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 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 configuredscrape_timeout
for a target. This allows you to measure each target to find out how close they are to timing out withscrape_duration_seconds / scrape_timeout_seconds
. -
scrape_sample_limit
. The configuredsample_limit
for a target. This allows you to measure each target to find out how close they are to reaching the limit withscrape_samples_post_metric_relabeling / scrape_sample_limit
. Note thatscrape_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 becausebody_size_limit
is exceeded report-1
, other scrape failures report0
.
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.
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.
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 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
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.
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.