promtail-config
Configuring Promtail
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
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.
Use environment variables in the configuration
You can use environment variable references in the configuration file to set values that need to be configurable during deployment.
To do this, pass -config.expand-env=true
and use:
${VAR}
Where VAR is the name of the environment variable.
Each variable reference is replaced at startup by the value of the environment variable. The replacement is case-sensitive and occurs before the YAML file is parsed. References to undefined variables are replaced by empty strings unless you specify a default value or custom error text.
To specify a default value, use:
${VAR:default_value}
Where default_value is the value to use if the environment variable is undefined.
Generic placeholders:
<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 string<secret>
: a string that represents a secret, such as a password
Supported contents and default values of config.yaml
:
# Configures the server for Promtail.
[server: <server_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>]
server
The server
block configures Promtail’s behavior as an HTTP server:
# Disable the HTTP and GRPC server.
[disable: <boolean> | default = false]
# HTTP server listen host
[http_listen_address: <string>]
# HTTP server listen port (0 means random port)
[http_listen_port: <int> | default = 80]
# gRPC server listen host
[grpc_listen_address: <string>]
# gRPC server listen port (0 means random 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>]
# Target managers check flag for Promtail readiness, if set to false the check is ignored
[health_check_target: <bool> | default = true]
positions
The positions
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]
scrape_configs
The scrape_configs
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 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 receive logs via the Loki push API, (e.g. from other Promtails or the Docker Logging Driver)
[loki_push_api: <loki_push_api_config>]
# Describes how to scrape logs from the Windows event logs.
[windows_events: <windows_events_config>]
# Describes how to fetch logs from Kafka via a Consumer group.
[kafka: <kafka_config>]
# Describes how to receive logs from gelf client.
[gelf: <gelf_config>]
# Configuration describing how to pull logs from Cloudflare.
[cloudflare: <cloudflare>]
# 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>]
# Describes how to use the Consul Catalog API to discover services registered with the
# consul cluster.
consul_sd_configs:
[ - <consul_sd_config> ... ]
# Describes how to use the Consul Agent API to discover services registered with the consul agent
# running on the same host as Promtail.
consulagent_sd_configs:
[ - <consulagent_sd_config> ... ]
# Describes how to use the Docker daemon API to discover containers running on
# the same host as Promtail.
docker_sd_configs:
[ - <docker_sd_config> ... ]
pipeline_stages
Pipeline stages are used to transform log entries and their labels. The pipeline is executed after the discovery process finishes. The pipeline_stages
object consists of a list of stages which correspond to the items listed below.
In most cases, you extract data from logs with regex
or json
stages. The extracted data is transformed into a temporary map object. The data can then be used by Promtail e.g. as values for labels
or as an output
. Additionally any other stage aside from docker
and cri
can access the extracted data.
- [
<docker> |
<cri> |
<regex> |
<json> |
<template> |
<match> |
<timestamp> |
<output> |
<labels> |
<metrics> |
<tenant> |
<replace>
]
docker
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
cri
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
regex
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>]
json
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>]
template
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 }}'
match
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.
[pipeline_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>
]
timestamp
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>]
output
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>
labels
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>] ... ]
metrics
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> ] ...]
counter
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 metric,
# 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 received 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>
gauge
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 metric,
# 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>
histogram
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 metric,
# 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 received 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>
tenant
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> ]
replace
The replace stage is a parsing stage that parses a log line using a regular expression and replaces the log line.
replace:
# The RE2 regular expression. Each named capture group will be added to extracted.
# Each capture group and named capture group will be replaced with the value given in
# `replace`
expression: <string>
# Name from extracted data to parse. If empty, uses the log message.
# The replaced value will be assigned back to soure key
[source: <string>]
# Value to which the captured group will be replaced. The captured group or the named
# captured group will be replaced with this value and the log line will be replaced with
# new replaced values. An empty value will remove the captured group from the log line.
[replace: <string>]
journal
The journal
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>]
Note: priority label is available as both value and keyword. For example, if priority
is 3
then the labels will be __journal_priority
with a value 3
and __journal_priority_keyword
with a corresponding keyword err
.
syslog
The syslog
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>
# Configure the receiver to use TLS.
tls_config:
# Certificate and key files sent by the server (required)
cert_file: <string>
key_file: <string>
# CA certificate used to validate client certificate. Enables client certificate verification when specified.
[ ca_file: <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> ... ]
# Whether Promtail should pass on the timestamp from the incoming syslog message.
# When false, or if no timestamp is present on the syslog message, Promtail will assign the current timestamp to the log when it was processed.
# Default is false
use_incoming_timestamp: <bool>
# Sets the maximum limit to the length of syslog messages
max_message_length: <int>
Available Labels
__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
.
loki_push_api
The loki_push_api
block configures Promtail to expose a Loki push API server.
Each job configured with a loki_push_api
will expose this API and will require a separate port.
Note the server
configuration is the same as server.
Promtail also exposes a second endpoint on /promtail/api/v1/raw
which expects newline-delimited log lines.
This can be used to send NDJSON or plaintext logs.
# The push server configuration options
[server: <server_config>]
# Label map to add to every log line sent to the push API
labels:
[ <labelname>: <labelvalue> ... ]
# If Promtail should pass on the timestamp from the incoming log or not.
# When false Promtail will assign the current timestamp to the log when it was processed.
# Does not apply to the plaintext endpoint on `/promtail/api/v1/raw`.
[use_incoming_timestamp: <bool> | default = false]
windows_events
The windows_events
block configures Promtail to scrape windows event logs and send them to Loki.
To subcribe to a specific events stream you need to provide either an eventlog_name
or an xpath_query
.
Events are scraped periodically every 3 seconds by default but can be changed using poll_interval
.
A bookmark path bookmark_path
is mandatory and will be used as a position file where Promtail will
keep record of the last event processed. This file persists across Promtail restarts.
You can set use_incoming_timestamp
if you want to keep incomming event timestamps. By default Promtail will use the timestamp when
the event was read from the event log.
Promtail will serialize JSON windows events, adding channel
and computer
labels from the event received.
You can add additional labels with the labels
property.
# LCID (Locale ID) for event rendering
# - 1033 to force English language
# - 0 to use default Windows locale
[locale: <int> | default = 0]
# Name of eventlog, used only if xpath_query is empty
# Example: "Application"
[eventlog_name: <string> | default = ""]
# xpath_query can be in defined short form like "Event/System[EventID=999]"
# or you can form a XML Query. Refer to the Consuming Events article:
# https://docs.microsoft.com/en-us/windows/win32/wes/consuming-events
# XML query is the recommended form, because it is most flexible
# You can create or debug XML Query by creating Custom View in Windows Event Viewer
# and then copying resulting XML here
[xpath_query: <string> | default = "*"]
# Sets the bookmark location on the filesystem.
# The bookmark contains the current position of the target in XML.
# When restarting or rolling out Promtail, the target will continue to scrape events where it left off based on the bookmark position.
# The position is updated after each entry processed.
[bookmark_path: <string> | default = ""]
# PollInterval is the interval at which we're looking if new events are available. By default the target will check every 3seconds.
[poll_interval: <duration> | default = 3s]
# Allows to exclude the xml event data.
[exclude_event_data: <bool> | default = false]
# Allows to exclude the user data of each windows event.
[exclude_user_data: <bool> | default = false]
# Label map to add to every log line read from the windows event log
labels:
[ <labelname>: <labelvalue> ... ]
# If Promtail should pass on the timestamp from the incoming log or not.
# When false Promtail will assign the current timestamp to the log when it was processed
[use_incoming_timestamp: <bool> | default = false]
kafka
The kafka
block configures Promtail to scrape logs from Kafka using a group consumer.
The brokers
should list available brokers to communicate with the Kafka cluster. Use multiple brokers when you want to increase availability.
The topics
is the list of topics Promtail will subscribe to. If a topic starts with ^
then a regular expression (RE2) is used to match topics.
For instance ^promtail-.*
will match the topic promtail-dev
and promtail-prod
. Topics are refreshed every 30 seconds, so if a new topic matches, it will be automatically added without requiring a Promtail restart.
The group_id
defined the unique consumer group id to use for consuming logs. Each log record published to a topic is delivered to one consumer instance within each subscribing consumer group.
- If all promtail instances have the same consumer group, then the records will effectively be load balanced over the promtail instances.
- If all promtail instances have different consumer groups, then each record will be broadcast to all promtail instances.
The group_id
is useful if you want to effectively send the data to multiple loki instances and/or other sinks.
The assignor
configuration allow you to select the rebalancing strategy to use for the consumer group.
Rebalancing is the process where a group of consumer instances (belonging to the same group) co-ordinate to own a mutually exclusive set of partitions of topics that the group is subscribed to.
range
the default, assigns partitions as ranges to consumer group members.sticky
assigns partitions to members with an attempt to preserve earlier assignmentsroundrobin
assigns partitions to members in alternating order.
The version
allows to select the kafka version required to connect to the cluster.(default to 2.2.1
)
By default, timestamps are assigned by Promtail when the message is read, if you want to keep the actual message timestamp from Kafka you can set the use_incoming_timestamp
to true.
# The list of brokers to connect to kafka (Required).
[brokers: <strings> | default = [""]]
# The list of Kafka topics to consume (Required).
[topics: <strings> | default = [""]]
# The Kafka consumer group id.
[group_id: <string> | default = "promtail"]
# The consumer group rebalancing strategy to use. (e.g `sticky`, `roundrobin` or `range`)
[assignor: <string> | default = "range"]
# Kafka version to connect to.
[version: <string> | default = "2.2.1"]
# Optional authentication configuration with Kafka brokers
authentication:
# Type is authentication type. Supported values [none, ssl, sasl]
[type: <string> | default = "none"]
# TLS configuration for authentication and encryption. It is used only when authentication type is ssl.
tls_config:
[ <tls_config> ]
# SASL configuration for authentication. It is used only when authentication type is sasl.
sasl_config:
# SASL mechanism. Supported values [PLAIN, SCRAM-SHA-256, SCRAM-SHA-512]
[mechanism: <string> | default = "PLAIN"]
# The user name to use for SASL authentication
[user: <string>]
# The password to use for SASL authentication
[password: <secret>]
# If true, SASL authentication is executed over TLS
[use_tls: <boolean> | default = false]
# The CA file to use to verify the server
[ca_file: <string>]
# 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]
# Label map to add to every log line read from kafka
labels:
[ <labelname>: <labelvalue> ... ]
# If Promtail should pass on the timestamp from the incoming log or not.
# When false Promtail will assign the current timestamp to the log when it was processed
[use_incoming_timestamp: <bool> | default = false]
Available Labels:
The list of labels below are discovered when consuming kafka:
__meta_kafka_topic
: The current topic for where the message has been read.__meta_kafka_partition
: The partition id where the message has been read.__meta_kafka_member_id
: The consumer group member id.__meta_kafka_group_id
: The consumer group id.__meta_kafka_message_key
: The message key. If it is empty, this value will be ’none'.
To keep discovered labels to your logs use the relabel_configs section.
GELF
The gelf
block configures a GELF UDP listener allowing users to push
logs to Promtail with the GELF protocol.
Currently only UDP is supported, please submit a feature request if you’re interested into TCP support.
GELF messages can be sent uncompressed or compressed with either GZIP or ZLIB.
Each GELF message received will be encoded in JSON as the log line. For example:
{"version":"1.1","host":"example.org","short_message":"A short message","timestamp":1231231123,"level":5,"_some_extra":"extra"}
You can leverage pipeline stages with the GELF target, if for example, you want to parse the log line and extract more labels or change the log line format.
# UDP address to listen on. Has the format of "host:port". Default to 0.0.0.0:12201
listen_address: <string>
# Label map to add to every log message.
labels:
[ <labelname>: <labelvalue> ... ]
# Whether Promtail should pass on the timestamp from the incoming gelf message.
# When false, or if no timestamp is present on the gelf message, Promtail will assign the current timestamp to the log when it was processed.
# Default is false
use_incoming_timestamp: <bool>
Available Labels:
__gelf_message_level
: The GELF level as string.__gelf_message_host
: The host sending the GELF message.__gelf_message_version
: The GELF level message version set by the client.__gelf_message_facility
: The GELF facility.
To keep discovered labels to your logs use the relabel_configs section.
Cloudflare
The cloudflare
block configures Promtail to pull logs from the Cloudflare
Logpull API.
These logs contain data related to the connecting client, the request path through the Cloudflare network, and the response from the origin web server. This data is useful for enriching existing logs on an origin server.
# The Cloudflare API token to use. (Required)
# You can create a new token by visiting your [Cloudflare profile](https://dash.cloudflare.com/profile/api-tokens).
api_token: <string>
# The Cloudflare zone id to pull logs for. (Required)
zone_id: <string>
# The time range to pull logs for.
[pull_range: <duration> | default = 1m]
# The quantity of workers that will pull logs.
[workers: <int> | default = 3]
# The type list of fields to fetch for logs.
# Supported values: default, minimal, extended, all.
[fields_type: <string> | default = default]
# Label map to add to every log message.
labels:
[ <labelname>: <labelvalue> ... ]
By default Promtail fetches logs with the default set of fields. Here are the different set of fields type available and the fields they include :
default
includes"ClientIP", "ClientRequestHost", "ClientRequestMethod", "ClientRequestURI", "EdgeEndTimestamp", "EdgeResponseBytes", "EdgeRequestHost", "EdgeResponseStatus", "EdgeStartTimestamp", "RayID"
minimal
includes alldefault
fields and adds"ZoneID", "ClientSSLProtocol", "ClientRequestProtocol", "ClientRequestPath", "ClientRequestUserAgent", "ClientRequestReferer", "EdgeColoCode", "ClientCountry", "CacheCacheStatus", "CacheResponseStatus", "EdgeResponseContentType
extended
includes allminimal
fields and adds"ClientSSLCipher", "ClientASN", "ClientIPClass", "CacheResponseBytes", "EdgePathingOp", "EdgePathingSrc", "EdgePathingStatus", "ParentRayID", "WorkerCPUTime", "WorkerStatus", "WorkerSubrequest", "WorkerSubrequestCount", "OriginIP", "OriginResponseStatus", "OriginSSLProtocol", "OriginResponseHTTPExpires", "OriginResponseHTTPLastModified"
all
includes allextended
fields and adds"ClientRequestBytes", "ClientSrcPort", "ClientXRequestedWith", "CacheTieredFill", "EdgeResponseCompressionRatio", "EdgeServerIP", "FirewallMatchesSources", "FirewallMatchesActions", "FirewallMatchesRuleIDs", "OriginResponseBytes", "OriginResponseTime", "ClientDeviceType", "WAFFlags", "WAFMatchedVar", "EdgeColoID"
To learn more about each field and its value, refer to the Cloudflare documentation.
Promtail saves the last successfully-fetched timestamp in the position file. If a position is found in the file for a given zone ID, Promtail will restart pulling logs from that position. When no position is found, Promtail will start pulling logs from the current time.
Promtail fetches logs using multiple workers (configurable via workers
) which request the last available pull range
(configured via pull_range
) repeatedly. Verify the last timestamp fetched by Promtail using the cloudflare_target_last_requested_end_timestamp
metric.
It is possible for Promtail to fall behind due to having too many log lines to process for each pull.
Adding more workers, decreasing the pull range, or decreasing the quantity of fields fetched can mitigate this performance issue.
All Cloudflare logs are in JSON. Here is an example:
{
"CacheCacheStatus": "miss",
"CacheResponseBytes": 8377,
"CacheResponseStatus": 200,
"CacheTieredFill": false,
"ClientASN": 786,
"ClientCountry": "gb",
"ClientDeviceType": "desktop",
"ClientIP": "100.100.5.5",
"ClientIPClass": "noRecord",
"ClientRequestBytes": 2691,
"ClientRequestHost": "www.foo.com",
"ClientRequestMethod": "GET",
"ClientRequestPath": "/comments/foo/",
"ClientRequestProtocol": "HTTP/1.0",
"ClientRequestReferer": "https://www.foo.com/foo/168855/?offset=8625",
"ClientRequestURI": "/foo/15248108/",
"ClientRequestUserAgent": "some bot",
"ClientSSLCipher": "ECDHE-ECDSA-AES128-GCM-SHA256",
"ClientSSLProtocol": "TLSv1.2",
"ClientSrcPort": 39816,
"ClientXRequestedWith": "",
"EdgeColoCode": "MAN",
"EdgeColoID": 341,
"EdgeEndTimestamp": 1637336610671000000,
"EdgePathingOp": "wl",
"EdgePathingSrc": "macro",
"EdgePathingStatus": "nr",
"EdgeRateLimitAction": "",
"EdgeRateLimitID": 0,
"EdgeRequestHost": "www.foo.com",
"EdgeResponseBytes": 14878,
"EdgeResponseCompressionRatio": 1,
"EdgeResponseContentType": "text/html",
"EdgeResponseStatus": 200,
"EdgeServerIP": "8.8.8.8",
"EdgeStartTimestamp": 1637336610517000000,
"FirewallMatchesActions": [],
"FirewallMatchesRuleIDs": [],
"FirewallMatchesSources": [],
"OriginIP": "8.8.8.8",
"OriginResponseBytes": 0,
"OriginResponseHTTPExpires": "",
"OriginResponseHTTPLastModified": "",
"OriginResponseStatus": 200,
"OriginResponseTime": 123000000,
"OriginSSLProtocol": "TLSv1.2",
"ParentRayID": "00",
"RayID": "6b0a...",
"SecurityLevel": "med",
"WAFAction": "unknown",
"WAFFlags": "0",
"WAFMatchedVar": "",
"WAFProfile": "unknown",
"WAFRuleID": "",
"WAFRuleMessage": "",
"WorkerCPUTime": 0,
"WorkerStatus": "unknown",
"WorkerSubrequest": false,
"WorkerSubrequestCount": 0,
"ZoneID": 1234
}
You can leverage pipeline stages if, for example, you want to parse the JSON log line and extract more labels or change the log line format.
relabel_configs
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.
static_configs
A static_configs
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.
# This is required by the prometheus service discovery code but doesn't
# really apply to Promtail which can ONLY look at files on the local machine
# As such it should only have the value of localhost, OR it can be excluded
# entirely and a default value of localhost will be applied by Promtail.
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_sd_config
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_config
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:
node
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.
service
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.
pod
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.
endpoints
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.
ingress
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.
consul_sd_config
Consul SD configurations allow retrieving scrape targets from the Consul Catalog API. When using the Catalog API, each running Promtail will get a list of all services known to the whole consul cluster when discovering new targets.
The following meta labels are available on targets during relabeling:
__meta_consul_address
: the address of the target__meta_consul_dc
: the datacenter name for the target__meta_consul_health
: the health status of the service__meta_consul_metadata_<key>
: each node metadata key value of the target__meta_consul_node
: the node name defined for the target__meta_consul_service_address
: the service address of the target__meta_consul_service_id
: the service ID of the target__meta_consul_service_metadata_<key>
: each service metadata key value of the target__meta_consul_service_port
: the service port of the target__meta_consul_service
: the name of the service the target belongs to__meta_consul_tagged_address_<key>
: each node tagged address key value of the target__meta_consul_tags
: the list of tags of the target joined by the tag separator
# The information to access the Consul Catalog API. It is to be defined
# as the Consul documentation requires.
[ server: <host> | default = "localhost:8500" ]
[ token: <secret> ]
[ datacenter: <string> ]
[ scheme: <string> | default = "http" ]
[ username: <string> ]
[ password: <secret> ]
tls_config:
[ <tls_config> ]
# A list of services for which targets are retrieved. If omitted, all services
# are scraped.
services:
[ - <string> ]
# See https://www.consul.io/api/catalog.html#list-nodes-for-service to know more
# about the possible filters that can be used.
# An optional list of tags used to filter nodes for a given service. Services must contain all tags in the list.
tags:
[ - <string> ]
# Node metadata key/value pairs to filter nodes for a given service.
[ node_meta:
[ <string>: <string> ... ] ]
# The string by which Consul tags are joined into the tag label.
[ tag_separator: <string> | default = , ]
# Allow stale Consul results (see https://www.consul.io/api/features/consistency.html). Will reduce load on Consul.
[ allow_stale: <boolean> | default = true ]
# The time after which the provided names are refreshed.
# On large setup it might be a good idea to increase this value because the catalog will change all the time.
[ refresh_interval: <duration> | default = 30s ]
Note that the IP number and port used to scrape the targets is assembled as
<__meta_consul_address>:<__meta_consul_service_port>
. However, in some
Consul setups, the relevant address is in __meta_consul_service_address
.
In those cases, you can use the relabel
feature to replace the special __address__
label.
The relabeling phase is the preferred and more powerful way to filter services or nodes for a service based on arbitrary labels. For users with thousands of services it can be more efficient to use the Consul API directly which has basic support for filtering nodes (currently by node metadata and a single tag).
consulagent_sd_config
Consul Agent SD configurations allow retrieving scrape targets from Consul’s Agent API. When using the Agent API, each running Promtail will only get services registered with the local agent running on the same host when discovering new targets. This is suitable for very large Consul clusters for which using the Catalog API would be too slow or resource intensive.
The following meta labels are available on targets during relabeling:
__meta_consulagent_address
: the address of the target__meta_consulagent_dc
: the datacenter name for the target__meta_consulagent_health
: the health status of the service__meta_consulagent_metadata_<key>
: each node metadata key value of the target__meta_consulagent_node
: the node name defined for the target__meta_consulagent_service_address
: the service address of the target__meta_consulagent_service_id
: the service ID of the target__meta_consulagent_service_metadata_<key>
: each service metadata key value of the target__meta_consulagent_service_port
: the service port of the target__meta_consulagent_service
: the name of the service the target belongs to__meta_consulagent_tagged_address_<key>
: each node tagged address key value of the target__meta_consulagent_tags
: the list of tags of the target joined by the tag separator
# The information to access the Consul Agent API. It is to be defined
# as the Consul documentation requires.
[ server: <host> | default = "localhost:8500" ]
[ token: <secret> ]
[ datacenter: <string> ]
[ scheme: <string> | default = "http" ]
[ username: <string> ]
[ password: <secret> ]
tls_config:
[ <tls_config> ]
# A list of services for which targets are retrieved. If omitted, all services
# are scraped.
services:
[ - <string> ]
# See https://www.consul.io/api-docs/agent/service#filtering to know more
# about the possible filters that can be used.
# An optional list of tags used to filter nodes for a given service. Services must contain all tags in the list.
tags:
[ - <string> ]
# Node metadata key/value pairs to filter nodes for a given service.
[ node_meta:
[ <string>: <string> ... ] ]
# The string by which Consul tags are joined into the tag label.
[ tag_separator: <string> | default = , ]
Note that the IP address and port number used to scrape the targets is assembled as
<__meta_consul_address>:<__meta_consul_service_port>
. However, in some
Consul setups, the relevant address is in __meta_consul_service_address
.
In those cases, you can use the relabel
feature to replace the special __address__
label.
The relabeling phase is the preferred and more powerful way to filter services or nodes for a service based on arbitrary labels. For users with thousands of services it can be more efficient to use the Consul API directly which has basic support for filtering nodes (currently by node metadata and a single tag).
docker_sd_config
Docker service discovery allows retrieving targets from a Docker daemon. It will only watch containers of the Docker daemon referenced with the host parameter. Docker service discovery should run on each node in a distributed setup. The containers must run with either the json-file or journald logging driver.
Please note that the discovery will not pick up finished containers. That means Promtail will not scrape the remaining logs from finished containers after a restart.
The configuration is inherited from Prometheus’ Docker service discovery.
# Address of the Docker daemon. Use unix:///var/run/docker.sock for a local setup.
host: <string>
# Optional proxy URL.
[ proxy_url: <string> ]
# TLS configuration.
tls_config:
[ <tls_config> ]
# The port to scrape metrics from, when `role` is nodes, and for discovered
# tasks and services that don't have published ports.
[ port: <int> | default = 80 ]
# The host to use if the container is in host networking mode.
[ host_networking_host: <string> | default = "localhost" ]
# Optional filters to limit the discovery process to a subset of available
# resources.
# The available filters are listed in the Docker documentation:
# Containers: https://docs.docker.com/engine/api/v1.41/#operation/ContainerList
[ filters:
[ - name: <string>
values: <string>, [...] ]
]
# The time after which the containers are refreshed.
[ refresh_interval: <duration> | default = 60s ]
# Authentication information used by Promtail to authenticate itself to the
# Docker daemon.
# Note that `basic_auth` and `authorization` 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 `Authorization` header configuration.
authorization:
# Sets the authentication type.
[ type: <string> | default: Bearer ]
# Sets the credentials. It is mutually exclusive with
# `credentials_file`.
[ credentials: <secret> ]
# Sets the credentials to the credentials read from the configured file.
# It is mutually exclusive with `credentials`.
[ credentials_file: <filename> ]
# Optional OAuth 2.0 configuration.
# Cannot be used at the same time as basic_auth or authorization.
oauth2:
[ <oauth2> ]
# Configure whether HTTP requests follow HTTP 3xx redirects.
[ follow_redirects: <bool> | default = true ]
Available meta labels:
__meta_docker_container_id
: the ID of the container__meta_docker_container_name
: the name of the container__meta_docker_container_network_mode
: the network mode of the container__meta_docker_container_label_<labelname>
: each label of the container__meta_docker_container_log_stream
: the log stream typestdout
orstderr
__meta_docker_network_id
: the ID of the network__meta_docker_network_name
: the name of the network__meta_docker_network_ingress
: whether the network is ingress__meta_docker_network_internal
: whether the network is internal__meta_docker_network_label_<labelname>
: each label of the network__meta_docker_network_scope
: the scope of the network__meta_docker_network_ip
: the IP of the container in this network__meta_docker_port_private
: the port on the container__meta_docker_port_public
: the external port if a port-mapping exists__meta_docker_port_public_ip
: the public IP if a port-mapping exists
These labels can be used during relabeling. For instance, the following configuration scrapes the container named flog
and removes the leading slash (/
) from the container name.
scrape_configs:
- job_name: flog_scrape
docker_sd_configs:
- host: unix:///var/run/docker.sock
refresh_interval: 5s
filters:
- name: name
values: [flog]
relabel_configs:
- source_labels: ['__meta_docker_container_name']
regex: '/(.*)'
target_label: 'container'
target_config
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"
Example Docker Config
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.
Example Static Config
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
If you are rotating logs, be careful when using a wildcard pattern like *.log
, and make sure it doesn’t match the rotated log file. For example, if you move your logs from server.log
to server.01-01-1970.log
in the same directory every night, a static config with a wildcard search pattern like *.log
will pick up that new file and read it, effectively causing the entire days logs to be re-ingested.
Example Static Config without targets
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:
- 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
Example Journal Config
This example reads entries from a systemd journal:
server:
http_listen_port: 9080
grpc_listen_port: 0
positions:
filename: /tmp/positions.yaml
scrape_configs:
- job_name: journal
journal:
max_age: 12h
labels:
job: systemd-journal
relabel_configs:
- source_labels: ['__journal__systemd_unit']
target_label: 'unit'
Example Syslog Config
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
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'
Example Push Config
The example starts Promtail as a Push receiver and will accept logs from other Promtail instances or the Docker Logging Dirver:
server:
http_listen_port: 9080
grpc_listen_port: 0
positions:
filename: /tmp/positions.yaml
scrape_configs:
- job_name: push1
loki_push_api:
server:
http_listen_port: 3500
grpc_listen_port: 3600
labels:
pushserver: push1
Please note the job_name
must be provided and must be unique between multiple loki_push_api
scrape_configs, it will be used to register metrics.
A new server instance is created so the http_listen_port
and grpc_listen_port
must be different from the Promtail server
config section (unless it’s disabled)
You can set grpc_listen_port
to 0
to have a random port assigned if not using httpgrpc.