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When using the Metrics Explorer, monitors, or dashboards to query metrics data, you can filter the data to narrow the scope of the timeseries returned. Any metric can be filtered by tag(s) using the from field to the right of the metric.
You can also perform advanced filtering with Boolean or Wildcard tag value filters. For queries outside of metrics data such as logs, traces, Network Monitoring, Real User Monitoring, Synthetics, or Security, see the Log Search Syntax documentation for configuration.
Boolean filtered queries
The following syntax is supported for Boolean filtered metric queries:
!
,
NOT
, not
AND
, and
OR
, or
IN
, in
NOT IN
, not in
When including or excluding multiple tags:
- Include uses
AND
logic - Exclude uses
OR
logic
For more information on tags, see the Getting Started With Using Tags guide.
Note: Symbolic boolean syntax (!
, ,
) cannot be used with functional syntax operators (NOT
, AND
, OR
, IN
, NOT IN
). The following query is considered invalid:
avg:mymetric{env:prod AND !region:us-east}
Boolean filtered query examples
To use the examples below, click the code icon </>
to see the query editor in the UI, and then copy and paste the query example into the query editor.
avg:system.cpu.user{env:staging AND (availability-zone:us-east-1a OR availability-zone:us-east-1c)} by {availability-zone}
avg:system.cpu.user{env:shop.ist AND availability-zone IN (us-east-1a, us-east-1b, us-east4-b)} by {availability-zone}
avg:system.cpu.user{env:prod AND location NOT IN (atlanta,seattle,las-vegas)}
Wildcard filtered queries
Prefix, suffix, and substring wildcard tag filtering are supported:
pod_name: web-*
cluster:*-trace
node:*-prod-*
Wildcard filtered query examples
avg:system.disk.in_use{!device:/dev/loop*} by {device}
sum:kubernetes.pods.running{service:*-canary} by {service}
avg:system.disk.utilized{region:*east*} by {region}
Exclusion functions
Add an exclusion function to your query to:
- Exclude N/A values.
- Apply a minimum or maximum value to metrics that meet the threshold.
- Exclude values that are above or below threshold values.
Functions do not delete datapoints from Datadog, but they do remove datapoints from your visualizations.
Further Reading
Más enlaces, artículos y documentación útiles: