Generate Metrics from Spans

문서 > APM > The Trace Pipeline > Generate Metrics from Spans

이 페이지는 아직 한국어로 제공되지 않으며 번역 작업 중입니다. 번역에 관한 질문이나 의견이 있으시면 언제든지 저희에게 연락해 주십시오.

Generate metrics from 100% of ingested spans, regardless of whether the spans are indexed by a retention filter.

Use custom metrics for specific fixed queries and comparisons, while creating retention filters to allow arbitrary querying and investigation of the retained trace and its flame graph.

Billing Note: Metrics created from ingested spans are billed as Custom Metrics.

For example, you may want to use custom metrics to visualize anomalies, create dashboards and monitors, and see trends across any parameters that are important to your business context. All generated metrics are available for 15 months as Datadog custom metrics.

Reason	Custom Metrics Generated from Spans	Retention Filters
Retention Period	15 months	15 days
Anomaly Detection	Create an Anomaly Monitor based on generated metrics.	Use Analytics to compare behavior over the past 15 days, and view complete traces to investigate root cause.
Investigation of matching traces with full context	N/A - Custom Metrics do not result in any retention of associated traces.	Keep exactly the traces relevant to your business context with retention filters.
Granularity of behavior	Create custom metrics for important endpoints or other low-cardinality groups.	Use Trace Explorer for specific endpoints, or use the ‘Group By’ option in Analytics.
Forecasting or complex mathematics	Create a Forecast monitor based on generated metrics.	N/A

To generate metrics from spans, on the APM Setup and Configuration page select the Generate Metrics tab, and click the New Metric button.

Creating a span-based metric

Define the metric query: Start by adding a query for filtering to your required dataset. The query syntax is the same as APM Search and Analytics.
Define the field you want to track: Select * to generate a count of all spans matching your query or enter an attribute (for example, @cassandra_row_count) to aggregate a numeric value and create its corresponding count, minimum, maximum, sum, and average aggregated metrics. If the attribute type is a measure, the value of the metric is the value of the span attribute.
Note: Span attributes that are not numerical values cannot be used for aggregation. To generate a metric that counts the distinct values of a span attribute (for instance count the number of user IDs hitting a specific endpoint), add this dimension to the group by selector, and use the count_nonzero function to count the number of tag values.
Specify the group-by dimension: By default, metrics generated from spans will not have any tags unless explicitly added. Any attribute or tag that exists in your spans can be used to create metric tags.
Check the Live Analytics and Search Query preview: You can view the impact of your query in real-time on the data visualization, and the matching spans considered for your query in a live preview.
Name your metric: Metric names must follow the metric naming convention. Metric names that start with trace.* are not permitted and will not be saved.

Span-based metrics are considered custom metrics and billed accordingly. Avoid grouping by unbounded or extremely high cardinality attributes like timestamps, user IDs, request IDs, or session IDs to avoid impacting your billing.

Updating existing span-based metrics

After a metric is created, only two fields can be updated:

Field	Reason
Stream filter query	Change the set of matching spans to be aggregated into metrics.
Aggregation groups	Update the tags to manage the cardinality of generated metrics.

Note: To change the metric type or name, create a new metric and delete the old one.

Generate Metrics from Spans

Creating a span-based metric

Updating existing span-based metrics

Further Reading