Query the Metric data type

When metrics are reported to New Relic via the Metric API (including from integrations that use that API), the data is reported as the Metric data type and is available for querying.

This doc explains:

How to view and query your metrics
Example metric queries
How to query multiple metrics with wildcards
How to explore metric data

Query APM metric timeslice data

APM reports a specific type of data that we call metric timeslice data. For how to query that, see Query metric timeslice data.

Important

You cannot query timeslice metrics in conjunction with dimensional metrics or event data. Any query involving newrelic.timeslice.value or an apm.* metric can only return APM metrics.

For information about other types of metrics, see Metric data types.

View and query your metrics

You can use NRQL to query your metric data in the query builder or using our NerdGraph API.

To query a metric, you can use the following query format:

FROM Metric SELECT function(metric_name) WHERE attribute=value FACET attribute TIMESERIES

For information about what functions are supported for what metric data types, see Metric data structure.

Add the names of the metrics you want to chart with the appropriate value functions in the SELECT clause. The WHERE and FACET clauses can be used with attribute values. Remember to include the keyword TIMESERIES if you want to chart the data.

This example demonstrates how you could chart the CPU usage in seconds for cluster foo . This query breaks down CPU usage by container, given a count metric named container_cpu_usage_seconds_total with the attributes containerName and clusterName:

FROM Metric SELECT sum(container_cpu_usage_seconds_total) 
WHERE clusterName = 'foo' 
FACET containerName 
TIMESERIES

If you want the CPU usage per minute (the rate of change), then you can add the rate function to the query above.

FROM Metric SELECT rate(sum(container_cpu_usage_seconds_total), 1 minute) 
WHERE clusterName = 'foo' 
FACET containerName 
TIMESERIES

View example metric queries

The previous examples demonstrate basic forms of metric queries, but NRQL can also be used to chart, explore, and analyze metric data.

Chart multiple metrics using a single query by providing a comma-separated list of metrics in the SELECT clause. For example, to chart the memory usage for a container along with the memory limit metric, use the following query:

FROM Metric 
SELECT latest(container_memory_usage_bytes), latest(container_spec_memory_limit_bytes) 
WHERE containerName = 'inventory' 
TIMESERIES

You can also do this using wildcards, as explained below.

Perform math operations on one or more metrics to compute a new, derived metric. To monitor available memory, you can calculate the percentage of available memory from the two metrics used in the previous example:

FROM Metric 
SELECT (latest(container_spec_memory_limit_bytes) - latest(container_memory_usage_bytes)) 
  / latest(container_spec_memory_limit_bytes) 
  * 100 
  AS '% Memory Available' 
WHERE containerName = 'inventory' 
TIMESERIES

You can also do this using wildcards, as explained below.

In addition to using a WHERE clause which applies to everything in SELECT, NRQL provides another aggregation function called filter which can be used to select a specific time series to be charted or operated on.

The following example charts a memory usage metric labeled "Total (k8s)" which is computed by adding together the memory usage of two specific containers within a pod:

FROM Metric 
SELECT filter(
  latest(container_memory_usage_bytes), 
  WHERE containerName = 'discovery') 
+ filter(
  latest(container_memory_usage_bytes), 
  WHERE containerName = 'my-proxy') 
AS 'Total (k8s)' 
WHERE clusterName = 'my-cluster' AND podName LIKE 'my-pilot-%' 
TIMESERIES

When querying metric data using FROM Metric, New Relic automatically selects the specific aggregate to use in the query, depending on the length of the query window and any bucket size specified as an argument to the TIMESERIES keyword. This ensures efficient querying and chart resolution. If you want to override this behavior to view or operate on the raw metric data points, use the optional RAW keyword in your query.

When querying these raw metric data points, there is a query time window limit of 48 hours. Any query attempting to access more than 48 hours of raw metric data will result in a query error.

This example shows how to list the last 20 data points received for a particular metric:

FROM Metric SELECT * WHERE metricName = 'container_fs_usage_bytes' LIMIT 20 RAW

Query multiple metrics with wildcards

Wildcards are represented in NRQL by the % character. If you want to query multiple metrics that use a standard naming convention, you can use the wildcard feature to return results for all of them without having to specify each metric name individually.

Wildcards can help you:

Aggregate metrics together and chart the results
FACET results by metric name in a chart
Find and chart all metrics matching a given naming convention

Wildcards are particularly helpful if you later add new metrics matching an existing naming convention. By using % instead of writing out each metric name in your query, you won't have to rewrite the query when you add new metrics.

Let's say you have multiple algorithms that perform a similar task. You can define the following metrics, which show the duration of the different algorithms:

myNeatProcess.algorithm1.duration
myNeatProcess.algorithm2.duration
myNeatProcess.algorithm3.duration

If used in a query, myNeatProcess.%.duration will return results for all three of the algorithms above. If you later create new algorithms named algorithm4, algorithm5, and algorithm6, the same query will return results for all six algorithms.

You can chart multiple metrics using a single query by using wildcards (%) in the SELECT clause. For example, to query all the algorithms in the example above and plot a line on the chart for each algorithm's average duration, use the following query:

FROM Metric 
SELECT average(myNeatProcess.%.duration) 
FACET metricName TIMESERIES

You can also use wildcards to perform math operations on multiple metrics and compute a new metric. You can calculate the mean duration for all algorithms listed in the example above:

FROM Metric 
SELECT average(myNeatProcess.%.duration) 
TIMESERIES

You can calculate what percentage of overall runtime a single algorithm takes:

FROM Metric 
SELECT myNeatProcess.algorithm1.duration / sum(myNeatProcess.%.duration) 
TIMESERIES

Return results for individual fields using `getField()`

There are multiple types of Metric data (for example, gauge and count) and each type has several associated fields. For details on the types of fields available, see getField().

You can use getField() to extract those fields. For example, if you want to use a single value within a metric to do a comparison in a WHERE clause, you can use getField(metricName, field) or the shorthand syntax metricName[field].

The average value of a metric is computed as total over count, so the following query returns metric data where the result of the average() value function is greater than 2.

FROM Metric 
SELECT average(apm.service.transaction.duration) 
WHERE appName = 'MyApp' 
AND getField(apm.service.transaction.duration, total) / getField(apm.service.transaction.duration, count) > 2

Or, you can use the shorthand:

FROM Metric 
SELECT average(apm.service.transaction.duration) 
WHERE appName = 'MyApp' 
AND apm.service.transaction.duration[total] / apm.service.transaction.duration[count] > 2

This example query returns a list of gauge metrics:

FROM Metric 
SELECT uniques(metricName) 
WHERE getField(%, type) = 'gauge'

Or, you can use the shorthand:

FROM Metric 
SELECT uniques(metricName) 
WHERE %[type] = 'gauge'

Note the use of the % wildcard to target any matching metricName.

Explore metric data

The NRQL keyset and uniques functions can be used together with the metricName attribute (available on all metrics) to perform tasks like listing all the available metrics in your account or discovering the attributes available on a particular metric.

Query APM metric timeslice data

Important

View and query your metrics

View example metric queries

Chart multiple metrics

Perform mathematical operations on metric data

Use filters to select specific time series

View the raw metric data points

Query multiple metrics with wildcards

Chart multiple metrics with wildcards

Perform mathematical operations on metric data with wildcards

Return results for individual fields using `getField()`

List all metric names for a particular host

List of gauge metrics

Explore metric data

List all metric names in an account

List all metric names for a particular host

Show the attribute keys for a specific metric

Query the Metric data type

Query APM metric timeslice data .css-21sua1{background:none;border:none;width:0;padding:0;}

Important

View and query your metrics

View example metric queries

Perform mathematical operations on metric data

Use filters to select specific time series

View the raw metric data points

Query multiple metrics with wildcards

Chart multiple metrics with wildcards

Perform mathematical operations on metric data with wildcards

Return results for individual fields using getField()

List all metric names for a particular host

List of gauge metrics

Explore metric data

List all metric names in an account

List all metric names for a particular host

Show the attribute keys for a specific metric

Query APM metric timeslice data

Return results for individual fields using `getField()`