prometheus/docs/feature_flags.md

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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.

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 trace_id=<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.

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.

Auto GOMEMLIMIT

--enable-feature=auto-gomemlimit

When enabled, the GOMEMLIMIT variable is automatically set to match the Linux container memory limit. If there is no container limit, or the process is running outside of containers, the system memory total is used.

There is also an additional tuning flag, --auto-gomemlimit.ratio, which allows controlling how much of the memory is used for Prometheus. The remainder is reserved for memory outside the process. For example, kernel page cache. Page cache is important for Prometheus TSDB query performance. The default is 0.9, which means 90% of the memory limit will be used for Prometheus.

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 classic and native histograms side by side. With this feature flag disabled, Prometheus will continue to parse the classic histogram (albeit via the text format). With this flag enabled, Prometheus will still ingest those classic histograms that do not come with a corresponding native histogram. However, if a native histogram is present, Prometheus will ignore the corresponding classic histogram, with the notable exception of exemplars, which are always ingested. To keep the classic 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 classic 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

Experimental PromQL functions

--enable-feature=promql-experimental-functions

Enables PromQL functions that are considered experimental. These functions might change their name, syntax, or semantics. They might also get removed entirely.

Created Timestamps Zero Injection

--enable-feature=created-timestamp-zero-ingestion

Enables ingestion of created timestamp. Created timestamps are injected as 0 valued samples when appropriate. See PromCon talk for details.

Currently Prometheus supports created timestamps only on the traditional Prometheus Protobuf protocol (WIP for other protocols). As a result, when enabling this feature, the Prometheus protobuf scrape protocol will be prioritized (See scrape_config.scrape_protocols settings for more details).

Besides enabling this feature in Prometheus, created timestamps need to be exposed by the application being scraped.

Concurrent evaluation of independent rules

--enable-feature=concurrent-rule-eval

By default, rule groups execute concurrently, but the rules within a group execute sequentially; this is because rules can use the output of a preceding rule as its input. However, if there is no detectable relationship between rules then there is no reason to run them sequentially. When the concurrent-rule-eval feature flag is enabled, rules without any dependency on other rules within a rule group will be evaluated concurrently. This has the potential to improve rule group evaluation latency and resource utilization at the expense of adding more concurrent query load.

The number of concurrent rule evaluations can be configured with --rules.max-concurrent-rule-evals, which is set to 4 by default.

Serve old Prometheus UI

Fall back to serving the old (Prometheus 2.x) web UI instead of the new UI. The new UI that was released as part of Prometheus 3.0 is a complete rewrite and aims to be cleaner, less cluttered, and more modern under the hood. However, it is not fully feature complete and battle-tested yet, so some users may still prefer using the old UI.

--enable-feature=old-ui

Metadata WAL Records

--enable-feature=metadata-wal-records

When enabled, Prometheus will store metadata in-memory and keep track of metadata changes as WAL records on a per-series basis.

This must be used if you are also using remote write 2.0 as it will only gather metadata from the WAL.

Delay compaction start time

--enable-feature=delayed-compaction

A random offset, up to 10% of the chunk range, is added to the Head compaction start time. This assists Prometheus instances in avoiding simultaneous compactions and reduces the load on shared resources.

Only auto Head compactions and the operations directly resulting from them are subject to this delay.

In the event of multiple consecutive Head compactions being possible, only the first compaction experiences this delay.

Note that during this delay, the Head continues its usual operations, which include serving and appending series.

Despite the delay in compaction, the blocks produced are time-aligned in the same manner as they would be if the delay was not in place.

Delay name label removal for PromQL engine

--enable-feature=promql-delayed-name-removal

When enabled, Prometheus will change the way in which the __name__ label is removed from PromQL query results (for functions and expressions for which this is necessary). Specifically, it will delay the removal to the last step of the query evaluation, instead of every time an expression or function creating derived metrics is evaluated.

This allows optionally preserving the __name__ label via the label_replace and label_join functions, and helps prevent the "vector cannot contain metrics with the same labelset" error, which can happen when applying a regex-matcher to the __name__ label.

Auto Reload Config

--enable-feature=auto-reload-config

When enabled, Prometheus will automatically reload its configuration file at a specified interval. The interval is defined by the --config.auto-reload-interval flag, which defaults to 30s.

Configuration reloads are triggered by detecting changes in the checksum of the main configuration file or any referenced files, such as rule and scrape configurations. To ensure consistency and avoid issues during reloads, it's recommended to update these files atomically.