The New Relic platform is built around four telemetry data types we believe are necessary for complete and effective system monitoring: metrics, events, logs, and traces.
This document describes the metric types collected and reported by our platform.
Metric types
The metric type determines how the data is aggregated over longer time windows. It also determines which functions you can use to query the data.
Metric types | Description | Available query functions |
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count |
Measures the number of occurrences of an event. The count should be reset to You must specify a value for The value must be a positive double. Generally, you want to take the rate of the sum:
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distribution |
Tracks the statistical distribution on a numeric attribute. This metric is re-aggregatable. For example, 1-minute data points from 60 minutes can be aggregated into a 1-hour data point, without degradation on accuracy. This type:
The distribution type uses the same algorithm as the percentile function. |
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gauge |
Represents a value that can increase or decrease with time. Examples of gauges include the temperature, CPU usage, and memory. For example, there is always a temperature, but you are periodically taking the temperature and reporting it. The value must fit into the range of a Java double. |
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summary |
Used to report pre-aggregated data, or information on aggregated discrete events. A summary includes a You must specify a value for |
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uniqueCount |
Tracks the number of unique values on a string or numeric attribute. This metric is re-aggregatable. For example, 1-minute data points from 60 minutes can be aggregated into a 1-hour data point, without degradation on accuracy. This type is generated only via the event-to-metrics service. |