Experimental PromQL functions and operators

Prometheus makes experimental functions and operators available behind a feature flag. The Prometheus project might change the name, syntax, or semantics of experimental functions or remove them entirely.

Observability Platform accepts a subset of PromQL experimental functions determined to be relatively stable, and which provide significant value while also being at a low risk of being removed by the Prometheus project.

When the upstream Prometheus project makes breaking changes, Observability Platform will either preserve backward compatibility if possible or notify users and provide a deprecation timeline.

The following experimental functions are available in Observability Platform:

double_exponential_smoothing()

Use the double_exponential_smoothing() experimental function to smooth a time series based on the importance you assign to older data and possible trends. See the PromQL documentation (opens in a new tab).

holt_winters() (deprecated)

As of Prometheus 3.0, this function is named double_exponential_smoothing(). While Observability Platform aliases holt_winters() to provide backward compatibility, you should replace it with the new name to avoid issues when Observability Platform removes the holt_winters() alias.

histogram_*() (native histogram functions)

All Prometheus native histogram functions remain behind a feature flag in the Prometheus project. Observability Platform has made the native histogram functions generally available for users to query OpenTelemetry exponential histograms and Prometheus native histograms.

For details on using these functions in Observability Platform and examples, as well as other supported histogram types, see Querying histograms.