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Generic command line non-JVM Apache Kafka producer and consumer
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Copyright (c) 2014-2019 Magnus Edenhill

kafkacat is a generic non-JVM producer and consumer for Apache Kafka >=0.8, think of it as a netcat for Kafka.

In producer mode kafkacat reads messages from stdin, delimited with a configurable delimiter (-D, defaults to newline), and produces them to the provided Kafka cluster (-b), topic (-t) and partition (-p).

In consumer mode kafkacat reads messages from a topic and partition and prints them to stdout using the configured message delimiter.

There's also support for the Kafka >=0.9 high-level balanced consumer, use the -G <group> switch and provide a list of topics to join the group.

kafkacat also features a Metadata list (-L) mode to display the current state of the Kafka cluster and its topics and partitions.

kafkacat is fast and lightweight; statically linked it is no more than 150Kb.


On recent enough Debian systems:

apt-get install kafkacat

And on Mac OS X with homebrew installed:

brew install kafkacat

Otherwise follow directions below.


On Ubuntu or Debian: sudo apt-get install librdkafka-dev libyajl-dev


./configure <usual-configure-options>
sudo make install

Quick build

The build script will download and build the required dependencies, providing a quick and easy means of building kafkacat. Internet connectivity and wget/curl is required by this script. The resulting kafkacat binary will be linked statically to avoid runtime dependencies. NOTE: Requires curl and cmake (for yajl) to be installed.



Any librdkafka configuration property can be set on the command line using -X property=value, or in a configuration file specified by -F <config-file>.

If no configuration file was specified with -F .. on the command line, kafkacat will try the $KAFKACAT_CONFIG environment variable, and then the default configuration file ~/.config/kafkacat.conf.

Configuration files are optional.


High-level balanced KafkaConsumer: subscribe to topic1 and topic2 (requires broker >=0.9.0 and librdkafka version >=0.9.1)

$ kafkacat -b mybroker -G mygroup topic1 topic2

Read messages from stdin, produce to 'syslog' topic with snappy compression

$ tail -f /var/log/syslog | kafkacat -b mybroker -t syslog -z snappy

Read messages from Kafka 'syslog' topic, print to stdout

$ kafkacat -b mybroker -t syslog

Produce messages from file (one file is one message)

$ kafkacat -P -b mybroker -t filedrop -p 0 myfile1.bin /etc/motd thirdfile.tgz

Read the last 2000 messages from 'syslog' topic, then exit

$ kafkacat -C -b mybroker -t syslog -p 0 -o -2000 -e

Consume from all partitions from 'syslog' topic

$ kafkacat -C -b mybroker -t syslog

Output consumed messages in JSON envelope:

$ kafkacat -b mybroker -t syslog -J

Output consumed messages according to format string:

$ kafkacat -b mybroker -t syslog -f 'Topic %t[%p], offset: %o, key: %k, payload: %S bytes: %s\n'

Read the last 100 messages from topic 'syslog' with librdkafka configuration parameter 'broker.version.fallback' set to '' :

$ kafkacat -C -b mybroker -X broker.version.fallback= -t syslog -p 0 -o -100 -e

Produce a tombstone (a "delete" for compacted topics) for key "abc" by providing an empty message value which -Z interpretes as NULL:

$ echo "abc:" | kafkacat -b mybroker -t mytopic -Z -K:

Produce with headers:

$ echo "hello there" | kafkacat -b mybroker -H "header1=header value" -H "nullheader" -H "emptyheader=" -H "header1=duplicateIsOk"

Print headers in consumer:

$ kafkacat -b mybroker -C -t mytopic -f 'Headers: %h: Message value: %s\n'

Enable the idempotent producer, providing exactly-once and strict-ordering producer guarantees:

$ kafkacat -b mybroker -X enable.idempotence=true -P -t mytopic ....

Metadata listing:

$ kafkacat -L -b mybroker
Metadata for all topics (from broker 1: mybroker:9092/1):
 3 brokers:
  broker 1 at mybroker:9092
  broker 2 at mybrokertoo:9092
  broker 3 at thirdbroker:9092
 16 topics:
  topic "syslog" with 3 partitions:
    partition 0, leader 3, replicas: 1,2,3, isrs: 1,2,3
    partition 1, leader 1, replicas: 1,2,3, isrs: 1,2,3
    partition 2, leader 1, replicas: 1,2, isrs: 1,2
  topic "rdkafkatest1_auto_49f744a4327b1b1e" with 2 partitions:
    partition 0, leader 3, replicas: 3, isrs: 3
    partition 1, leader 1, replicas: 1, isrs: 1
  topic "rdkafkatest1_auto_e02f58f2c581cba" with 2 partitions:
    partition 0, leader 3, replicas: 3, isrs: 3
    partition 1, leader 1, replicas: 1, isrs: 1

JSON metadata listing

$ kafkacat -b mybroker -L -J

Pretty-printed JSON metadata listing

$ kafkacat -b mybroker -L -J | jq .

Query offset(s) by timestamp(s)

$ kafkacat -b mybroker -Q -t mytopic:3:2389238523 -t mytopic2:0:18921841

Running in Docker

You can find an image for kafkacat on Docker Hub.

If you are connecting to Kafka brokers also running on Docker you should specify the network name as part of the docker run command using the --network parameter. For more details of networking with Kafka and Docker see this post.

Here are two short examples of using kafkacat from Docker. See the Docker Hub listing and kafkacat docs for more details:

  • Send messages using here doc:

    docker run --interactive --rm \
        confluentinc/cp-kafkacat \
        kafkacat -b kafka-broker:9092 \
                -t test \
                -K: \
                -P <<EOF
    1:{"order_id":1,"order_ts":1534772501276,"total_amount":10.50,"customer_name":"Bob Smith"}
    2:{"order_id":2,"order_ts":1534772605276,"total_amount":3.32,"customer_name":"Sarah Black"}
    3:{"order_id":3,"order_ts":1534772742276,"total_amount":21.00,"customer_name":"Emma Turner"}
  • Consume messages:

    docker run --tty --interactive --rm \
           confluentinc/cp-kafkacat \
           kafkacat -b kafka-broker:9092 \ 
           -C \
           -f '\nKey (%K bytes): %k\t\nValue (%S bytes): %s\n\Partition: %p\tOffset: %o\n--\n' \
           -t test
    Key (1 bytes): 1
    Value (88 bytes): {"order_id":1,"order_ts":1534772501276,"total_amount":10.50,"customer_name":"Bob Smith"}
    Partition: 0    Offset: 0
    Key (1 bytes): 2
    Value (89 bytes): {"order_id":2,"order_ts":1534772605276,"total_amount":3.32,"customer_name":"Sarah Black"}
    Partition: 0    Offset: 1
    Key (1 bytes): 3
    Value (90 bytes): {"order_id":3,"order_ts":1534772742276,"total_amount":21.00,"customer_name":"Emma Turner"}
    Partition: 0    Offset: 2
    % Reached end of topic test [0] at offset 3
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