AWS DevOps Engineer Professional Practice Test 2026 - Free DevOps Practice Questions and Certification Study Guide

Configuring CloudWatch to ignore missing data points is a practical approach when dealing with data sources that provide metrics at longer intervals. By selecting this option, you instruct CloudWatch to treat the absence of data points as a non-significant event rather than a definitive signal that would trigger an alarm state like INSUFFICIENT_DATA. This is especially important for metrics that may only report at longer intervals since the lack of information over shorter periods can lead to misleading alarm conditions.

In scenarios where data might not be sent consistently, ignoring missing data points helps maintain the integrity of your monitoring system, ensuring that you are not alerted unnecessarily due to the temporal nature of the data source.

While adjusting the evaluation period or changing the threshold might have some effect, they do not resolve the fundamental issue of missing data impacting alarm states. Higher thresholds may not be applicable for every scenario, and enabling verification of data points focuses more on validating the integrity of the data rather than addressing the delay or gaps in data transmission. As a result, ignoring missing data points stands out as the most effective method when managing alarms for sources with infrequent updates.