telegraf/plugins/inputs/kafka_consumer/README.md

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# Kafka Consumer Input Plugin
The [Kafka][kafka] consumer plugin reads from Kafka
and creates metrics using one of the supported [input data formats][].
For old kafka version (< 0.8), please use the [kafka_consumer_legacy][] input plugin
and use the old zookeeper connection method.
### Configuration
```toml
[[inputs.kafka_consumer]]
## Kafka brokers.
brokers = ["localhost:9092"]
## Topics to consume.
topics = ["telegraf"]
## When set this tag will be added to all metrics with the topic as the value.
# topic_tag = ""
## Optional Client id
# client_id = "Telegraf"
## Set the minimal supported Kafka version. Setting this enables the use of new
## Kafka features and APIs. Must be 0.10.2.0 or greater.
## ex: version = "1.1.0"
# version = ""
## 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
# insecure_skip_verify = false
## Optional SASL Config
# sasl_username = "kafka"
# sasl_password = "secret"
## Name of the consumer group.
# consumer_group = "telegraf_metrics_consumers"
## Initial offset position; one of "oldest" or "newest".
# offset = "oldest"
## Consumer group partition assignment strategy; one of "range", "roundrobin" or "sticky".
# balance_strategy = "range"
## Maximum length of a message to consume, in bytes (default 0/unlimited);
## larger messages are dropped
max_message_len = 1000000
## Maximum messages to read from the broker that have not been written by an
## output. For best throughput set based on the number of metrics within
## each message and the size of the output's metric_batch_size.
##
## For example, if each message from the queue contains 10 metrics and the
## output metric_batch_size is 1000, setting this to 100 will ensure that a
## full batch is collected and the write is triggered immediately without
## waiting until the next flush_interval.
# max_undelivered_messages = 1000
## Data format to consume.
## 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_INPUT.md
data_format = "influx"
```
[kafka]: https://kafka.apache.org
[kafka_consumer_legacy]: /plugins/inputs/kafka_consumer_legacy/README.md
[input data formats]: /docs/DATA_FORMATS_INPUT.md