Semantic Conventions for Runtime Environment Metrics

Status: Experimental

This document includes semantic conventions for runtime environment level metrics in OpenTelemetry. Also consider the general metric, system metrics and OS Process metrics semantic conventions when instrumenting runtime environments.

Metric Instruments

Runtime environments vary widely in their terminology, implementation, and relative values for a given metric. For example, Go and Python are both garbage collected languages, but comparing heap usage between the Go and CPython runtimes directly is not meaningful. For this reason, this document does not propose any standard top-level runtime metric instruments. See OTEP 108 for additional discussion.

Runtime Environment Specific Metrics - runtime.{environment}.

Metrics specific to a certain runtime environment should be prefixed with runtime.{environment}. and follow the semantic conventions outlined in general metric semantic conventions. Authors of runtime instrumentations are responsible for the choice of {environment} to avoid ambiguity when interpreting a metric’s name or values.

For example, some programming languages have multiple runtime environments that vary significantly in their implementation, like Python which has many implementations. For such languages, consider using specific {environment} prefixes to avoid ambiguity, like runtime.cpython. and runtime.pypy..

There are other dimensions even within a given runtime environment to consider, for example pthreads vs green thread implementations.