Signed-off-by: Artem Navoiev <tenmozes@gmail.com>
(cherry picked from commit 507879380b
)
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Relabeling cookbook
VictoriaMetrics and vmagent support Prometheus-compatible relabeling with additional enhancements.
The relabeling is mostly used for the following tasks:
- Dropping unneeded scrape targets during service discovery. See how to drop discovered targets.
- Adding or updating static labels at scrape targets. See how to add labels to scrape targets.
- Copying target labels from another labels. See how to copy labels in scrape targets.
- Modifying scrape urls for discovered targets. See how to modify scrape urls in targets.
- Modifying
instance
andjob
labels. See how to modify instance and job. - Extracting label parts into another labels. See how to extract label parts.
- Removing prefixes from target label names. See how to remove prefixes from target label names.
- Removing some labels from discovered targets. See how to remove labels from targets.
- Dropping some metrics during scape. See how to drop metrics during scrape.
- Removing some labels from scraped metrics. See how to remove labels from metrics.
- Removing some labels from metrics matching some series selector. See how to remove labels from metrics subset.
See also relabeling docs at vmagent.
How to remove labels from metrics subset
Sometimes it may be needed to remove labels from a subset of scraped metrics, while leaving these labels in the rest of scraped metrics.
In this case the if
series selector
can be applied to action: labeldrop
or action: labelkeep
.
For example, the following config drops labels with names starting from foo_
prefix from metrics matching a{b="c"}
series selector:
scrape_configs:
- job_name: test
static_configs:
- targets: [host123]
metric_relabel_configs:
- action: labeldrop
if: 'a{b="c"}'
regex: "foo_.*"
See also how to remove labels from scraped metrics.
How to remove labels from scraped metrics
Sometimes it may be needed to remove labels from scraped metrics. For example, if some labels
lead to high cardinality
or high churn rate issues,
then it may be a good idea to drop these labels during scrapes.
This can be done with action: labeldrop
or action: labelkeep
relabeling rules at metric_relabel_configs
section:
action: labeldrop
drops labels with names matching the givenregex
optionaction: labelkeep
drops labels with names not matching the givenregex
option
For example, the following config drops labels with names starting with foo_
prefix from all the metrics scraped from the http://host123/metrics
:
scrape_configs:
- job_name: test
static_configs:
- targets: [host123]
metric_relabel_configs:
- action: labeldrop
regex: "foo_.*"
The regex
option can contain arbitrary regular expression in RE2 format.
The regex
option is applied to every label name in the target. It is automatically anchored, so it must match the whole label name.
The label name is left as is if the regex
doesn't match it.
Important notes:
- Labels with
__
prefix are automatically removed after the relabeling, so there is no need in removing them with relabeling rules. - Make sure that metrics exposed by the target can be uniquely identified by their names and the remaining labels after label removal. Otherwise, duplicate metrics with duplicate timestamps and different values will be pushed to the storage. This is an undesired issue in most cases.
See also useful tips for metric relabeling.
How to drop metrics during scrape
Sometimes it is needed to drop some metrics during scrapes. For example, if some metrics result
in high cardinality
or high churn rate issues,
then it may be a good idea to drop these metrics during scrapes. This can be done with the action: drop
or action: keep
relabeling rules at metric_relabel_configs
section:
action: drop
drops all the metrics, which match theif
series selectoraction: keep
drops all the metrics, which don't match theif
series selector
For example, the following config drops all the metrics obtained from http://host123/metrics
, which start with foo_
prefix:
scrape_configs:
- job_name: test
static_configs:
- targets: [host123]
metric_relabel_configs:
- if: '{__name__=~"foo_.*"}'
action: drop
Note that the relabeling config is specified under metric_relabel_configs
section instead of relabel_configs
section:
- The
relabel_configs
is applied to the configured/discovered targets. - The
metric_relabel_configs
is applied to metrics scraped from the configured/discovered targets.
See also useful tips for metric relabeling.
How to remove labels from a subset of targets
Sometimes it is needed to remove some labels from a subset of discovered targets,
while leaving these labels in the rest of discovered targets.
In this case the if
selector
can be added to action: labeldrop
or action: labelkeep
relabeling rule.
For example, the following config discovers pod targets in Kubernetes,
extracts pod-level labels into labels with foo_
prefix and then drops all the labels
with foo_bar_
prefix in their names for targets matching {__address__=~"pod123.+"}
selector:
scrape_configs:
- job_name: k8s
kubernetes_sd_configs:
- role: pod
relabel_configs:
- action: labelmap
regex: "__meta_kubernetes_pod_label_(.+)"
replacement: "foo_$1"
- action: labeldrop
if: '{__address__=~"pod123.+"}'
regex: "foo_bar_.*"
See also how to remove labels from targets.
How to remove labels from targets
Sometimes it is needed to remove some labels from discovered targets.
In this case the action: labeldrop
and action: labelkeep
relabeling options can be used:
action: labeldrop
drops all the labels with names matching theregex
optionaction: labelkeep
drops all the labels with names not matching theregex
option
For example, the following config discovers pod targets in Kubernetes,
extracts pod-level labels into labels with foo_
prefix and then drops all the labels
with foo_bar_
prefix in their names:
scrape_configs:
- job_name: k8s
kubernetes_sd_configs:
- role: pod
relabel_configs:
- action: labelmap
regex: "__meta_kubernetes_pod_label_(.+)"
replacement: "foo_$1"
- action: labeldrop
regex: "foo_bar_.*"
The regex
option can contain arbitrary regular expression in RE2 format.
The regex
option is applied to every label name in the target. It is automatically anchored, so it must match the whole label name.
The label name is left as is if the regex
doesn't match it.
Important notes:
- Labels with
__
prefix are automatically removed after the relabeling, so there is no need in removing them with relabeling rules. - Do not remove
instance
andjob
labels, since this may result in duplicate scrape targets with identical sets of labels.
See also useful tips for target relabeling.
How to remove prefixes from target label names
Sometimes it is needed to remove __meta_*
prefixes from meta-labels of the discovered targets.
For example, Kubernetes service discovery adds __meta_kubernetes_pod_label_<labelname>
labels per each pod-level label. In this case it may be needed to leave only the <labelname>
part of such label names,
while removing the __meta_kubernetes_pod_label_
prefix. This can be done with action: labelmap
relabeling option:
scrape_configs:
- job_name: k8s
kubernetes_sd_configs:
- role: pod
relabel_configs:
- action: labelmap
regex: "__meta_kubernetes_pod_label_(.+)"
replacement: "$1"
The regex
option can contain arbitrary regular expression in RE2 format.
The regex
option is applied to every label name in the target. It is automatically anchored, so it must match the whole label name.
It can contain capture groups such as (.+)
in the config above. These capture groups can be referenced then inside replacement
option
with the $N
syntax, where N
is the number of the capture group in regex
. The first capture group has the $1
reference.
The label name is left as is if the regex
doesn't match it.
See also useful tips for target relabeling.
How to extract label parts
Relabeling allows extracting parts from label values and storing them into arbitrary labels.
This is performed with regex
and replacement
options in relabeling rules.
For example, the following config discovers pod targets in Kubernetes,
extracts bar
part from foo/bar
container name and stores it into the xyz
label with abc_
prefix:
scrape_configs:
- job_name: k8s
kubernetes_sd_configs:
- role: pod
relabel_configs:
- source_labels: [__meta_kubernetes_pod_container_name]
regex: "[^/]+/(.+)"
replacement: "abc_$1"
target_label: xyz
The regex
option can contain arbitrary regular expression in RE2 format.
The regex
option is automatically anchored, so it must match the whole value from source_labels
.
It can contain capture groups such as (.+)
in the config above. These capture groups can be referenced then inside replacement
option
with the $N
syntax, where N
is the number of the capture group in regex
. The first capture group has the $1
reference.
It is possible to construct a label from multiple parts of different labels. In this case just specify the needed source labels inside source_labels
list.
The values of labels specified in source_labels
list are joined with ;
separator by default before being matched against the regex
.
The separator can be overridden via separator
option.
If the regex
doesn't match the value constructed from source_labels
, then the relabeling rule is skipped and the remaining relabeling rules are executed.
See also useful tips for target relabeling.
How to modify instance and job
Single-node VictoriaMetrics and vmagent automatically add instance
and job
labels per each discovered target:
- The
job
label is set tojob_name
value specified in the corresponding scrape_config. - The
instance
label is set to thehost:port
part of__address__
label value after target-level relabeling. The__address__
label value is automatically set to the most suitable value depending on the used service discovery type. The__address__
label can be overridden during relabeling - see these docs.
Both instance
and job
labels can be overridden during relabeling. For example, the following config discovers pod targets
in Kubernetes and overrides job
label from k8s
to foo
:
scrape_configs:
- job_name: k8s
kubernetes_sd_configs:
- role: pod
relabel_configs:
- target_label: job
replacement: foo
See also useful tips for target relabeling.
How to modify scrape urls in targets
URLs for scrape targets are composed of the following parts:
- Scheme (e.g.
http
orhttps
). The scheme is available during target relabeling in a special label -__scheme__
. By default, the scheme is set tohttp
. It can be overridden either by specifying thescheme
option at scrape_config level or by updating the__scheme__
label during relabeling. - Host and port (e.g.
host12:3456
). This information is available during target relabeling in a special label -__address__
. Every supported service discovery type sets the__address__
label to the most suitable value. Sometimes this value needs to be modified. In this case just update the__address__
label during relabeling to the needed value. The port part is optional. If it is missing, then it is automatically set either to80
or443
depending on the used scheme (http
orhttps
). Thehost:port
part from the final__address__
label is automatically set toinstance
label unless theinstance
label is explicitly set during relabeling. The__address__
label can contain the full scrape url, e.g.http://host:port/metrics/path?query_args
. In this case the__scheme__
and__metrics_path__
labels are ignored. - URL path (e.g.
/metrics
). This information is available during target relabeling in a special label -__metrics_path__
. By default, the__metrics_path__
is set to/metrics
. It can be overridden either by specifying themetrics_path
option at scrape_config or by updating the__metrics_path__
label during relabeling. - Query args (e.g.
?foo=bar&baz=xyz
). This information is available during target relabeling in special labels with__param_
prefix. For example,__param_foo
would have thebar
value, while__param_baz
would have thexyz
value for?foo=bar&baz=xyz
query string. The query args can be specified either viaparams
section at scrape_config or by updating/setting the corresponding__param_*
labels during relabeling.
The resulting scrape url looks like the following:
<__scheme__> + "://" + <__address__> + <__metrics_path__> + <"?" + query_args_from_param_labels>
It is expected that the target exposes metrics in Prometheus text exposition format at the resulting scrape url.
Given the scrape url construction rules above, the following config discovers pod targets
in Kubernetes
and constructs per-target scrape url as https://<pod_name>/foo/bar?baz=<container_name>
:
scrape_configs:
- job_name: k8s
kubernetes_sd_configs:
- role: pod
metrics_path: /foo/bar
relabel_configs:
- target_label: __scheme__
replacement: https
- source_labels: [__meta_kubernetes_pod_name]
target_label: __address__
- source_labels: [__meta_kubernetes_pod_container_name]
target_label: __param_baz
See also useful tips for target relabeling.
How to copy labels in scrape targets
Labels can be copied by specifying the source labels via source_labels
relabeling option
and specifying the target label via target_label
relabeling option.
For example, the following config copies __meta_kubernetes_pod_name
label to pod
label
for all the discovered pods in Kubernetes:
scrape_configs:
- job_name: k8s
kubernetes_sd_configs:
- role: pod
relabel_configs:
- source_labels: [__meta_kubernetes_pod_name]
target_label: pod
Note that the source_labels
option accepts a list of labels in square brackets. If multiple labels are specified
in the source_labels
list, then the specified label values are joined into a single string with ;
delimiter by default.
The delimiter can be modified by specifying it via separator
option.
For example, the following config sets the pod_name:container_port
value to the host_port
label
for all the discovered pod targets in Kubernetes:
scrape_configs:
- job_name: k8s
kubernetes_sd_configs:
- role: pod
relabel_configs:
- source_labels: [__meta_kubernetes_pod_name, __meta_kubernetes_pod_container_port_number]
separator: ":"
target_label: host_port
See also useful tips for target relabeling.
How to add labels to scrape targets
Additional labels can be added to scrape targets by specifying the label name in target_label
relabeling option
and by specifying the label value in replacement
relabeling option.
The same approach can be used for updating already existing label values at target level.
For example, the following config adds {foo="bar"}
label to all the discovered pods in Kubernetes:
scrape_configs:
- job_name: k8s
kubernetes_sd_configs:
- role: pod
relabel_configs:
- target_label: "foo"
replacement: "bar"
The labels, which are added to the target, are automatically added to all the metrics scraped from the target.
For example, if the target exposes the metric metric{label="value"}
, then the metric is transformed into metric{label="value",foo="bar"}
before being sent to the storage.
If the metric exported by the target contains the same label as the target itself, then the exported_
prefix is added to the exported label name.
For example, if the target exposes the metric metric{foo="baz"}
, then the metric is transformed into metric{exported_foo="baz",foo="bar"}
.
This behaviour can be changed by specifying honor_labels: true
option at the given scrape config. In this case the exported label overrides
the target's label. In this case the metric{foo="baz"}
stays the same. Example config with honor_labels: true
:
scrape_configs:
- job_name: k8s
kubernetes_sd_configs:
- role: pod
honor_labels: true
relabel_configs:
- target_label: "foo"
replacement: "bar"
See also useful tips for target relabeling.
How to drop discovered targets
If a particular discovered target shouldn't be scraped, then action: keep
or action: drop
relabeling rules
must be used inside relabel_configs
section.
The action: keep
keeps only scrape targets with labels matching the if
selector,
while dropping the rest of targets. For example, the following config discovers pod targets in Kubernetes
and scrapes only pods with names starting with foo
prefix:
scrape_configs:
- job_name: foo_pods
kubernetes_sd_configs:
- role: pod
relabel_configs:
- if: '{__meta_kubernetes_pod_name=~"foo.*"}'
action: keep
The action: drop
drops all the scrape targets with labels matching the if
selector,
while keeping the rest of targets. For example, the following config discovers pod targets in Kubernetes
and scrapes only pods with names starting with prefixes other than foo
:
scrape_configs:
- job_name: not_foo_pods
kubernetes_sd_configs:
- role: pod
relabel_configs:
- if: '{__meta_kubernetes_pod_name=~"foo.*"}'
action: drop
See also useful tips for target relabeling.
Useful tips for target relabeling
- Target relabeling can be debugged by clicking the
debug
link for the needed target on thehttp://vmagent:8429/target
or on thehttp://vmagent:8429/service-discovery
pages. See these docs. - Every discovered target contains a set of meta-labels, which start with
__meta_
prefix. The specific sets of labels per each supported service discovery option are listed here. - Every discovered target contains additional labels with
__
prefix other than__meta_
labels. See these docs for more details. - All the labels, which start with
__
prefix, are automatically removed from targets after the relabeling. So it is common practice to store temporary labels with names starting with__
during target relabeling. - All the target-level labels are automatically added to all the metrics scraped from targets.
- The list of discovered scrape targets with all the discovered meta-labels is available at
http://vmagent:8429/service-discovery
page forvmagent
and athttp://victoriametrics:8428/service-discovery
page for single-node VictoriaMetrics. - The list of active targets with the final set of labels left after relabeling is available at
http://vmagent:8429/targets
page forvmagent
and athttp://victoriametrics:8428/targets
page for single-node VictoriaMetrics.
Useful tips for metric relabeling
- Metric relabeling can be debugged at
http://vmagent:8429/metric-relabel-debug
page. See these docs. - All the labels, which start with
__
prefix, are automatically removed from metrics after the relabeling. So it is common practice to store temporary labels with names starting with__
during metrics relabeling. - All the target-level labels are automatically added to all the metrics scraped from targets, so target-level labels are available during metrics relabeling.