What is the correct order of aggregation when using Datadog?

In Datadog, when aggregating data, time aggregation happens before space aggregation to ensure that the data aligns correctly over the specified time intervals before further categorizing or grouping it spatially. This order is crucial because it allows for a coherent understanding of metrics over time before introducing the complexity of space-based distinctions, such as hosts, tags, or services.

By first aggregating time, you can capture trends, spikes, or anomalies that occur during specific periods, and subsequently apply space aggregation to break down that data further. For example, if you were to analyze traffic data, you'd want to first determine the total traffic volume over defined time intervals, and only then could you start to differentiate that traffic by geographical location or application type.

This structured approach is vital for analyzing time-series data effectively, providing more meaningful insights and ensuring that the context of the data is preserved throughout the aggregation process.