telegraf/plugins/outputs/kafka/README.md

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# Kafka Output Plugin
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This plugin writes to a [Kafka Broker](http://kafka.apache.org/07/quickstart.html) acting a Kafka Producer.
### Configuration:
```toml
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[[outputs.kafka]]
## URLs of kafka brokers
brokers = ["localhost:9092"]
## Kafka topic for producer messages
topic = "telegraf"
## Optional Client id
# client_id = "Telegraf"
## Set the minimal supported Kafka version. Setting this enables the use of new
## Kafka features and APIs. Of particular interested, lz4 compression
## requires at least version 0.10.0.0.
## ex: version = "1.1.0"
# version = ""
## Optional topic suffix configuration.
## If the section is omitted, no suffix is used.
## Following topic suffix methods are supported:
## measurement - suffix equals to separator + measurement's name
## tags - suffix equals to separator + specified tags' values
## interleaved with separator
## Suffix equals to "_" + measurement name
# [outputs.kafka.topic_suffix]
# method = "measurement"
# separator = "_"
## Suffix equals to "__" + measurement's "foo" tag value.
## If there's no such a tag, suffix equals to an empty string
# [outputs.kafka.topic_suffix]
# method = "tags"
# keys = ["foo"]
# separator = "__"
## Suffix equals to "_" + measurement's "foo" and "bar"
## tag values, separated by "_". If there is no such tags,
## their values treated as empty strings.
# [outputs.kafka.topic_suffix]
# method = "tags"
# keys = ["foo", "bar"]
# separator = "_"
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## Telegraf tag to use as a routing key
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## ie, if this tag exists, its value will be used as the routing key
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routing_tag = "host"
## Static routing key. Used when no routing_tag is set or as a fallback
## when the tag specified in routing tag is not found. If set to "random",
## a random value will be generated for each message.
## ex: routing_key = "random"
## routing_key = "telegraf"
# routing_key = ""
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## CompressionCodec represents the various compression codecs recognized by
## Kafka in messages.
## 0 : No compression
## 1 : Gzip compression
## 2 : Snappy compression
## 3 : LZ4 compression
# compression_codec = 0
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## RequiredAcks is used in Produce Requests to tell the broker how many
## replica acknowledgements it must see before responding
## 0 : the producer never waits for an acknowledgement from the broker.
## This option provides the lowest latency but the weakest durability
## guarantees (some data will be lost when a server fails).
## 1 : the producer gets an acknowledgement after the leader replica has
## received the data. This option provides better durability as the
## client waits until the server acknowledges the request as successful
## (only messages that were written to the now-dead leader but not yet
## replicated will be lost).
## -1: the producer gets an acknowledgement after all in-sync replicas have
## received the data. This option provides the best durability, we
## guarantee that no messages will be lost as long as at least one in
## sync replica remains.
# required_acks = -1
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## The maximum number of times to retry sending a metric before failing
## until the next flush.
# max_retry = 3
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## Optional TLS Config
# tls_ca = "/etc/telegraf/ca.pem"
# tls_cert = "/etc/telegraf/cert.pem"
# tls_key = "/etc/telegraf/key.pem"
## Use TLS but skip chain & host verification
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# insecure_skip_verify = false
## Optional SASL Config
# sasl_username = "kafka"
# sasl_password = "secret"
## Data format to output.
## Each data format has its own unique set of configuration options, read
## more about them here:
## https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_OUTPUT.md
# data_format = "influx"
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```
#### `max_retry`
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This option controls the number of retries before a failure notification is
displayed for each message when no acknowledgement is received from the
broker. When the setting is greater than `0`, message latency can be reduced,
duplicate messages can occur in cases of transient errors, and broker loads
can increase during downtime.
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The option is similar to the
[retries](https://kafka.apache.org/documentation/#producerconfigs) Producer
option in the Java Kafka Producer.