Today customers can only report timeslice metrics through our language agents. The feature ergonomics are lacking. These custom metrics are not dimensional, they are simple flat metric names that must be queried through the “magical” newrelic.timeslice.value metric, hindering discoverability.
Acceptance Criteria
We will add a new dimensional metric API to our language agents supporting count and summary metrics.
Design Consideration/Limitations
Custom metric data will be more discoverable as a normal dimensional metric. DM data is more usable - customers can filter and facet on autocompletable attribute names. The API and data format is closer to modern telemetry apis like OTel. Customers can build dashboards using these metrics, and if they later switch to OpenTelemetry agents, they will be able to report the same metrics into their existing dashboards. A dimensional metric API is a compelling feature that may drive agent upgrades.
Description
Today customers can only report timeslice metrics through our language agents. The feature ergonomics are lacking. These custom metrics are not dimensional, they are simple flat metric names that must be queried through the “magical”
newrelic.timeslice.value
metric, hindering discoverability.Acceptance Criteria
We will add a new dimensional metric API to our language agents supporting count and summary metrics.
Design Consideration/Limitations
Custom metric data will be more discoverable as a normal dimensional metric. DM data is more usable - customers can filter and facet on autocompletable attribute names. The API and data format is closer to modern telemetry apis like OTel. Customers can build dashboards using these metrics, and if they later switch to OpenTelemetry agents, they will be able to report the same metrics into their existing dashboards. A dimensional metric API is a compelling feature that may drive agent upgrades.
Dependencies
N/A
Additional context
Full document with details: APM Agent Dimensional metrics API - Google Docs