The text delves into the advantages and applications of Datadog's nested metric queries, emphasizing their capability to enhance visibility and control over distributed applications by allowing users to perform complex queries on large datasets. These nested queries enable multilayer aggregation, facilitating the analysis of telemetry data across different levels of granularity, from entire infrastructures down to individual components. This flexibility supports various use cases, such as resource capacity planning, where accurate forecasting of CPU utilization over time is crucial, as well as load balancing in Kafka topics to identify and rectify imbalances. Furthermore, the use of nested queries allows for the calculation of percentiles on count, rate, and gauge metrics, aiding in resource provisioning and network monitoring, while also enabling the retention of data granularity over long-term analyses for executive reporting and resource allocation. The text concludes by encouraging readers to explore these functionalities through a 14-day free trial of Datadog.