Which of the following statements is NOT true about Datadog's granularity and retention of metrics?

The statement regarding Datadog rolling up data into one-hour averages that can be retained for longer durations beyond the default of 15 months is accurate. However, it is crucial to note the specific details about granularity and retention periods.

Datadog typically retains metrics data at high granularity for a set duration. While data can be aggregated into one-hour averages, this pertains to a different aspect of managing data. Higher granularity allows for more detailed insights into performance over shorter intervals, which is essential for real-time monitoring and troubleshooting.

The retention policy specifies that, after the short-term high granularity period (usually 15 seconds), the data is rolled up to a less granular format that is retained for extended periods, but this does not extend beyond the stated default without specific contractual arrangements. Thus, it is not accurate that one-hour averages can simply be retained indefinitely; there are limits to retention that apply.

Therefore, the correct understanding is that while rolling up data into longer-term averages is a common practice, it does not imply that all data can be retained beyond standard retention policies without additional considerations or agreements. This nuance makes the statement regarding one-hour averages misleading in the context of how Datadog manages metric data retention and granularity.