Configure the Kafka output
editConfigure the Kafka output
editThe Kafka output sends the events to Apache Kafka.
Example configuration:
output.kafka: # initial brokers for reading cluster metadata hosts: ["kafka1:9092", "kafka2:9092", "kafka3:9092"] # message topic selection + partitioning topic: '%{[fields.log_topic]}' partition.round_robin: reachable_only: false required_acks: 1 compression: gzip max_message_bytes: 1000000
Events bigger than max_message_bytes
will be dropped. To avoid this problem, make sure Metricbeat does not generate events bigger than max_message_bytes
.
Compatibility
editThis output works with all Kafka versions in between 0.11 and 2.2.2. Older versions might work as well, but are not supported.
Configuration options
editYou can specify the following options in the kafka
section of the metricbeat.yml
config file:
enabled
editThe enabled
config is a boolean setting to enable or disable the output. If set
to false, the output is disabled.
The default value is true.
hosts
editThe list of Kafka broker addresses from where to fetch the cluster metadata. The cluster metadata contain the actual Kafka brokers events are published to.
version
editKafka version metricbeat is assumed to run against. Defaults to 1.0.0.
Event timestamps will be added, if version 0.10.0.0+ is enabled.
Valid values are all kafka releases in between 0.8.2.0
and 2.0.0
.
See Compatibility for information on supported versions.
username
editThe username for connecting to Kafka. If username is configured, the password must be configured as well. Only SASL/PLAIN is supported.
password
editThe password for connecting to Kafka.
topic
editThe Kafka topic used for produced events.
You can set the topic dynamically by using a format string to access any
event field. For example, this configuration uses a custom field,
fields.log_topic
, to set the topic for each event:
topic: '%{[fields.log_topic]}'
To learn how to add custom fields to events, see the
fields
option.
See the topics
setting for other ways to set the
topic dynamically.
topics
editAn array of topic selector rules. Each rule specifies the topic
to use for
events that match the rule. During publishing, Metricbeat sets the topic
for each event based on the first matching rule in the array. Rules
can contain conditionals, format string-based fields, and name mappings. If the
topics
setting is missing or no rule matches, the
topic
field is used.
Rule settings:
-
topic
-
The topic format string to use. If this string contains field
references, such as
%{[fields.name]}
, the fields must exist, or the rule fails. -
mappings
-
A dictionary that takes the value returned by
topic
and maps it to a new name. -
default
-
The default string value to use if
mappings
does not find a match. -
when
- A condition that must succeed in order to execute the current rule. All the conditions supported by processors are also supported here.
The following example sets the topic based on whether the message field contains the specified string:
output.kafka: hosts: ["localhost:9092"] topic: "logs-%{[agent.version]}" topics: - topic: "critical-%{[agent.version]}" when.contains: message: "CRITICAL" - topic: "error-%{[agent.version]}" when.contains: message: "ERR"
This configuration results in topics named critical-7.9.3
,
error-7.9.3
, and logs-7.9.3
.
key
editOptional formatted string specifying the Kafka event key. If configured, the event key can be extracted from the event using a format string.
See the Kafka documentation for the implications of a particular choice of key; by default, the key is chosen by the Kafka cluster.
partition
editKafka output broker event partitioning strategy. Must be one of random
,
round_robin
, or hash
. By default the hash
partitioner is used.
random.group_events
: Sets the number of events to be published to the same
partition, before the partitioner selects a new partition by random. The
default value is 1 meaning after each event a new partition is picked randomly.
round_robin.group_events
: Sets the number of events to be published to the
same partition, before the partitioner selects the next partition. The default
value is 1 meaning after each event the next partition will be selected.
hash.hash
: List of fields used to compute the partitioning hash value from.
If no field is configured, the events key
value will be used.
hash.random
: Randomly distribute events if no hash or key value can be computed.
All partitioners will try to publish events to all partitions by default. If a
partition’s leader becomes unreachable for the beat, the output might block. All
partitioners support setting reachable_only
to overwrite this
behavior. If reachable_only
is set to true
, events will be published to
available partitions only.
Publishing to a subset of available partitions potentially increases resource usage because events may become unevenly distributed.
client_id
editThe configurable ClientID used for logging, debugging, and auditing purposes. The default is "beats".
worker
editThe number of concurrent load-balanced Kafka output workers.
codec
editOutput codec configuration. If the codec
section is missing, events will be json encoded.
See Change the output codec for more information.
metadata
editKafka metadata update settings. The metadata do contain information about brokers, topics, partition, and active leaders to use for publishing.
-
refresh_frequency
- Metadata refresh interval. Defaults to 10 minutes.
-
full
-
Strategy to use when fetching metadata, when this option is
true
, the client will maintain a full set of metadata for all the available topics, if the this option is set tofalse
it will only refresh the metadata for the configured topics. The default is false. -
retry.max
- Total number of metadata update retries when cluster is in middle of leader election. The default is 3.
-
retry.backoff
- Waiting time between retries during leader elections. Default is 250ms.
max_retries
editThe number of times to retry publishing an event after a publishing failure. After the specified number of retries, the events are typically dropped.
Set max_retries
to a value less than 0 to retry until all events are published.
The default is 3.
bulk_max_size
editThe maximum number of events to bulk in a single Kafka request. The default is 2048.
bulk_flush_frequency
editDuration to wait before sending bulk Kafka request. 0 is no delay. The default is 0.
timeout
editThe number of seconds to wait for responses from the Kafka brokers before timing out. The default is 30 (seconds).
broker_timeout
editThe maximum duration a broker will wait for number of required ACKs. The default is 10s.
channel_buffer_size
editPer Kafka broker number of messages buffered in output pipeline. The default is 256.
keep_alive
editThe keep-alive period for an active network connection. If 0s, keep-alives are disabled. The default is 0 seconds.
compression
editSets the output compression codec. Must be one of none
, snappy
, lz4
and gzip
. The default is gzip
.
compression_level
editSets the compression level used by gzip. Setting this value to 0 disables compression. The compression level must be in the range of 1 (best speed) to 9 (best compression).
Increasing the compression level will reduce the network usage but will increase the cpu usage.
The default value is 4.
max_message_bytes
editThe maximum permitted size of JSON-encoded messages. Bigger messages will be dropped. The default value is 1000000 (bytes). This value should be equal to or less than the broker’s message.max.bytes
.
required_acks
editThe ACK reliability level required from broker. 0=no response, 1=wait for local commit, -1=wait for all replicas to commit. The default is 1.
Note: If set to 0, no ACKs are returned by Kafka. Messages might be lost silently on error.
ssl
editConfiguration options for SSL parameters like the root CA for Kafka connections.
The Kafka host keystore should be created with the
-keyalg RSA
argument to ensure it uses a cipher supported by
Filebeat’s Kafka library.
See SSL for more information.