prometheus/docs/feature_flags.md
Julien Pivotto c92fbf3fdf Add feature flag for PromQL experimental functions.
This PR adds an Experimental flag to the functions.

This can be used by https://github.com/prometheus/prometheus/pull/13059
but also xrate and other future functions.

Signed-off-by: Julien Pivotto <roidelapluie@o11y.eu>
2023-11-14 17:48:58 +01:00

9.9 KiB

title sort_rank
Feature flags 12

Feature flags

Here is a list of features that are disabled by default since they are breaking changes or are considered experimental. Their behaviour can change in future releases which will be communicated via the release changelog.

You can enable them using the --enable-feature flag with a comma separated list of features. They may be enabled by default in future versions.

Expand environment variables in external labels

--enable-feature=expand-external-labels

Replace ${var} or $var in the external_labels values according to the values of the current environment variables. References to undefined variables are replaced by the empty string. The $ character can be escaped by using $$.

Remote Write Receiver

--enable-feature=remote-write-receiver

The remote write receiver allows Prometheus to accept remote write requests from other Prometheus servers. More details can be found here.

Activating the remote write receiver via a feature flag is deprecated. Use --web.enable-remote-write-receiver instead. This feature flag will be ignored in future versions of Prometheus.

Exemplars storage

--enable-feature=exemplar-storage

OpenMetrics introduces the ability for scrape targets to add exemplars to certain metrics. Exemplars are references to data outside of the MetricSet. A common use case are IDs of program traces.

Exemplar storage is implemented as a fixed size circular buffer that stores exemplars in memory for all series. Enabling this feature will enable the storage of exemplars scraped by Prometheus. The config file block storage/exemplars can be used to control the size of circular buffer by # of exemplars. An exemplar with just a traceID=<jaeger-trace-id> uses roughly 100 bytes of memory via the in-memory exemplar storage. If the exemplar storage is enabled, we will also append the exemplars to WAL for local persistence (for WAL duration).

Memory snapshot on shutdown

--enable-feature=memory-snapshot-on-shutdown

This takes the snapshot of the chunks that are in memory along with the series information when shutting down and stores it on disk. This will reduce the startup time since the memory state can be restored with this snapshot and m-mapped chunks without the need of WAL replay.

Extra scrape metrics

--enable-feature=extra-scrape-metrics

When enabled, for each instance scrape, Prometheus stores a sample in the following additional time series:

  • scrape_timeout_seconds. The configured scrape_timeout for a target. This allows you to measure each target to find out how close they are to timing out with scrape_duration_seconds / scrape_timeout_seconds.
  • scrape_sample_limit. The configured sample_limit for a target. This allows you to measure each target to find out how close they are to reaching the limit with scrape_samples_post_metric_relabeling / scrape_sample_limit. Note that scrape_sample_limit can be zero if there is no limit configured, which means that the query above can return +Inf for targets with no limit (as we divide by zero). If you want to query only for targets that do have a sample limit use this query: scrape_samples_post_metric_relabeling / (scrape_sample_limit > 0).
  • scrape_body_size_bytes. The uncompressed size of the most recent scrape response, if successful. Scrapes failing because body_size_limit is exceeded report -1, other scrape failures report 0.

New service discovery manager

--enable-feature=new-service-discovery-manager

When enabled, Prometheus uses a new service discovery manager that does not restart unchanged discoveries upon reloading. This makes reloads faster and reduces pressure on service discoveries' sources.

Users are encouraged to test the new service discovery manager and report any issues upstream.

In future releases, this new service discovery manager will become the default and this feature flag will be ignored.

Prometheus agent

--enable-feature=agent

When enabled, Prometheus runs in agent mode. The agent mode is limited to discovery, scrape and remote write.

This is useful when you do not need to query the Prometheus data locally, but only from a central remote endpoint.

Per-step stats

--enable-feature=promql-per-step-stats

When enabled, passing stats=all in a query request returns per-step statistics. Currently this is limited to totalQueryableSamples.

When disabled in either the engine or the query, per-step statistics are not computed at all.

Auto GOMAXPROCS

--enable-feature=auto-gomaxprocs

When enabled, GOMAXPROCS variable is automatically set to match Linux container CPU quota.

No default scrape port

--enable-feature=no-default-scrape-port

When enabled, the default ports for HTTP (:80) or HTTPS (:443) will not be added to the address used to scrape a target (the value of the __address_ label), contrary to the default behavior. In addition, if a default HTTP or HTTPS port has already been added either in a static configuration or by a service discovery mechanism and the respective scheme is specified (http or https), that port will be removed.

Native Histograms

--enable-feature=native-histograms

When enabled, Prometheus will ingest native histograms (formerly also known as sparse histograms or high-res histograms). Native histograms are still highly experimental. Expect breaking changes to happen (including those rendering the TSDB unreadable).

Native histograms are currently only supported in the traditional Prometheus protobuf exposition format. This feature flag therefore also enables a new (and also experimental) protobuf parser, through which all metrics are ingested (i.e. not only native histograms). Prometheus will try to negotiate the protobuf format first. The instrumented target needs to support the protobuf format, too, and it needs to expose native histograms. The protobuf format allows to expose conventional and native histograms side by side. With this feature flag disabled, Prometheus will continue to parse the conventional histogram (albeit via the text format). With this flag enabled, Prometheus will still ingest those conventional histograms that do not come with a corresponding native histogram. However, if a native histogram is present, Prometheus will ignore the corresponding conventional histogram, with the notable exception of exemplars, which are always ingested. To keep the conventional histograms as well, enable scrape_classic_histograms in the scrape job.

Note about the format of le and quantile label values:

In certain situations, the protobuf parsing changes the number formatting of the le labels of conventional histograms and the quantile labels of summaries. Typically, this happens if the scraped target is instrumented with client_golang provided that promhttp.HandlerOpts.EnableOpenMetrics is set to false. In such a case, integer label values are represented in the text format as such, e.g. quantile="1" or le="2". However, the protobuf parsing changes the representation to float-like (following the OpenMetrics specification), so the examples above become quantile="1.0" and le="2.0" after ingestion into Prometheus, which changes the identity of the metric compared to what was ingested before via the text format.

The effect of this change is that alerts, recording rules and dashboards that directly reference label values as whole numbers such as le="1" will stop working.

Aggregation by the le and quantile labels for vectors that contain the old and new formatting will lead to unexpected results, and range vectors that span the transition between the different formatting will contain additional series. The most common use case for both is the quantile calculation via histogram_quantile, e.g. histogram_quantile(0.95, sum by (le) (rate(histogram_bucket[10m]))). The histogram_quantile function already tries to mitigate the effects to some extent, but there will be inaccuracies, in particular for shorter ranges that cover only a few samples.

Ways to deal with this change either globally or on a per metric basis:

  • Fix references to integer le, quantile label values, but otherwise do nothing and accept that some queries that span the transition time will produce inaccurate or unexpected results. This is the recommended solution, to get consistently normalized label values. Also Prometheus 3.0 is expected to enforce normalization of these label values.
  • Use metric_relabel_config to retain the old labels when scraping targets. This should only be applied to metrics that currently produce such labels.
    metric_relabel_configs:
      - source_labels:
          - quantile
        target_label: quantile
        regex: (\d+)\.0+
      - source_labels:
          - le
          - __name__
        target_label: le
        regex: (\d+)\.0+;.*_bucket

OTLP Receiver

--enable-feature=otlp-write-receiver

The OTLP receiver allows Prometheus to accept OpenTelemetry metrics writes. Prometheus is best used as a Pull based system, and staleness, up metric, and other Pull enabled features won't work when you push OTLP metrics.

Experimental PromQL functions

--enable-feature=promql-experimental-functions

Enables PromQL functions that are considered experimental and whose name or semantics could change.