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Short Description
Apache Kafka is a distributed streaming platform used for building real-time applications
Full Description



What is kafka?

Apache Kafka is a distributed streaming platform used for building real-time data pipelines and
streaming apps. It is horizontally scalable, fault-tolerant, wicked fast, and runs in production in
thousands of companies. Kafka requires a connection to a Zookeeper service.

https://kafka.apache.org/

TL;DR;

Docker Compose

version: '2'

services:
  zookeeper:
    image: 'bitnami/zookeeper:latest'
    ports:
      - '2181:2181'
  kafka:
    image: 'bitnami/kafka:0'
    ports:
      - '9092:9092'
    environment:
      - KAFKA_ZOOKEEPER_CONNECT=zookeeper:2181

Kubernetes

WARNING: This is a beta configuration, currently unsupported.

Get the raw URL pointing to the kubernetes.yml manifest and use kubectl to create the resources on your Kubernetes cluster like so:

$ kubectl create -f https://raw.githubusercontent.com/bitnami/bitnami-docker-kafka/master/kubernetes.yml

Why use Bitnami Images?

  • Bitnami closely tracks upstream source changes and promptly publishes new versions of this image using our automated systems.
  • With Bitnami images the latest bug fixes and features are available as soon as possible.
  • Bitnami containers, virtual machines and cloud images use the same components and configuration approach - making it easy to switch between formats based on your project needs.
  • Bitnami images are built on CircleCI and automatically pushed to the Docker Hub.
  • All our images are based on minideb a minimalist Debian based container image which gives you a small base container image and the familiarity of a leading linux distribution.

Get this image

The recommended way to get the Bitnami Kafka Docker Image is to pull the prebuilt image from the Docker Hub Registry.

docker pull bitnami/kafka:latest

To use a specific version, you can pull a versioned tag. You can view the
list of available versions
in the Docker Hub Registry.

docker pull bitnami/kafka:[TAG]

If you wish, you can also build the image yourself.

docker build -t bitnami/kafka:latest https://github.com/bitnami/bitnami-docker-kafka.git

Persisting your data

If you remove the container all your data and configurations will be lost, and the next time you run the image the database will be reinitialized. To avoid this loss of data, you should mount a volume that will persist even after the container is removed.

Note!
If you have already started using your database, follow the steps on
backing up and restoring to pull the data from your running container down to your host.

The image exposes a volume at /bitnami/kafka for the Kafka data and configurations. For persistence you can mount a directory at this location from your host. If the mounted directory is empty, it will be initialized on the first run.

Using Docker Compose:

version: '2'

services:
  zookeeper:
    image: 'bitnami/zookeeper:latest'
    ports:
      - '2181:2181'
  kafka:
    image: 'bitnami/kafka:latest'
    ports:
      - '9092:9092'
    volumes:
      - /path/to/kafka-persistence:/bitnami/kafka

Connecting to other containers

Using Docker container networking, a Kafka server running inside a container can easily be accessed by your application containers.

Containers attached to the same network can communicate with each other using the container name as the hostname.

Using the Command Line

In this example, we will create a Kafka client instance that will connect to the server instance that is running on the same docker network as the client.

Step 1: Create a network

$ docker network create app-tier --driver bridge

Step 2: Launch the Zookeeper server instance

Use the --network app-tier argument to the docker run command to attach the Zookeeper container to the app-tier network.

$ docker run -d --name zookeeker-server \
    --network app-tier \
    bitnami/zookeeper:latest

Step 2: Launch the Kafka server instance

Use the --network app-tier argument to the docker run command to attach the Kafka container to the app-tier network.

$ docker run -d --name kafka-server \
    --network app-tier \
    -e KAFKA_ZOOKEEPER_CONNECT=zookeeper:2181 \
    bitnami/kafka:latest

Step 3: Launch your Kafka client instance

Finally we create a new container instance to launch the Kafka client and connect to the server created in the previous step:

$ docker run -it --rm \
    --network app-tier \
    -e KAFKA_ZOOKEEPER_CONNECT=zookeeper:2181 \
    bitnami/kafka:latest kafka-topics.sh --list  --zookeeper zookeeper-server:2181

Using Docker Compose

When not specified, Docker Compose automatically sets up a new network and attaches all deployed services to that network. However, we will explicitly define a new bridge network named app-tier. In this example we assume that you want to connect to the Kafka server from your own custom application image which is identified in the following snippet by the service name myapp.

version: '2'

networks:
  app-tier:
    driver: bridge

services:
  zookeeper:
    image: 'bitnami/zookeeper:latest'
    networks:
      - app-tier
  kafka:
    image: 'bitnami/kafka:latest'
    networks:
      - app-tier
  myapp:
    image: 'YOUR_APPLICATION_IMAGE'
    networks:
      - app-tier

IMPORTANT:

  1. Please update the YOUR_APPLICATION_IMAGE placeholder in the above snippet with your application image
  2. In your application container, use the hostname kafka to connect to the Kafka server

Launch the containers using:

$ docker-compose up -d

Configuration

The configuration can easily be setup with the Bitnami Kafka Docker image using the following environment variables:

  • ALLOW_PLAINTEXT_LISTENER: Allow to use the PLAINTEXT listener. Default: no
  • KAFKA_PORT_NUMBER: Kafka port. Default: 9092
  • KAFKA_BROKER_ID: ID of the Kafka node. Default: -1
  • KAFKA_NUM_NETWORK_THREADS: The number of threads handling network requests.
  • KAFKA_NUM_IO_THREADS: The number of threads doing disk I/O. Default: 3
  • KAFKA_SOCKET_SEND_BUFFER_BYTES: The send buffer (SO_SNDBUF) used by the socket server. Default: 102400
  • KAFKA_SOCKET_RECEIVE_BUFFER_BYTES: The receive buffer (SO_RCVBUF) used by the socket server. Default: 102400
  • KAFKA_SOCKET_REQUEST_MAX_BYTES: The maximum size of a request that the socket server will accept (protection against OOM). Default: 104857600
  • KAFKA_LOGS_DIRS: A comma separated list of directories under which to store log files. Default: /opt/bitnami/kafka/data
  • KAFKA_DELETE_TOPIC_ENABLE: Switch to enable topic deletion or not, default value is false. Default: false
  • KAFKA_LISTENERS: The address the socket server listens on. Default: PLAINTEXT://:9092
  • KAFKA_ADVERTISED_LISTENERS: Hostname and port the broker will advertise to producers and consumers. Default: PLAINTEXT://:9092
  • KAFKA_NUM_PARTITIONS: The default number of log partitions per topic. Default: 1
  • KAFKA_NUM_RECOVERY_THREADS_PER_DATA_DIR The number of threads per data directory to be used for log recovery at startup and flushing at shutdown. Default: 1
  • KAFKA_LOG_FLUSH_INTERVAL_MESSAGES: The number of messages to accept before forcing a flush of data to disk. Default: 10000
  • KAFKA_LOG_FLUSH_INTERVAL_MS: The maximum amount of time a message can sit in a log before we force a flush. Default: 1000
  • KAFKA_LOG_RETENTION_HOURS: The minimum age of a log file to be eligible for deletion due to age. Default: 168
  • KAFKA_LOG_RETENTION_BYTES: A size-based retention policy for logs. Default: 1073741824
  • KAFKA_SEGMENT_BYTES: The maximum size of a log segment file. When this size is reached a new log segment will be created. Default: 1073741824
  • KAFKA_LOG_RETENTION_CHECK_INTERVALS_MS: The interval at which log segments are checked to see if they can be deleted. Default: 300000
  • KAFKA_ZOOKEEPER_CONNECT: Comma separated host:port pairs, each corresponding to a Zookeeper Server. Default: localhost:2181
  • KAFKA_ZOOKEEPER_CONNECT_TIMEOUT_MS: Timeout in ms for connecting to zookeeper. Default: 6000
  • KAFKA_INTER_BROKER_USER: Kafka inter broker communication user. Default: admin. Default: admin
  • KAFKA_INTER_BROKER_PASSWORD: Kafka inter broker communication password. Default: bitnami
  • KAFKA_BROKER_USER: Kafka client user. Default: user
  • KAFKA_BROKER_PASSWORD: Kafka client user password. Default: bitnami
  • KAFKA_ZOOKEEPER_USER: Kafka Zookeeper user. No defaults
  • KAFKA_ZOOKEEPER_PASSWORD: Kafka Zookeeper user password. No defaults
  • KAFKA_CERTIFICATE_PASSWORD: Password for certificates. Default: bitnami1
  • KAFKA_HEAP_OPTS: Kafka's Java Heap size. Default: -Xmx1024m -Xms1024m
docker run --name kafka -e KAFKA_ZOOKEEPER_CONNECT=zookeeper:2181 bitnami/kafka:latest

or using Docker Compose:

version: '2'

services:
  zookeeper:
    image: 'bitnami/zookeeper:latest'
    ports:
      - '2181:2181'
    volumes:
      - 'zookeeper_data:/bitnami/zookeeper'
  kafka:
    image: 'bitnami/kafka:0'
    ports:
      - '9092:9092'
    volumes:
      - 'kafka_data:/bitnami/kafka'
    environment:
      - KAFKA_ZOOKEEPER_CONNECT=zookeeper:2181

volumes:
  zookeeper_data:
    driver: local
  kafka_data:
    driver: local

Security

The Bitnami Kafka docker image disables the PLAINTEXT listener for security reasons.
You can enable the PLAINTEXT listener by adding this environment variable, but remember that this
configuration is not recommended for production.

ALLOW_PLAINTEXT_LISTENER=yes

In order to configure SASL authentication over SSL, you should just define the proper listener by
passing the following env vars:

KAFKA_LISTENERS=SASL_SSL://:9092
KAFKA_ADVERTISED_LISTENERS=SASL_SSL://:9092

You can use your own certificates for SSL. You can drop your Java Key Stores files into
/bitnami/kafka/conf/certs.
If the JKS is password protected (recommended), you will need to provide it to get access to the keystores:

KAFKA_CERTITICATE_PASSWORD=myCertificatePassword

This script will help you with the creation of the JKS and certificates. Use the same password for
all them:

https://raw.githubusercontent.com/confluentinc/confluent-platform-security-tools/master/kafka-generate-ssl.sh

InterBroker communications

By default, communications that happens between brokers are authenticated.
You can provide your own credentials using this environment variables:

  • KAFKA_INTER_BROKER_USER: Kafka inter broker communication user. Default: admin
  • KAFKA_INTER_BROKER_PASSWORD: Kafka inter broker communication password. Default: bitnami

Kafka client configuration

By default, any Kafka client needs to authenticate before can connect to a broker.
You can provide your own credentials using this environment variables:

  • KAFKA_BROKER_USER: Kafka client user. Default: user
  • KAFKA_BROKER_PASSWORD: Kafka client user password. Default: bitnami

Kafka ZooKeeper client configuration

In order to authenticate Kafka against a Zookeeper server with SASL authentication you should provide
the next environment variables:

  • KAFKA_ZOOKEEPER_USER: Kafka Zookeeper user. No defaults.
  • KAFKA_ZOOKEEPER_PASSWORD: Kafka Zookeeper user password. No defaults.

Below you can see a complete Docker Compose example:

version: '2'

services:
  zookeeper:
    image: 'bitnami/zookeeper:latest'
    ports:
     - '2181:2181'
    environment:
      - ZOO_ENABLE_AUTH=yes
      - ZOO_SERVER_USERS=kafka
      - ZOO_SERVER_PASSWORDS=kafka_password
  kafka:
    image: 'bitnami/kafka:latest'
    ports:
      - '9092'
    environment:
      - KAFKA_ZOOKEEPER_CONNECT=zookeeper:2181
      - KAFKA_LISTENERS=SASL_SSL://:9092
      - KAFKA_ADVERTISED_LISTENERS=SASL_SSL://:9092
      - KAFKA_ZOOKEEPER_USER=kafka
      - KAFKA_ZOOKEEPER_PASSWORD=kafka_password

Connecting services with security enabled

In order to get the required credentials to consume and produce messages you need to provide the
credentials in the client. If your Kafka client allows it, use the credentials you've provided.

While producing and consuming messages using the bitnami/kafka image, you'll need to point to the
consumer.properties and/or producer.properties file, which contains the needed configuration
to work. You can find this files in the /bitnami/kafka/config directory

Use this to generate messages using a secure setup

export KAFKA_OPTS="-Djava.security.auth.login.config=/opt/bitnami/kafka/conf/kafka_jaas.conf"
kafka-console-producer.sh --broker-list 127.0.0.1:9092 --topic test --producer.config /opt/bitnami/kafka/conf/producer.properties

Use this to consume messages using a secure setup

export KAFKA_OPTS="-Djava.security.auth.login.config=/opt/bitnami/kafka/conf/kafka_jaas.conf"
kafka-console-consumer.sh --bootstrap-server 127.0.0.1:9092 --topic test --consumer.config /opt/bitnami/kafka/conf/consumer.properties

If you use other tools to use your Kafka cluster, you'll need to provide the required information.
You can find the required information in the files located at /bitnami/kafka/conf directory.

Setting up a Kafka Cluster

A Kafka cluster can easily be setup with the Bitnami Kafka Docker image using the following environment variables:

  • KAFKA_ZOOKEEPER_CONNECT: Comma separated host:port pairs, each corresponding to a Zookeeper Server.

Create a Docker network to enable visibility to each other via the docker container name

docker network create app-tier --driver bridge

Step 1: Create the first node for Zookeeper

The first step is to create one Zookeeper instance.

docker run --name zookeeper \
  --network app-tier \
  -p 2181:2181 \
  bitnami/zookeeper:latest

Step 2: Create the first node for Kafka

The first step is to create one Kafka instance.

docker run --name kafka1 \
  --network app-tier \
  -e KAFKA_ZOOKEEPER_CONNECT=zookeeper:2181 \
  -p 9092:9092 \
  bitnami/kafka:latest

Step 2: Create the second node

Next we start a new Kafka container.

docker run --name kafka2 \
  --network app-tier \
  -e KAFKA_ZOOKEEPER_CONNECT=zookeeper:2181 \
  -p 9092:9092 \
  bitnami/kafka:latest

Step 3: Create the third node

Next we start another new Kafka container.

docker run --name kafka3 \
  --network app-tier \
  -e KAFKA_ZOOKEEPER_CONNECT=zookeeper:2181 \
  -p 9092:9092 \
  bitnami/kafka:latest

You now have a Kafka cluster up and running. You can scale the cluster by adding/removing slaves without incurring any downtime.

With Docker Compose, topic replication can be setup using:

version: '2'

services:
  zookeeper:
    image: 'bitnami/zookeeper:latest'
    ports:
     - '2181:2181'
  kafka1:
    image: 'bitnami/kafka:latest'
    ports:
      - '9092'
    environment:
      - KAFKA_ZOOKEEPER_CONNECT=zookeeper:2181
  kafka2:
    image: 'bitnami/kafka:latest'
    ports:
      - '9092'
    environment:
      - KAFKA_ZOOKEEPER_CONNECT=zookeeper:2181
  kafka3:
    image: 'bitnami/kafka:latest'
    ports:
      - '9092'
    environment:
      - KAFKA_ZOOKEEPER_CONNECT=zookeeper:2181

Then, you can create a replicated topic with:

root@kafka1:/# /opt/bitnami/kafka/bin/kafka-topics.sh --create --zookeeper zookeeper:2181 --topic mytopic --partitions 3 --replication-factor 3
Created topic "mytopic".

root@kafka1:/# /opt/bitnami/kafka/bin/kafka-topics.sh --describe --zookeeper zookeeper:2181 --topic mytopic
Topic:mytopic   PartitionCount:3        ReplicationFactor:3     Configs:
        Topic: mytopic  Partition: 0    Leader: 2       Replicas: 2,3,1 Isr: 2,3,1
        Topic: mytopic  Partition: 1    Leader: 3       Replicas: 3,1,2 Isr: 3,1,2
        Topic: mytopic  Partition: 2    Leader: 1       Replicas: 1,2,3 Isr: 1,2,3

Configuration

The image looks for configuration in the config/ directory of /bitnami/kafka.

docker run --name kafka -v /path/to/my_custom_conf_directory:/bitnami/kafka bitnami/kafka:latest

After that, your changes will be taken into account in the server's behaviour.

Step 1: Run the Kafka image

Run the Kafka image, mounting a directory from your host.

Using Docker Compose:

version: '2'

services:
  kafka:
    image: 'bitnami/kafka:latest'
    ports:
      - '9092:9092'
    volumes:
      - /path/to/kafka-persistence:/bitnami/kafka

Step 2: Edit the configuration

Edit the configuration on your host using your favorite editor.

vi /path/to/kafka-persistence/config/server.properties

Step 3: Restart Kafka

After changing the configuration, restart your Kafka container for changes to take effect.

docker restart kafka

or using Docker Compose:

docker-compose restart kafka

Logging

The Bitnami Kafka Docker image sends the container logs to the stdout. To view the logs:

docker logs kafka

or using Docker Compose:

docker-compose logs kafka

You can configure the containers logging driver using the --log-driver option if you wish to consume the container logs differently. In the default configuration docker uses the json-file driver.

Maintenance

Backing up your container

To backup your data, configuration and logs, follow these simple steps:

Step 1: Stop the currently running container

docker stop kafka

or using Docker Compose:

docker-compose stop kafka

Step 2: Run the backup command

We need to mount two volumes in a container we will use to create the backup: a directory on your host to store the backup in, and the volumes from the container we just stopped so we can access the data.

docker run --rm -v /path/to/kafka-backups:/backups --volumes-from kafka busybox \
  cp -a /bitnami/kafka:latest /backups/latest

or using Docker Compose:

docker run --rm -v /path/to/kafka-backups:/backups --volumes-from `docker-compose ps -q kafka` busybox \
  cp -a /bitnami/kafka:latest /backups/latest

Restoring a backup

Restoring a backup is as simple as mounting the backup as volumes in the container.

docker run -v /path/to/kafka-backups/latest:/bitnami/kafka bitnami/kafka:latest

or using Docker Compose:

version: '2'

services:
  kafka:
    image: 'bitnami/kafka:latest'
    ports:
      - '9092:9092'
    volumes:
      - /path/to/kafka-backups/latest:/bitnami/kafka

Upgrade this image

Bitnami provides up-to-date versions of Kafka, including security patches, soon after they are made upstream. We recommend that you follow these steps to upgrade your container.

Step 1: Get the updated image

docker pull bitnami/kafka:latest

or if you're using Docker Compose, update the value of the image property to
bitnami/kafka:latest.

Step 2: Stop and backup the currently running container

Before continuing, you should backup your container's data, configuration and logs.

Follow the steps on creating a backup.

Step 3: Remove the currently running container

docker rm -v kafka

or using Docker Compose:

docker-compose rm -v kafka

Step 4: Run the new image

Re-create your container from the new image, restoring your backup if necessary.

docker run --name kafka bitnami/kafka:latest

or using Docker Compose:

docker-compose start kafka

Notable Changes

0.10.2.1-r3

  • The kafka container has been migrated to a non-root container approach. Previously the container run as root user and the kafka daemon was started as kafka user. From now own, both the container and the kafka daemon run as user 1001.
    As a consequence, the configuration files are writable by the user running the kafka process.

0.10.2.1-r0

  • New Bitnami release

Contributing

We'd love for you to contribute to this container. You can request new features by creating an issue, or submit a pull request with your contribution.

Issues

If you encountered a problem running this container, you can file an issue. For us to provide better support, be sure to include the following information in your issue:

  • Host OS and version
  • Docker version (docker version)
  • Output of docker info
  • Version of this container (echo $BITNAMI_IMAGE_VERSION inside the container)
  • The command you used to run the container, and any relevant output you saw (masking any sensitive information)

Community

Most real time communication happens in the #containers channel at bitnami-oss.slack.com; you can sign up at slack.oss.bitnami.com.

Discussions are archived at bitnami-oss.slackarchive.io.

License

Copyright (c) 2015-2017 Bitnami

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.

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