Promtail is configured in a YAML file (usually referred to as config.yaml
)
which contains information on the Promtail server, where positions are stored,
and how to scrape logs from files.
- Configuration File Reference
- server_config
- client_config
- position_config
- scrape_config
- target_config
- Example Docker Config
- Example Static Config
- Example Journal Config
- Example Syslog Config
To specify which configuration file to load, pass the -config.file
flag at the
command line. The file is written in YAML format,
defined by the schema below. Brackets indicate that a parameter is optional. For
non-list parameters the value is set to the specified default.
For more detailed information on configuring how to discover and scrape logs from targets, see Scraping. For more information on transforming logs from scraped targets, see Pipelines.
Generic placeholders are defined as follows:
<boolean>
: a boolean that can take the valuestrue
orfalse
<int>
: any integer matching the regular expression[1-9]+[0-9]*
<duration>
: a duration matching the regular expression[0-9]+(ms|[smhdwy])
<labelname>
: a string matching the regular expression[a-zA-Z_][a-zA-Z0-9_]*
<labelvalue>
: a string of Unicode characters<filename>
: a valid path relative to current working directory or an absolute path.<host>
: a valid string consisting of a hostname or IP followed by an optional port number<string>
: a regular string<secret>
: a regular string that is a secret, such as a password
Supported contents and default values of config.yaml
:
# Configures the server for Promtail.
[server: <server_config>]
# Describes how Promtail connects to multiple instances
# of Loki, sending logs to each.
clients:
- [<client_config>]
# Describes how to save read file offsets to disk
[positions: <position_config>]
scrape_configs:
- [<scrape_config>]
# Configures how tailed targets will be watched.
[target_config: <target_config>]
The server_config
block configures Promtail's behavior as an HTTP server:
# HTTP server listen host
[http_listen_address: <string>]
# HTTP server listen port
[http_listen_port: <int> | default = 80]
# gRPC server listen host
[grpc_listen_address: <string>]
# gRPC server listen port
[grpc_listen_port: <int> | default = 9095]
# Register instrumentation handlers (/metrics, etc.)
[register_instrumentation: <boolean> | default = true]
# Timeout for graceful shutdowns
[graceful_shutdown_timeout: <duration> | default = 30s]
# Read timeout for HTTP server
[http_server_read_timeout: <duration> | default = 30s]
# Write timeout for HTTP server
[http_server_write_timeout: <duration> | default = 30s]
# Idle timeout for HTTP server
[http_server_idle_timeout: <duration> | default = 120s]
# Max gRPC message size that can be received
[grpc_server_max_recv_msg_size: <int> | default = 4194304]
# Max gRPC message size that can be sent
[grpc_server_max_send_msg_size: <int> | default = 4194304]
# Limit on the number of concurrent streams for gRPC calls (0 = unlimited)
[grpc_server_max_concurrent_streams: <int> | default = 100]
# Log only messages with the given severity or above. Supported values [debug,
# info, warn, error]
[log_level: <string> | default = "info"]
# Base path to server all API routes from (e.g., /v1/).
[http_path_prefix: <string>]
The client_config
block configures how Promtail connects to an instance of
Loki:
# The URL where Loki is listening, denoted in Loki as http_listen_address and
# http_listen_port. If Loki is running in microservices mode, this is the HTTP
# URL for the Distributor.
url: <string>
# The tenant ID used by default to push logs to Loki. If omitted or empty
# it assumes Loki is running in single-tenant mode and no X-Scope-OrgID header
# is sent.
[tenant_id: <string>]
# Maximum amount of time to wait before sending a batch, even if that
# batch isn't full.
[batchwait: <duration> | default = 1s]
# Maximum batch size (in bytes) of logs to accumulate before sending
# the batch to Loki.
[batchsize: <int> | default = 102400]
# If using basic auth, configures the username and password
# sent.
basic_auth:
# The username to use for basic auth
[username: <string>]
# The password to use for basic auth
[password: <string>]
# The file containing the password for basic auth
[password_file: <filename>]
# Bearer token to send to the server.
[bearer_token: <secret>]
# File containing bearer token to send to the server.
[bearer_token_file: <filename>]
# HTTP proxy server to use to connect to the server.
[proxy_url: <string>]
# If connecting to a TLS server, configures how the TLS
# authentication handshake will operate.
tls_config:
# The CA file to use to verify the server
[ca_file: <string>]
# The cert file to send to the server for client auth
[cert_file: <filename>]
# The key file to send to the server for client auth
[key_file: <filename>]
# Validates that the server name in the server's certificate
# is this value.
[server_name: <string>]
# If true, ignores the server certificate being signed by an
# unknown CA.
[insecure_skip_verify: <boolean> | default = false]
# Configures how to retry requests to Loki when a request
# fails.
backoff_config:
# Initial backoff time between retries
[minbackoff: <duration> | default = 100ms]
# Maximum backoff time between retries
[maxbackoff: <duration> | default = 10s]
# Maximum number of retries to do
[maxretries: <int> | default = 10]
# Static labels to add to all logs being sent to Loki.
# Use map like {"foo": "bar"} to add a label foo with
# value bar.
external_labels:
[ <labelname>: <labelvalue> ... ]
# Maximum time to wait for a server to respond to a request
[timeout: <duration> | default = 10s]
The position_config
block configures where Promtail will save a file
indicating how far it has read into a file. It is needed for when Promtail
is restarted to allow it to continue from where it left off.
# Location of positions file
[filename: <string> | default = "/var/log/positions.yaml"]
# How often to update the positions file
[sync_period: <duration> | default = 10s]
# Whether to ignore & later overwrite positions files that are corrupted
[ignore_invalid_yaml: <boolean> | default = false]
The scrape_config
block configures how Promtail can scrape logs from a series
of targets using a specified discovery method:
# Name to identify this scrape config in the Promtail UI.
job_name: <string>
# Describes how to parse log lines. Suported values [cri docker raw]
[entry_parser: <string> | default = "docker"]
# Describes how to transform logs from targets.
[pipeline_stages: <pipeline_stages>]
# Describes how to scrape logs from the journal.
[journal: <journal_config>]
# Describes how to receive logs from syslog.
[syslog: <syslog_config>]
# Describes how to relabel targets to determine if they should
# be processed.
relabel_configs:
- [<relabel_config>]
# Static targets to scrape.
static_configs:
- [<static_config>]
# Files containing targets to scrape.
file_sd_configs:
- [<file_sd_configs>]
# Describes how to discover Kubernetes services running on the
# same host.
kubernetes_sd_configs:
- [<kubernetes_sd_config>]
The pipeline stages (pipeline_stages
) is used to transform
log entries and their labels after discovery and consists of a list of any of the items listed below.
Stages serve several purposes, more detail can be found here, however generally you extract data with regex
or json
stages into a temporary map which can then be use as labels
or output
or any of the other stages aside from docker
and cri
which are explained in more detail below.
- [
<docker> |
<cri> |
<regex> |
<json> |
<template> |
<match> |
<timestamp> |
<output> |
<labels> |
<metrics> |
<tenant>
]
The Docker stage parses the contents of logs from Docker containers, and is defined by name with an empty object:
docker: {}
The docker stage will match and parse log lines of this format:
`{"log":"level=info ts=2019-04-30T02:12:41.844179Z caller=filetargetmanager.go:180 msg=\"Adding target\"\n","stream":"stderr","time":"2019-04-30T02:12:41.8443515Z"}`
Automatically extracting the time
into the logs timestamp, stream
into a label, and log
field into the output, this can be very helpful as docker is wrapping your application log in this way and this will unwrap it for further pipeline processing of just the log content.
The Docker stage is just a convenience wrapper for this definition:
- json:
output: log
stream: stream
timestamp: time
- labels:
stream:
- timestamp:
source: timestamp
format: RFC3339Nano
- output:
source: output
The CRI stage parses the contents of logs from CRI containers, and is defined by name with an empty object:
cri: {}
The CRI stage will match and parse log lines of this format:
2019-01-01T01:00:00.000000001Z stderr P some log message
Automatically extracting the time
into the logs timestamp, stream
into a label, and the remaining message into the output, this can be very helpful as CRI is wrapping your application log in this way and this will unwrap it for further pipeline processing of just the log content.
The CRI stage is just a convenience wrapper for this definition:
- regex:
expression: "^(?s)(?P<time>\\S+?) (?P<stream>stdout|stderr) (?P<flags>\\S+?) (?P<content>.*)$",
- labels:
stream:
- timestamp:
source: time
format: RFC3339Nano
- output:
source: content
The Regex stage takes a regular expression and extracts captured named groups to be used in further stages.
regex:
# The RE2 regular expression. Each capture group must be named.
expression: <string>
# Name from extracted data to parse. If empty, uses the log message.
[source: <string>]
The JSON stage parses a log line as JSON and takes JMESPath expressions to extract data from the JSON to be used in further stages.
json:
# Set of key/value pairs of JMESPath expressions. The key will be
# the key in the extracted data while the expression will be the value,
# evaluated as a JMESPath from the source data.
expressions:
[ <string>: <string> ... ]
# Name from extracted data to parse. If empty, uses the log message.
[source: <string>]
The template stage uses Go's
text/template
language to manipulate
values.
template:
# Name from extracted data to parse. If key in extract data doesn't exist, an
# entry for it will be created.
source: <string>
# Go template string to use. In additional to normal template
# functions, ToLower, ToUpper, Replace, Trim, TrimLeft, TrimRight,
# TrimPrefix, TrimSuffix, and TrimSpace are available as functions.
template: <string>
Example:
template:
source: level
template: '{{ if eq .Value "WARN" }}{{ Replace .Value "WARN" "OK" -1 }}{{ else }}{{ .Value }}{{ end }}'
The match stage conditionally executes a set of stages when a log entry matches a configurable LogQL stream selector.
match:
# LogQL stream selector.
selector: <string>
# Names the pipeline. When defined, creates an additional label in
# the pipeline_duration_seconds histogram, where the value is
# concatenated with job_name using an underscore.
[pipieline_name: <string>]
# Nested set of pipeline stages only if the selector
# matches the labels of the log entries:
stages:
- [
<docker> |
<cri> |
<regex>
<json> |
<template> |
<match> |
<timestamp> |
<output> |
<labels> |
<metrics>
]
The timestamp stage parses data from the extracted map and overrides the final time value of the log that is stored by Loki. If this stage isn't present, Promtail will associate the timestamp of the log entry with the time that log entry was read.
timestamp:
# Name from extracted data to use for the timestamp.
source: <string>
# Determines how to parse the time string. Can use
# pre-defined formats by name: [ANSIC UnixDate RubyDate RFC822
# RFC822Z RFC850 RFC1123 RFC1123Z RFC3339 RFC3339Nano Unix
# UnixMs UnixUs UnixNs].
format: <string>
# IANA Timezone Database string.
[location: <string>]
The output stage takes data from the extracted map and sets the contents of the log entry that will be stored by Loki.
output:
# Name from extracted data to use for the log entry.
source: <string>
The labels stage takes data from the extracted map and sets additional labels on the log entry that will be sent to Loki.
labels:
# Key is REQUIRED and the name for the label that will be created.
# Value is optional and will be the name from extracted data whose value
# will be used for the value of the label. If empty, the value will be
# inferred to be the same as the key.
[ <string>: [<string>] ... ]
The metrics stage allows for defining metrics from the extracted data.
Created metrics are not pushed to Loki and are instead exposed via Promtail's
/metrics
endpoint. Prometheus should be configured to scrape Promtail to be
able to retrieve the metrics configured by this stage.
# A map where the key is the name of the metric and the value is a specific
# metric type.
metrics:
[<string>: [ <counter> | <gauge> | <histogram> ] ...]
Defines a counter metric whose value only goes up.
# The metric type. Must be Counter.
type: Counter
# Describes the metric.
[description: <string>]
# Key from the extracted data map to use for the mtric,
# defaulting to the metric's name if not present.
[source: <string>]
config:
# Filters down source data and only changes the metric
# if the targeted value exactly matches the provided string.
# If not present, all data will match.
[value: <string>]
# Must be either "inc" or "add" (case insensitive). If
# inc is chosen, the metric value will increase by 1 for each
# log line receieved that passed the filter. If add is chosen,
# the extracted value most be convertible to a positive float
# and its value will be added to the metric.
action: <string>
Defines a gauge metric whose value can go up or down.
# The metric type. Must be Gauge.
type: Gauge
# Describes the metric.
[description: <string>]
# Key from the extracted data map to use for the mtric,
# defaulting to the metric's name if not present.
[source: <string>]
config:
# Filters down source data and only changes the metric
# if the targeted value exactly matches the provided string.
# If not present, all data will match.
[value: <string>]
# Must be either "set", "inc", "dec"," add", or "sub". If
# add, set, or sub is chosen, the extracted value must be
# convertible to a positive float. inc and dec will increment
# or decrement the metric's value by 1 respectively.
action: <string>
Defines a histogram metric whose values are bucketed.
# The metric type. Must be Histogram.
type: Histogram
# Describes the metric.
[description: <string>]
# Key from the extracted data map to use for the mtric,
# defaulting to the metric's name if not present.
[source: <string>]
config:
# Filters down source data and only changes the metric
# if the targeted value exactly matches the provided string.
# If not present, all data will match.
[value: <string>]
# Must be either "inc" or "add" (case insensitive). If
# inc is chosen, the metric value will increase by 1 for each
# log line receieved that passed the filter. If add is chosen,
# the extracted value most be convertible to a positive float
# and its value will be added to the metric.
action: <string>
# Holds all the numbers in which to bucket the metric.
buckets:
- <int>
The tenant stage is an action stage that sets the tenant ID for the log entry picking it from a field in the extracted data map.
tenant:
# Name from extracted data to whose value should be set as tenant ID.
# Either source or value config option is required, but not both (they
# are mutually exclusive).
[ source: <string> ]
# Value to use to set the tenant ID when this stage is executed. Useful
# when this stage is included within a conditional pipeline with "match".
[ value: <string> ]
The journal_config
block configures reading from the systemd journal from
Promtail. Requires a build of Promtail that has journal support enabled. If
using the AMD64 Docker image, this is enabled by default.
# When true, log messages from the journal are passed through the
# pipeline as a JSON message with all of the journal entries' original
# fields. When false, the log message is the text content of the MESSAGE
# field from the journal entry.
[json: <boolean> | default = false]
# The oldest relative time from process start that will be read
# and sent to Loki.
[max_age: <duration> | default = 7h]
# Label map to add to every log coming out of the journal
labels:
[ <labelname>: <labelvalue> ... ]
# Path to a directory to read entries from. Defaults to system
# paths (/var/log/journal and /run/log/journal) when empty.
[path: <string>]
The syslog_config
block configures a syslog listener allowing users to push
logs to promtail with the syslog protocol.
Currently supported is IETF Syslog (RFC5424)
with and without octet counting.
The recommended deployment is to have a dedicated syslog forwarder like syslog-ng or rsyslog in front of promtail. The forwarder can take care of the various specifications and transports that exist (UDP, BSD syslog, ...).
Octet counting is recommended as the message framing method. In a stream with non-transparent framing, promtail needs to wait for the next message to catch multi-line messages, therefore delays between messages can occur.
See recommended output configurations for syslog-ng and rsyslog. Both configurations enable IETF Syslog with octet-counting.
You may need to increase the open files limit for the promtail process
if many clients are connected. (ulimit -Sn
)
# TCP address to listen on. Has the format of "host:port".
listen_address: <string>
# The idle timeout for tcp syslog connections, default is 120 seconds.
idle_timeout: <duration>
# Whether to convert syslog structured data to labels.
# A structured data entry of [example@99999 test="yes"] would become
# the label "__syslog_message_sd_example_99999_test" with the value "yes".
label_structured_data: <bool>
# Label map to add to every log message.
labels:
[ <labelname>: <labelvalue> ... ]
__syslog_connection_ip_address
: The remote IP address.__syslog_connection_hostname
: The remote hostname.__syslog_message_severity
: The syslog severity parsed from the message. Symbolic name as per syslog_message.go.__syslog_message_facility
: The syslog facility parsed from the message. Symbolic name as per syslog_message.go andsyslog(3)
.__syslog_message_hostname
: The hostname parsed from the message.__syslog_message_app_name
: The app-name field parsed from the message.__syslog_message_proc_id
: The procid field parsed from the message.__syslog_message_msg_id
: The msgid field parsed from the message.__syslog_message_sd_<sd_id>[_<iana_enterprise_id>]_<sd_name>
: The structured-data field parsed from the message. The data field[custom@99770 example="1"]
becomes__syslog_message_sd_custom_99770_example
.
Relabeling is a powerful tool to dynamically rewrite the label set of a target before it gets scraped. Multiple relabeling steps can be configured per scrape configuration. They are applied to the label set of each target in order of their appearance in the configuration file.
After relabeling, the instance
label is set to the value of __address__
by
default if it was not set during relabeling. The __scheme__
and
__metrics_path__
labels are set to the scheme and metrics path of the target
respectively. The __param_<name>
label is set to the value of the first passed
URL parameter called <name>
.
Additional labels prefixed with __meta_
may be available during the relabeling
phase. They are set by the service discovery mechanism that provided the target
and vary between mechanisms.
Labels starting with __
will be removed from the label set after target
relabeling is completed.
If a relabeling step needs to store a label value only temporarily (as the
input to a subsequent relabeling step), use the __tmp
label name prefix. This
prefix is guaranteed to never be used by Prometheus itself.
# The source labels select values from existing labels. Their content is concatenated
# using the configured separator and matched against the configured regular expression
# for the replace, keep, and drop actions.
[ source_labels: '[' <labelname> [, ...] ']' ]
# Separator placed between concatenated source label values.
[ separator: <string> | default = ; ]
# Label to which the resulting value is written in a replace action.
# It is mandatory for replace actions. Regex capture groups are available.
[ target_label: <labelname> ]
# Regular expression against which the extracted value is matched.
[ regex: <regex> | default = (.*) ]
# Modulus to take of the hash of the source label values.
[ modulus: <uint64> ]
# Replacement value against which a regex replace is performed if the
# regular expression matches. Regex capture groups are available.
[ replacement: <string> | default = $1 ]
# Action to perform based on regex matching.
[ action: <relabel_action> | default = replace ]
<regex>
is any valid
RE2 regular expression. It is
required for the replace
, keep
, drop
, labelmap
,labeldrop
and
labelkeep
actions. The regex is anchored on both ends. To un-anchor the regex,
use .*<regex>.*
.
<relabel_action>
determines the relabeling action to take:
replace
: Matchregex
against the concatenatedsource_labels
. Then, settarget_label
toreplacement
, with match group references (${1}
,${2}
, ...) inreplacement
substituted by their value. Ifregex
does not match, no replacement takes place.keep
: Drop targets for whichregex
does not match the concatenatedsource_labels
.drop
: Drop targets for whichregex
matches the concatenatedsource_labels
.hashmod
: Settarget_label
to themodulus
of a hash of the concatenatedsource_labels
.labelmap
: Matchregex
against all label names. Then copy the values of the matching labels to label names given byreplacement
with match group references (${1}
,${2}
, ...) inreplacement
substituted by their value.labeldrop
: Matchregex
against all label names. Any label that matches will be removed from the set of labels.labelkeep
: Matchregex
against all label names. Any label that does not match will be removed from the set of labels.
Care must be taken with labeldrop
and labelkeep
to ensure that logs are
still uniquely labeled once the labels are removed.
A static_config
allows specifying a list of targets and a common label set
for them. It is the canonical way to specify static targets in a scrape
configuration.
# Configures the discovery to look on the current machine. Must be either
# localhost or the hostname of the current computer.
targets:
- localhost
# Defines a file to scrape and an optional set of additional labels to apply to
# all streams defined by the files from __path__.
labels:
# The path to load logs from. Can use glob patterns (e.g., /var/log/*.log).
__path__: <string>
# Additional labels to assign to the logs
[ <labelname>: <labelvalue> ... ]
File-based service discovery provides a more generic way to configure static targets and serves as an interface to plug in custom service discovery mechanisms.
It reads a set of files containing a list of zero or more
<static_config>
s. Changes to all defined files are detected via disk watches
and applied immediately. Files may be provided in YAML or JSON format. Only
changes resulting in well-formed target groups are applied.
The JSON file must contain a list of static configs, using this format:
[
{
"targets": [ "localhost" ],
"labels": {
"__path__": "<string>", ...
"<labelname>": "<labelvalue>", ...
}
},
...
]
As a fallback, the file contents are also re-read periodically at the specified refresh interval.
Each target has a meta label __meta_filepath
during the
relabeling phase. Its value is set to the
filepath from which the target was extracted.
# Patterns for files from which target groups are extracted.
files:
[ - <filename_pattern> ... ]
# Refresh interval to re-read the files.
[ refresh_interval: <duration> | default = 5m ]
Where <filename_pattern>
may be a path ending in .json
, .yml
or .yaml
.
The last path segment may contain a single *
that matches any character
sequence, e.g. my/path/tg_*.json
.
Kubernetes SD configurations allow retrieving scrape targets from Kubernetes' REST API and always staying synchronized with the cluster state.
One of the following role
types can be configured to discover targets:
The node
role discovers one target per cluster node with the address
defaulting to the Kubelet's HTTP port.
The target address defaults to the first existing address of the Kubernetes
node object in the address type order of NodeInternalIP
, NodeExternalIP
,
NodeLegacyHostIP
, and NodeHostName
.
Available meta labels:
__meta_kubernetes_node_name
: The name of the node object.__meta_kubernetes_node_label_<labelname>
: Each label from the node object.__meta_kubernetes_node_labelpresent_<labelname>
:true
for each label from the node object.__meta_kubernetes_node_annotation_<annotationname>
: Each annotation from the node object.__meta_kubernetes_node_annotationpresent_<annotationname>
:true
for each annotation from the node object.__meta_kubernetes_node_address_<address_type>
: The first address for each node address type, if it exists.
In addition, the instance
label for the node will be set to the node name
as retrieved from the API server.
The service
role discovers a target for each service port of each service.
This is generally useful for blackbox monitoring of a service.
The address will be set to the Kubernetes DNS name of the service and respective
service port.
Available meta labels:
__meta_kubernetes_namespace
: The namespace of the service object.__meta_kubernetes_service_annotation_<annotationname>
: Each annotation from the service object.__meta_kubernetes_service_annotationpresent_<annotationname>
: "true" for each annotation of the service object.__meta_kubernetes_service_cluster_ip
: The cluster IP address of the service. (Does not apply to services of type ExternalName)__meta_kubernetes_service_external_name
: The DNS name of the service. (Applies to services of type ExternalName)__meta_kubernetes_service_label_<labelname>
: Each label from the service object.__meta_kubernetes_service_labelpresent_<labelname>
:true
for each label of the service object.__meta_kubernetes_service_name
: The name of the service object.__meta_kubernetes_service_port_name
: Name of the service port for the target.__meta_kubernetes_service_port_protocol
: Protocol of the service port for the target.
The pod
role discovers all pods and exposes their containers as targets. For
each declared port of a container, a single target is generated. If a container
has no specified ports, a port-free target per container is created for manually
adding a port via relabeling.
Available meta labels:
__meta_kubernetes_namespace
: The namespace of the pod object.__meta_kubernetes_pod_name
: The name of the pod object.__meta_kubernetes_pod_ip
: The pod IP of the pod object.__meta_kubernetes_pod_label_<labelname>
: Each label from the pod object.__meta_kubernetes_pod_labelpresent_<labelname>
:true
for each label from the pod object.__meta_kubernetes_pod_annotation_<annotationname>
: Each annotation from the pod object.__meta_kubernetes_pod_annotationpresent_<annotationname>
:true
for each annotation from the pod object.__meta_kubernetes_pod_container_init
:true
if the container is an InitContainer__meta_kubernetes_pod_container_name
: Name of the container the target address points to.__meta_kubernetes_pod_container_port_name
: Name of the container port.__meta_kubernetes_pod_container_port_number
: Number of the container port.__meta_kubernetes_pod_container_port_protocol
: Protocol of the container port.__meta_kubernetes_pod_ready
: Set totrue
orfalse
for the pod's ready state.__meta_kubernetes_pod_phase
: Set toPending
,Running
,Succeeded
,Failed
orUnknown
in the lifecycle.__meta_kubernetes_pod_node_name
: The name of the node the pod is scheduled onto.__meta_kubernetes_pod_host_ip
: The current host IP of the pod object.__meta_kubernetes_pod_uid
: The UID of the pod object.__meta_kubernetes_pod_controller_kind
: Object kind of the pod controller.__meta_kubernetes_pod_controller_name
: Name of the pod controller.
The endpoints
role discovers targets from listed endpoints of a service. For
each endpoint address one target is discovered per port. If the endpoint is
backed by a pod, all additional container ports of the pod, not bound to an
endpoint port, are discovered as targets as well.
Available meta labels:
__meta_kubernetes_namespace
: The namespace of the endpoints object.__meta_kubernetes_endpoints_name
: The names of the endpoints object.- For all targets discovered directly from the endpoints list (those not additionally inferred
from underlying pods), the following labels are attached:
__meta_kubernetes_endpoint_hostname
: Hostname of the endpoint.__meta_kubernetes_endpoint_node_name
: Name of the node hosting the endpoint.__meta_kubernetes_endpoint_ready
: Set totrue
orfalse
for the endpoint's ready state.__meta_kubernetes_endpoint_port_name
: Name of the endpoint port.__meta_kubernetes_endpoint_port_protocol
: Protocol of the endpoint port.__meta_kubernetes_endpoint_address_target_kind
: Kind of the endpoint address target.__meta_kubernetes_endpoint_address_target_name
: Name of the endpoint address target.
- If the endpoints belong to a service, all labels of the
role: service
discovery are attached. - For all targets backed by a pod, all labels of the
role: pod
discovery are attached.
The ingress
role discovers a target for each path of each ingress.
This is generally useful for blackbox monitoring of an ingress.
The address will be set to the host specified in the ingress spec.
Available meta labels:
__meta_kubernetes_namespace
: The namespace of the ingress object.__meta_kubernetes_ingress_name
: The name of the ingress object.__meta_kubernetes_ingress_label_<labelname>
: Each label from the ingress object.__meta_kubernetes_ingress_labelpresent_<labelname>
:true
for each label from the ingress object.__meta_kubernetes_ingress_annotation_<annotationname>
: Each annotation from the ingress object.__meta_kubernetes_ingress_annotationpresent_<annotationname>
:true
for each annotation from the ingress object.__meta_kubernetes_ingress_scheme
: Protocol scheme of ingress,https
if TLS config is set. Defaults tohttp
.__meta_kubernetes_ingress_path
: Path from ingress spec. Defaults to/
.
See below for the configuration options for Kubernetes discovery:
# The information to access the Kubernetes API.
# The API server addresses. If left empty, Prometheus is assumed to run inside
# of the cluster and will discover API servers automatically and use the pod's
# CA certificate and bearer token file at /var/run/secrets/kubernetes.io/serviceaccount/.
[ api_server: <host> ]
# The Kubernetes role of entities that should be discovered.
role: <role>
# Optional authentication information used to authenticate to the API server.
# Note that `basic_auth`, `bearer_token` and `bearer_token_file` options are
# mutually exclusive.
# password and password_file are mutually exclusive.
# Optional HTTP basic authentication information.
basic_auth:
[ username: <string> ]
[ password: <secret> ]
[ password_file: <string> ]
# Optional bearer token authentication information.
[ bearer_token: <secret> ]
# Optional bearer token file authentication information.
[ bearer_token_file: <filename> ]
# Optional proxy URL.
[ proxy_url: <string> ]
# TLS configuration.
tls_config:
[ <tls_config> ]
# Optional namespace discovery. If omitted, all namespaces are used.
namespaces:
names:
[ - <string> ]
Where <role>
must be endpoints
, service
, pod
, node
, or
ingress
.
See this example Prometheus configuration file for a detailed example of configuring Prometheus for Kubernetes.
You may wish to check out the 3rd party Prometheus Operator, which automates the Prometheus setup on top of Kubernetes.
The target_config
block controls the behavior of reading files from discovered
targets.
# Period to resync directories being watched and files being tailed to discover
# new ones or stop watching removed ones.
sync_period: "10s"
It's fairly difficult to tail Docker files on a standalone machine because they are in different locations for every OS. We recommend the Docker logging driver for local Docker installs or Docker Compose.
If running in a Kubernetes environment, you should look at the defined configs which are in helm and jsonnet, these leverage the prometheus service discovery libraries (and give promtail it's name) for automatically finding and tailing pods. The jsonnet config explains with comments what each section is for.
While promtail may have been named for the prometheus service discovery code, that same code works very well for tailing logs without containers or container environments directly on virtual machines or bare metal.
server:
http_listen_port: 9080
grpc_listen_port: 0
positions:
filename: /var/log/positions.yaml # This location needs to be writeable by promtail.
client:
url: http://ip_or_hostname_where_Loki_run:3100/loki/api/v1/push
scrape_configs:
- job_name: system
pipeline_stages:
static_configs:
- targets:
- localhost
labels:
job: varlogs # A `job` label is fairly standard in prometheus and useful for linking metrics and logs.
host: yourhost # A `host` label will help identify logs from this machine vs others
__path__: /var/log/*.log # The path matching uses a third party library: https://github.com/bmatcuk/doublestar
This example reads entries from a systemd journal:
server:
http_listen_port: 9080
grpc_listen_port: 0
positions:
filename: /tmp/positions.yaml
clients:
- url: http://ip_or_hostname_where_loki_runns:3100/loki/api/v1/push
scrape_configs:
- job_name: journal
journal:
max_age: 12h
labels:
job: systemd-journal
relabel_configs:
- source_labels: ['__journal__systemd_unit']
target_label: 'unit'
This example starts Promtail as a syslog receiver and can accept syslog entries in Promtail over TCP:
server:
http_listen_port: 9080
grpc_listen_port: 0
positions:
filename: /tmp/positions.yaml
clients:
- url: http://loki_addr:3100/loki/api/v1/push
scrape_configs:
- job_name: syslog
syslog:
listen_address: 0.0.0.0:1514
labels:
job: "syslog"
relabel_configs:
- source_labels: ['__syslog_message_hostname']
target_label: 'host'