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According to the Splunk Observability Cloud documentation1, lag is a rollup function that returns the difference between the most recent and the previous data point values seen in the metric time series reporting interval.This can be used to measure the time delta between a data point being sent and a data point being received, as long as the data points have timestamps that reflect their send and receive times. For example, if a data point is sent at 10:00:00 and received at 10:00:05, the lag value for that data point is 5 seconds.

The correct answer is D. Metric type.A metric type is an optional, but highly recommended field that specifies the kind of measurement that a datapoint represents. For example, a metric type can be gauge, counter, cumulative counter, or histogram. A metric type helps Splunk Observability Cloud to interpret and display the data correctly1To learn more about how to send metrics to Splunk Observability Cloud, you can refer to this documentation2.1: https://docs.splunk.com/Observability/gdi/metrics/metrics.html#Metric-types2: https://docs.splunk.com/Observability/gdi/metrics/metrics.html

According to the Splunk Observability Cloud documentation1, the maximum function is an analytic function that returns the highest value of a metric or a dimension over a specified time interval. The maximum function can be used as a transformation or an aggregation. A transformation applies the function to each metric time series (MTS) individually, while an aggregation applies the function to all MTS and returns a single value. For example, to discover the peak page visits for a site over the last day, you can use the following SignalFlow code:maximum(24h, counters(''page.visits''))This will return the highest value of the page.visits counter metric for each MTS over the last 24 hours. You can then use a chart to visualize the results and identify the peak page visits for each MTS.