidates links, tips, gotchas, and best practices.
This is an early in-progress draft! It’s our first attempt at assembling this information, so is far from comprehensive still, and likely to have omissions or errors.
Please help by contributing to the guide. This guide is open to contributions, so unlike a blog, it can keep improving. Like any open source effort, we combine efforts but also review to ensure high quality.
For example, when examining four hours, data points are combined into two-minute buckets. This is called a rollup. As the time interval you’ve defined for your query increases, the granularity of your data decreases.
