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Docker Configuration ¶

You can install the Confluent Platform using Docker images. This section provides an overview of Confluent’s Docker images for the Confluent Platform.

Contents

Docker Configuration

Confluent Docker Images ¶

The Confluent Platform Docker images support passing configuration variables dynamically using environment variables. More specifically, we use the Docker -e or --env flags for setting various settings in the respective images when starting up the images.

The images are available for Confluent Platform 3.0.1 and greater. Images are available on DockerHub for each component of the Confluent Platform. Alternatively, the source files for the images are available on Github if you would prefer to extend and/or rebuild the images and upload them to your own DockerHub repository.

The table below lists the available images and the Confluent software packages they contain. You’ll note that some images are identified as `cp-enterprise-${component_name}`. These images include proprietary components that must be licensed from Confluent when deployed.

Component	Image Name	Type	Packages Included
Base Image	cp-base	Open Source	zulu-openjdk-8
Kafka	cp-kafka	Open Source	confluent-kafka-*
Kafka	cp-enterprise-kafka	Enterprise	confluent-kafka-* confluent-rebalancer confluent-support-metrics
Control Center	cp-enterprise-control-center	Enterprise	confluent-control-center
Replicator	cp-enterprise-replicator	Enterprise	confluent-kafka-replicator confluent-schema-registry confluent-control-center
Replicator Executable	cp-enterprise-replicator -executable	Enterprise	confluent-kafka-replicator confluent-schema-registry confluent-control-center
Kafka Connect	cp-kafka-connect	Enterprise	confluent-kafka-connect-jdbc confluent-kafka-connect-hdfs confluent-schema-registry confluent-control-center confluent-kafka-connect-elasticsearch confluent-kafka-connect-s3
Schema Registry	cp-schema-registry	Open Source	confluent-schema-registry
REST Proxy	cp-kafka-rest	Open Source	confluent-kafka-rest

Note: The Kafka Connect image is labeled as “Enterprise” simply because it contains the Confluent Control Center package. That package enables the deployed connectors to collect the metrics visualized in Confluent Control Center. No explicit license is required when using the Kafka Connect image on its own.

Configuration Notes ¶

Persistent Data (Mounted Volumes)

When deploying the Kafka and ZooKeeper images, you should always use mounted volumes for the file systems those images use for their persistent data. This ensures that the containers will retain their proper state when stopped and restarted. The other images maintain their state directly in Kafka topics, so mounted volumes are not usually required for those containers.
Bridge Networking vs. Host Networking
Bridge networking is currently only supported on a single host. For multiple hosts, you will need to use overlay networks which are not currently supported. To expose Kafka to clients outside of the bridge network, you need to find the container IP and put it in advertised.listeners. This can be difficult to achieve depending on how you’re using the images. Furthermore, it can add a network hop and may not be as performant as the host network, which shares the network stack. In summary, host networking is the recommended option in the following cases:
Multi-host clusters without using Swarm/Kubernetes host network is the best approach

If you need clients to be able to access Kafka outside the bridge/overlay network
Adding Connectors to the Kafka Connect Image
There are currently two ways to add new connectors to the Kafka Connect image.
- Build a new Docker image that has the connector installed. You can follow the examples found in Extending Images. You will need to make sure that the connector jars are on the CLASSPATH for the Connect service (the default location of /usr/share/java/kafka-connect-* is the recommended location).
- Add the connector jars via volumes. If you don’t want to create a new Docker image, please see our documentation on Configuring Kafka Connect with External Jars to configure the cp-kafka-connect container with external jars.
Included Java

The Confluent Docker images are tested and shipped with Azul Zulu OpenJDK. For more information about Java support, see supported Java versions.
Untested Features
The following features/environments are not currently tested:
The images are not currently tested on Docker Swarm.

Configuration Parameters ¶

Some configuration variables are required when starting up the Docker images. We have outlined those variables below for each component along with an example of how to pass them. For a full list of all available configuration options for each Confluent Platform component, you should refer to their respective documentation.

ZooKeeper
Confluent Kafka (cp-kafka)
Confluent Enterprise Kafka (cp-enterprise-kafka)
Schema Registry
Kafka REST Proxy
Kafka Connect
Confluent Control Center
Confluent Enterprise Replicator
Confluent Enterprise Replicator Executable
KSQL Server
KSQL CLI

ZooKeeper ¶

The ZooKeeper image uses variables prefixed with ZOOKEEPER_ with the variables expressed exactly as they would appear in the zookeeper.properties file. As an example, to set clientPort, tickTime, and syncLimit run the command below:

docker run -d \
--net=host \
--name=zookeeper \
-e ZOOKEEPER_CLIENT_PORT=32181 \
-e ZOOKEEPER_TICK_TIME=2000 \
-e ZOOKEEPER_SYNC_LIMIT=2 \
confluentinc/cp-zookeeper:4.1.5-SNAPSHOT

Required Settings¶

ZOOKEEPER_CLIENT_PORT

This field is always required. Tells ZooKeeper where to listen for connections by clients such as Kafka.

ZOOKEEPER_SERVER_ID

Only required when running in clustered mode. Sets the server ID in the myid file, which consists of a single line containing only the text of that machine’s id. So myid of server 1 would contain the text “1” and nothing else. The id must be unique within the ensemble and should have a value between 1 and 255.

Confluent Kafka (cp-kafka)¶

The Kafka image uses variables prefixed with KAFKA_ with an underscore (_) separating each word instead of periods. As an example, to set broker.id, advertised.listeners, zookeeper.connect, and offsets.topic.replication.factor, you’d run the following command:

docker run -d \
    --net=host \
    --name=kafka \
    -e KAFKA_ZOOKEEPER_CONNECT=localhost:32181 \
    -e KAFKA_ADVERTISED_LISTENERS=PLAINTEXT://localhost:29092 \
    -e KAFKA_BROKER_ID=2 \
    -e KAFKA_OFFSETS_TOPIC_REPLICATION_FACTOR=1 \
    confluentinc/cp-kafka:4.1.5-SNAPSHOT
Note

You’ll notice that we set the KAFKA_ADVERTISED_LISTENERS variable to localhost:29092. This is an important setting, as it will make Kafka accessible from outside the container by advertising its location on the Docker host.

Also notice that we set KAFKA_OFFSETS_TOPIC_REPLICATION_FACTOR to 1. This is needed when you are running with a single-node cluster. If you have three or more nodes, you do not need to change this from the default.

Required Settings¶

KAFKA_ZOOKEEPER_CONNECT

Tells Kafka how to get in touch with ZooKeeper.

KAFKA_ADVERTISED_LISTENERS

Advertised listeners is required for starting up the Docker image because it is important to think through how other clients are going to connect to kafka. In a Docker environment, you will need to make sure that your clients can connect to Kafka and other services. Advertised listeners is how it gives out a host name that can be reached by the client.

Confluent Enterprise Kafka (cp-enterprise-kafka)¶

The Enterprise Kafka image includes the packages for Confluent Auto Data Balancing and Proactive support in addition to Kafka. The Enterprise Kafka image uses variables prefixed with KAFKA_ for Apache Kafka and with CONFLUENT_ for Confluent components. These variables have an underscore (_) separating each word instead of periods. As an example, to set broker.id, advertised.listeners, zookeeper.connect, offsets.topic.replication.factor, and confluent.support.customer.id you’d run the following command:

docker run -d \
    --net=host \
    --name=kafka \
    -e KAFKA_ZOOKEEPER_CONNECT=localhost:32181 \
    -e KAFKA_ADVERTISED_LISTENERS=PLAINTEXT://localhost:29092 \
    -e KAFKA_BROKER_ID=2 \
    -e KAFKA_OFFSETS_TOPIC_REPLICATION_FACTOR=1 \
    -e CONFLUENT_SUPPORT_CUSTOMER_ID=c0 \
    confluentinc/cp-enterprise-kafka:4.1.5-SNAPSHOT
Note

You’ll notice that we set the KAFKA_ADVERTISED_LISTENERS variable to localhost:29092. This is an important setting, as it will make Kafka accessible from outside the container by advertising its location on the Docker host.

If you want to enable Proactive support or use Confluent Auto Data Balancing features, please follow the Proactive support and ADB documentation at Confluent documentation.

Also notice that we set KAFKA_OFFSETS_TOPIC_REPLICATION_FACTOR to 1. This is needed when you are running with a single-node cluster. If you have three or more nodes, you do not need to change this from the default.

Required Settings¶

KAFKA_ZOOKEEPER_CONNECT

Tells Kafka how to get in touch with ZooKeeper.

KAFKA_ADVERTISED_LISTENERS

Advertised listeners is required for starting up the Docker image because it is important to think through how other clients are going to connect to kafka. In a Docker environment, you will need to make sure that your clients can connect to Kafka and other services. Advertised listeners is how it gives out a host name that can be reached by the client.

Schema Registry ¶

For the Schema Registry image, use variables prefixed with SCHEMA_REGISTRY_ with an underscore (_) separating each word instead of periods. As an example, to set kafkastore.connection.url, host.name, listeners and debug you’d run the following:

docker run -d \
  --net=host \
  --name=schema-registry \
  -e SCHEMA_REGISTRY_KAFKASTORE_CONNECTION_URL=localhost:32181 \
  -e SCHEMA_REGISTRY_HOST_NAME=localhost \
  -e SCHEMA_REGISTRY_LISTENERS=http://localhost:8081 \
  -e SCHEMA_REGISTRY_DEBUG=true \
  confluentinc/cp-schema-registry:4.1.5-SNAPSHOT

Required Settings¶

SCHEMA_REGISTRY_KAFKASTORE_CONNECTION_URL

ZooKeeper URL for the Kafka cluster.

SCHEMA_REGISTRY_HOST_NAME

The host name advertised in ZooKeeper. Make sure to set this if running Schema Registry with multiple nodes. Hostname is required because it defaults to the Java canonical host name for the container, which may not always be resolvable in a Docker environment. Hostname must be resolveable because slave nodes serve registration requests indirectly by simply forwarding them to the current master, and returning the response supplied by the master. For more information, please refer to the Schema Registry documentation on Single Master Architecture.

Kafka REST Proxy ¶

For the Kafka REST Proxy image use variables prefixed with KAFKA_REST_ with an underscore (_) separating each word instead of periods. As an example, to set the listeners, schema.registry.url and zookeeper.connect you’d run the following command:

docker run -d \
  --net=host \
  --name=kafka-rest \
  -e KAFKA_REST_ZOOKEEPER_CONNECT=localhost:32181 \
  -e KAFKA_REST_LISTENERS=http://localhost:8082 \
  -e KAFKA_REST_SCHEMA_REGISTRY_URL=http://localhost:8081 \
  confluentinc/cp-kafka-rest:4.1.5-SNAPSHOT

Required Settings¶

The following settings must be passed to run the REST Proxy Docker image.

KAFKA_REST_HOST_NAME

The host name used to generate absolute URLs in responses. Hostname is required because it defaults to the Java canonical host name for the container, which may not always be resolvable in a Docker environment. For more details, please refer to the Confluent Platform documentation on REST proxy deployment.

KAFKA_REST_ZOOKEEPER_CONNECT

Specifies the ZooKeeper connection string in the form hostname:port where host and port are the host and port of a ZooKeeper server. To allow connecting through other ZooKeeper nodes when that ZooKeeper machine is down you can also specify multiple hosts in the form hostname1:port1,hostname2:port2,hostname3:port3.

The server may also have a ZooKeeper chroot path as part of its ZooKeeper connection string which puts its data under some path in the global ZooKeeper namespace. If so the consumer should use the same chroot path in its connection string. For example to give a chroot path of /chroot/path you would give the connection string as hostname1:port1,hostname2:port2,hostname3:port3/chroot/path.

Kafka Connect ¶

The Kafka Connect image uses variables prefixed with CONNECT_ with an underscore (_) separating each word instead of periods. As an example, to set the required properties like bootstrap.servers, the topic names for config, offsets and status as well the key or value converter, run the following command:

docker run -d \
  --name=kafka-connect \
  --net=host \
  -e CONNECT_BOOTSTRAP_SERVERS=localhost:29092 \
  -e CONNECT_REST_PORT=28082 \
  -e CONNECT_GROUP_ID="quickstart" \
  -e CONNECT_CONFIG_STORAGE_TOPIC="quickstart-config" \
  -e CONNECT_OFFSET_STORAGE_TOPIC="quickstart-offsets" \
  -e CONNECT_STATUS_STORAGE_TOPIC="quickstart-status" \
  -e CONNECT_KEY_CONVERTER="org.apache.kafka.connect.json.JsonConverter" \
  -e CONNECT_VALUE_CONVERTER="org.apache.kafka.connect.json.JsonConverter" \
  -e CONNECT_INTERNAL_KEY_CONVERTER="org.apache.kafka.connect.json.JsonConverter" \
  -e CONNECT_INTERNAL_VALUE_CONVERTER="org.apache.kafka.connect.json.JsonConverter" \
  -e CONNECT_REST_ADVERTISED_HOST_NAME="localhost" \
  -e CONNECT_LOG4J_LOGGERS=org.reflections=ERROR \
  -e CONNECT_PLUGIN_PATH=/usr/share/java \
  confluentinc/cp-kafka-connect:4.1.5-SNAPSHOT

Required Settings¶

The following settings must be passed to run the Kafka Connect Docker image.

CONNECT_BOOTSTRAP_SERVERS

A unique string that identifies the Connect cluster group this worker belongs to.

CONNECT_GROUP_ID

A unique string that identifies the Connect cluster group this worker belongs to.

CONNECT_CONFIG_STORAGE_TOPIC

The name of the topic in which to store connector and task configuration data. This must be the same for all workers with the same group.id

CONNECT_OFFSET_STORAGE_TOPIC

The name of the topic in which to store offset data for connectors. This must be the same for all workers with the same group.id

CONNECT_STATUS_STORAGE_TOPIC

The name of the topic in which to store state for connectors. This must be the same for all workers with the same group.id

CONNECT_KEY_CONVERTER

Converter class for keys. This controls the format of the data that will be written to Kafka for source connectors or read from Kafka for sink connectors.

CONNECT_VALUE_CONVERTER

Converter class for values. This controls the format of the data that will be written to Kafka for source connectors or read from Kafka for sink connectors.

CONNECT_INTERNAL_KEY_CONVERTER

Converter class for internal keys that implements the Converter interface.

CONNECT_INTERNAL_VALUE_CONVERTER

Converter class for internal values that implements the Converter interface.

CONNECT_REST_ADVERTISED_HOST_NAME

Advertised host name is required for starting up the Docker image because it is important to think through how other clients are going to connect to Connect REST API. In a Docker environment, you will need to make sure that your clients can connect to Connect and other services. Advertised host name is how Connect gives out a host name that can be reached by the client.

CONNECT_PLUGIN_PATH: The plugin.path value indicating the location from which to load Connect plugins in classloading isolation.

Optional Settings¶

All other settings for Connect like security, monitoring interceptors, producer and consumer overrides can be passed to the Docker images as environment variables. The names of these environment variables are derived by replacing . with _, converting the resulting string to uppercase and prefixing it with CONNECT_. For example, if you need to set ssl.key.password, the environment variable name would be CONNECT_SSL_KEY_PASSWORD.

The image will then convert these environment variables to corresponding Connect config variables.

Confluent Control Center ¶

The Confluent Control Center image uses variables prefixed with CONTROL_CENTER_ with an underscore (_) separating each word instead of periods. As an example, the following command runs Control Center, passing in its ZooKeeper, Kafka, and Connect configuration parameters.

docker run -d \
  --net=host \
  --name=control-center \
  --ulimit nofile=16384:16384 \
  -e CONTROL_CENTER_ZOOKEEPER_CONNECT=localhost:32181 \
  -e CONTROL_CENTER_BOOTSTRAP_SERVERS=localhost:29092 \
  -e CONTROL_CENTER_REPLICATION_FACTOR=1 \
  -e CONTROL_CENTER_CONNECT_CLUSTER=http://localhost:28082 \
  -v /mnt/control-center/data:/var/lib/confluent-control-center \
  confluentinc/cp-enterprise-control-center:4.1.5-SNAPSHOT

Docker Options¶

File descriptor limit: Control Center may require many open files so we recommend setting the file descriptor limit to at least 16384
Data persistence: the Control Center image stores its data in the /var/lib/confluent-control-center directory. We recommend that you bind this to a volume on the host machine so that data is persisted across runs.

Required Settings¶

The following settings must be passed to run the Confluent Control Center image.

CONTROL_CENTER_ZOOKEEPER_CONNECT

Specifies the ZooKeeper connection string in the form hostname:port where host and port are the host and port of a ZooKeeper server. To allow connecting through other ZooKeeper nodes when that ZooKeeper machine is down you can also specify multiple hosts in the form hostname1:port1,hostname2:port2,hostname3:port3.

The server may also have a ZooKeeper chroot path as part of its ZooKeeper connection string which puts its data under some path in the global ZooKeeper namespace. If so the consumer should use the same chroot path in its connection string. For example to give a chroot path of /chroot/path you would give the connection string as hostname1:port1,hostname2:port2,hostname3:port3/chroot/path.

CONTROL_CENTER_BOOTSTRAP_SERVERS

A list of host/port pairs to use for establishing the initial connection to the Kafka cluster. The client will make use of all servers irrespective of which servers are specified here for bootstrapping; this list only impacts the initial hosts used to discover the full set of servers. This list should be in the form host1:port1,host2:port2,…. Since these servers are just used for the initial connection to discover the full cluster membership (which may change dynamically), this list need not contain the full set of servers (you may want more than one, though, in case a server is down).

CONTROL_CENTER_REPLICATION_FACTOR

Replication factor for Control Center topics. We recommend setting this to 3 in a production environment.

Optional Settings¶

CONTROL_CENTER_CONNECT_CLUSTER

To enable Control Center to interact with a Kafka Connect cluster, set this parameter to the REST endpoint URL for the Kafka Connect cluster.

Confluent Enterprise Replicator ¶

Confluent Kafka Replicator is a Kafka connector and runs on a Kafka Connect cluster. The image uses variables prefixed with CONNECT_ with an underscore (_) separating each word instead of periods. As an example, to set the required properties like bootstrap.servers, the topic names for config, offsets and status as well the key or value converter, run the following command:

docker run -d \
  --name=cp-enterprise-replicator \
  --net=host \
  -e CONNECT_BOOTSTRAP_SERVERS=localhost:29092 \
  -e CONNECT_REST_PORT=28082 \
  -e CONNECT_GROUP_ID="quickstart" \
  -e CONNECT_CONFIG_STORAGE_TOPIC="quickstart-config" \
  -e CONNECT_OFFSET_STORAGE_TOPIC="quickstart-offsets" \
  -e CONNECT_STATUS_STORAGE_TOPIC="quickstart-status" \
  -e CONNECT_KEY_CONVERTER="org.apache.kafka.connect.json.JsonConverter" \
  -e CONNECT_VALUE_CONVERTER="org.apache.kafka.connect.json.JsonConverter" \
  -e CONNECT_INTERNAL_KEY_CONVERTER="org.apache.kafka.connect.json.JsonConverter" \
  -e CONNECT_INTERNAL_VALUE_CONVERTER="org.apache.kafka.connect.json.JsonConverter" \
  -e CONNECT_REST_ADVERTISED_HOST_NAME="localhost" \
  confluentinc/cp-enterprise-replicator:4.1.5-SNAPSHOT

The following example shows how to create a Confluent Kafka Replicator connector which replicates topic “confluent” from source Kafka cluster (src) to a destination Kafka cluster (dest).

curl -X POST \
     -H "Content-Type: application/json" \
     --data '{
        "name": "confluent-src-to-dest",
        "config": {
          "connector.class":"io.confluent.connect.replicator.ReplicatorSourceConnector",
          "key.converter": "io.confluent.connect.replicator.util.ByteArrayConverter",
          "value.converter": "io.confluent.connect.replicator.util.ByteArrayConverter",
          "src.zookeeper.connect": "zookeeper-src:2181",
          "src.kafka.bootstrap.servers": "kafka-src:9082",
          "dest.zookeeper.connect": "zookeeper-dest:2181",
          "topic.whitelist": "confluent",
          "topic.rename.format": "${topic}.replica"}}'  \
            http://localhost:28082/connectors

Required Settings¶

The following settings must be passed to run the Kafka Connect Docker image:

CONNECT_BOOTSTRAP_SERVERS

A unique string that identifies the Connect cluster group this worker belongs to.

CONNECT_GROUP_ID

A unique string that identifies the Connect cluster group this worker belongs to.

CONNECT_CONFIG_STORAGE_TOPIC

The name of the topic in which to store connector and task configuration data. This must be the same for all workers with the same group.id

CONNECT_OFFSET_STORAGE_TOPIC

The name of the topic in which to store offset data for connectors. This must be the same for all workers with the same group.id

CONNECT_STATUS_STORAGE_TOPIC

The name of the topic in which to store state for connectors. This must be the same for all workers with the same group.id

CONNECT_KEY_CONVERTER

Converter class for keys. This controls the format of the data that will be written to Kafka for source connectors or read from Kafka for sink connectors.

CONNECT_VALUE_CONVERTER

Converter class for values. This controls the format of the data that will be written to Kafka for source connectors or read from Kafka for sink connectors.

CONNECT_INTERNAL_KEY_CONVERTER

Converter class for internal keys that implements the Converter interface.

CONNECT_INTERNAL_VALUE_CONVERTER

Converter class for internal values that implements the Converter interface.

CONNECT_REST_ADVERTISED_HOST_NAME

Advertised host name is required for starting up the Docker image because it is important to think through how other clients are going to connect to Connect REST API. In a Docker environment, you will need to make sure that your clients can connect to Connect and other services. Advertised host name is how Connect gives out a host name that can be reached by the client.

Optional Settings¶

All other settings for Connect like security, monitoring interceptors, producer and consumer overrides can be passed to the Docker images as environment variables. The names of these environment variables are derived by replacing . with _, converting the resulting string to uppercase and prefixing it with CONNECT_. For example, if you need to set ssl.key.password, the environment variable name would be CONNECT_SSL_KEY_PASSWORD.

The image will then convert these environment variables to corresponding Connect config variables.

Confluent Enterprise Replicator Executable ¶

Confluent Kafka Replicator Executable provides another way to run Replicator by consolidating configuration properties and abstracting Kafka Connect details. The image depends on input files that can be passed by mounting a directory with the expected input files or by mounting each file individually. Additionally, the image supports passing command line parameters to the Replicator executable via environment variables as well. For example:

docker run -d \
  --name=ReplicatorX \
  --net=host \
  -e REPLICATOR_LOG4J_ROOT_LOGLEVEL=DEBUG \
  -v /mnt/replicator/config:/etc/replicator \
  confluentinc/cp-enterprise-replicator-executable:4.1.5-SNAPSHOT

will start Replicator given that the local directory /mnt/replicator/config, that will be mounted under /etc/replicator on the Docker image, contains the required files consumer.properties, producer.properties and the optional but often necessary file replication.properties.

In a similar example, we start Replicator by omitting to add a replication.properties and by specifying the replication properties by using environment variables. For a complete list of the expected environment variables see the list of settings in the next sections.

docker run -d \
  --name=ReplicatorX \
  --net=host \
  -e CLUSTER_ID=replicator-east-to-west \
  -e WHITELIST=confluent \
  -e TOPIC_RENAME_FORMAT='${topic}.replica' \
  -e REPLICATOR_LOG4J_ROOT_LOGLEVEL=DEBUG \
  -v /mnt/replicator/config:/etc/replicator \
  confluentinc/cp-enterprise-replicator-executable:4.1.5-SNAPSHOT

Required Settings with Defaults¶

The following files must be passed to run the Replicator Executable Docker image:

CONSUMER_CONFIG

A file that contains the configuration settings for the consumer reading from the origin cluster. Default location is /etc/replicator/consumer.properties in the Docker image.

PRODUCER_CONFIG

A file that contains the configuration settings for the producer writing to the destination cluster. Default location is /etc/replicator/producer.properties in the Docker image.

CLUSTER_ID

A string that specifies the unique identifier for the Replicator cluster. Default value is replicator.

Optional Settings¶

Additional settings that are optional and maybe passed to Replicator Executable via environment variable instead of files are:

REPLICATION_CONFIG

A file that contains the configuration settings for the replication from the origin cluster. Default location is /etc/replicator/replication.properties in the Docker image.

CONSUMER_MONITORING_CONFIG

A file that contains the configuration settings of the producer writing monitoring information related to Replicator’s consumer. Default location is /etc/replicator/consumer-monitoring.properties in the Docker image.

PRODUCER_MONITORING_CONFIG

A file that contains the configuration settings of the producer writing monitoring information related to Replicator’s producer. Default location is /etc/replicator/producer-monitoring.properties in the Docker image.

BLACKLIST

A comma-separated list of topics that should not be replicated, even if they are included in the whitelist or matched by the regular expression.

WHITELIST

A comma-separated list of the names of topics that should be replicated. Any topic that is in this list and not in the blacklist will be replicated.

CLUSTER_THREADS

The total number of threads across all workers in the Replicator cluster.

CONFLUENT_LICENSE

The Confluent license key. Without the license key, Replicator can be used for a 30-day trial period.

TOPIC_AUTO_CREATE

Whether to automatically create topics in the destination cluster if required. If you disable automatic topic creation, Kafka Streams and KSQL applications continue to work. Kafka Streams and KSQL applications use the Admin Client, so topics are still created.

TOPIC_CONFIG_SYNC

Whether to periodically sync topic configuration to the destination cluster.

TOPIC_CONFIG_SYNC_INTERVAL_MS

How often to check for configuration changes when topic.config.sync is enabled.

TOPIC_CREATE_BACKOFF_MS

Time to wait before retrying auto topic creation or expansion.

TOPIC_POLL_INTERVAL_MS

Specifies how frequently to poll the source cluster for new topics matching the whitelist or regular expression.

TOPIC_PRESERVE_PARTITIONS

Whether to automatically increase the number of partitions in the destination cluster to match the source cluster and ensure that messages replicated from the source cluster use the same partition in the destination cluster.

TOPIC_REGEX

A regular expression that matches the names of the topics to be replicated. Any topic that matches this expression (or is listed in the whitelist) and not in the blacklist will be replicated.

TOPIC_RENAME_FORMAT

A format string for the topic name in the destination cluster, which may contain ${topic} as a placeholder for the originating topic name.

TOPIC_TIMESTAMP_TYPE

The timestamp type for the topics in the destination cluster.

The above optional, non-file, command line settings as well as any other settings for Replicator can be passed to Replicator Executable through the required or optional files listed above as well.

KSQL Server ¶

For a complete list of KSQL parameters, see KSQL Configuration Parameter Reference.

KSQL Headless Server Settings¶

Run a standalone KSQL Server instance in a container.

KSQL_BOOTSTRAP_SERVERS: A list of hosts for establishing the initial connection to the Kafka cluster.
KSQL_KSQL_SERVICE_ID: The service ID of the KSQL server, which is used as the prefix for the internal topics created by KSQL.
KSQL_KSQL_QUERIES_FILE: A file that specifies predefined KSQL queries.

docker run -d \
  -v /path/on/host:/path/in/container/ \
  -e KSQL_BOOTSTRAP_SERVERS=localhost:9092 \
  -e KSQL_KSQL_SERVICE_ID=confluent_standalone_2_ \
  -e KSQL_KSQL_QUERIES_FILE=/path/in/container/queries.sql \
  confluentinc/cp-ksql-server:4.1.3

KSQL Headless Server with Interceptors Settings¶

Run a standalone KSQL Server with specified interceptor classes in a container. For more info on interceptor classes, see Confluent Monitoring Interceptors.

KSQL_BOOTSTRAP_SERVERS: A list of hosts for establishing the initial connection to the Kafka cluster.
KSQL_KSQL_SERVICE_ID: The service ID of the KSQL server, which is used as the prefix for the internal topics created by KSQL.
KSQL_KSQL_QUERIES_FILE: A file that specifies predefined KSQL queries.
KSQL_PRODUCER_INTERCEPTOR_CLASSES: A list of fully qualified class names for producer interceptors.
KSQL_CONSUMER_INTERCEPTOR_CLASSES: A list of fully qualified class names for consumer interceptors.

docker run -d \
  -v /path/on/host:/path/in/container/ \
  -e KSQL_BOOTSTRAP_SERVERS=localhost:9092 \
  -e KSQL_KSQL_SERVICE_ID=confluent_standalone_2_ \
  -e KSQL_PRODUCER_INTERCEPTOR_CLASSES=io.confluent.monitoring.clients.interceptor.MonitoringProducerInterceptor \
  -e KSQL_CONSUMER_INTERCEPTOR_CLASSES=io.confluent.monitoring.clients.interceptor.MonitoringConsumerInterceptor \
  -e KSQL_KSQL_QUERIES_FILE=/path/in/container/queries.sql \
  confluentinc/cp-ksql-server:4.1.3

Interactive Server Configuration¶

Run a KSQL Server that enables manual interaction by using the KSQL CLI.

KSQL_BOOTSTRAP_SERVERS: A list of hosts for establishing the initial connection to the Kafka cluster.
KSQL_KSQL_SERVICE_ID: The service ID of the KSQL server, which is used as the prefix for the internal topics created by KSQL.
KSQL_LISTENERS: A list of URIs, including the protocol, that the broker listens on.

docker run -d \
  -p 127.0.0.1:8088:8088 \
  -e KSQL_BOOTSTRAP_SERVERS=localhost:9092 \
  -e KSQL_LISTENERS=http://0.0.0.0:8088/ \
  -e KSQL_KSQL_SERVICE_ID=confluent_test_2 \
  confluentinc/cp-ksql-server:4.1.3

Interactive Server Configuration with Interceptors¶

Run a KSQL Server with interceptors that enables manual interaction by using the KSQL CLI. For more info on interceptor classes, see Confluent Monitoring Interceptors.

KSQL_BOOTSTRAP_SERVERS: A list of hosts for establishing the initial connection to the Kafka cluster.
KSQL_KSQL_SERVICE_ID: The service ID of the KSQL server, which is used as the prefix for the internal topics created by KSQL.
KSQL_LISTENERS: A list of URIs, including the protocol, that the broker listens on.
KSQL_PRODUCER_INTERCEPTOR_CLASSES: A list of fully qualified class names for producer interceptors.
KSQL_CONSUMER_INTERCEPTOR_CLASSES: A list of fully qualified class names for consumer interceptors.

docker run -d \
  -p 127.0.0.1:8088:8088 \
  -e KSQL_BOOTSTRAP_SERVERS=localhost:9092 \
  -e KSQL_LISTENERS=http://0.0.0.0:8088/ \
  -e KSQL_KSQL_SERVICE_ID=confluent_test_2_ \
  -e KSQL_PRODUCER_INTERCEPTOR_CLASSES=io.confluent.monitoring.clients.interceptor.MonitoringProducerInterceptor \
  -e KSQL_CONSUMER_INTERCEPTOR_CLASSES=io.confluent.monitoring.clients.interceptor.MonitoringConsumerInterceptor \
  confluentinc/cp-ksql-server:4.1.3

In interactive mode, the CLI instance running outside Docker can connect to the server running in Docker.

./bin/ksql

...
CLI v4.1.3, Server v4.1.3-SNAPSHOT located at http://localhost:8088

Having trouble? Type 'help' (case-insensitive) for a rundown of how things work!

ksql>

Connect to a Secure Kafka Cluster, Like Confluent Cloud¶

Run a KSQL Server that uses a secure connection to a Kafka cluster. Learn about KSQL Security.

KSQL_BOOTSTRAP_SERVERS: A list of hosts for establishing the initial connection to the Kafka cluster.
KSQL_KSQL_SERVICE_ID: The service ID of the KSQL server, which is used as the prefix for the internal topics created by KSQL.
KSQL_LISTENERS: A list of URIs, including the protocol, that the broker listens on.
KSQL_KSQL_SINK_REPLICAS: The default number of replicas for the topics created by KSQL. The default is one.
KSQL_KSQL_STREAMS_REPLICATION_FACTOR: The replication factor for internal topics, the command topic, and output topics.
KSQL_SECURITY_PROTOCOL: The protocol that your Kafka cluster uses for security.
KSQL_SASL_MECHANISM: The SASL mechanism that your Kafka cluster uses for security.
KSQL_SASL_JAAS_CONFIG: The Java Authentication and Authorization Service (JAAS) configuration.

docker run -d \
  -p 127.0.0.1:8088:8088 \
  -e KSQL_BOOTSTRAP_SERVERS=REMOVED_SERVER1:9092,REMOVED_SERVER2:9093,REMOVED_SERVER3:9094 \
  -e KSQL_LISTENERS=http://0.0.0.0:8088/ \
  -e KSQL_KSQL_SERVICE_ID=default_ \
  -e KSQL_KSQL_SINK_REPLICAS=3 \
  -e KSQL_KSQL_STREAMS_REPLICATION_FACTOR=3 \
  -e KSQL_SECURITY_PROTOCOL=SASL_SSL \
  -e KSQL_SASL_MECHANISM=PLAIN \
  -e KSQL_SASL_JAAS_CONFIG="org.apache.kafka.common.security.plain.PlainLoginModule required username=\"<username>\" password=\"<strong-password>\";" \
  confluentinc/cp-ksql-server:4.1.3

Configure a KSQL Server by Using Java System Properties¶

Run a KSQL Server with a configration that’s defined by Java properties.

KSQL_BOOTSTRAP_SERVERS: A list of hosts for establishing the initial connection to the Kafka cluster.
KSQL_OPTS: A space-separated list of Java options.

docker run -d \
  -v /path/on/host:/path/in/container/ \
  -e KSQL_BOOTSTRAP_SERVERS=localhost:9092 \
  -e KSQL_OPTS="-Dksql.service.id=confluent_test_3_  -Dksql.queries.file=/path/in/container/queries.sql" \
  confluentinc/cp-ksql-server:4.1.3

View logs¶

Use the docker logs command to view KSQL logs that are generated from within the container.

docker logs -f <container-id>
[2018-05-24 23:43:05,591] INFO stream-thread [_confluent-ksql-default_transient_1507119262168861890_1527205385485-71c8a94c-abe9-45ba-91f5-69a762ec5c1d-StreamThread-17] Starting (org.apache.kafka.streams.processor.internals.StreamThread:713)
...

KSQL CLI ¶

Connect to a Dockerized KSQL Server¶

Run a KSQL CLI instance in a container and connect to a KSQL Server that’s running in a container.

The Docker network created by KSQL Server enables you to connect to a dockerized KSQL server.

KSQL_BOOTSTRAP_SERVERS: A list of hosts for establishing the initial connection to the Kafka cluster.
KSQL_OPTS: A space-separated list of Java options.

# Run KSQL Server.
docker run -d -p 10.0.0.11:8088:8088 \
  -e KSQL_BOOTSTRAP_SERVERS=localhost:9092 \
  -e KSQL_OPTS="-Dksql.service.id=confluent_test_3_  -Dlisteners=http://0.0.0.0:8088/" \
  confluentinc/cp-ksql-server:4.1.3

# Connect the KSQL CLI to the server.
docker run -it confluentinc/cp-ksql-cli http://10.0.0.11:8088
...
Copyright 2017 Confluent Inc.

CLI v4.1.3-SNAPSHOT, Server v4.1.3-SNAPSHOT located at http://10.0.0.11:8088

Having trouble? Type 'help' (case-insensitive) for a rundown of how things work!

ksql>

Provide a Configuration File¶

Set up a a KSQL CLI instance by using a configuration file, and run it in a container.

# Assume KSQL Server is running.
# Ensure that the configuration file exists.
ls /path/on/host/ksql-cli.properties

docker run -it \
  -v /path/on/host/:/path/in/container  \
  confluentinc/cp-ksql-cli:4.1.3 http://10.0.0.11:8088 \
  --config-file /path/in/container/ksql-cli.properties

Connect to a KSQL Server Running on Another Host, Like AWS¶

Run a KSQL CLI instance in a container and connect to a remote KSQL Server host.

docker run -it confluentinc/cp-ksql-cli:4.1.3 \
  http://ec2-etc.us-etc.compute.amazonaws.com:8080

...
Copyright 2017 Confluent Inc.

CLI v4.1.3-SNAPSHOT, Server v4.1.3-SNAPSHOT located at http://ec2-blah.us-blah.compute.amazonaws.com:8080

Having trouble? Type 'help' (case-insensitive) for a rundown of how things work!

ksql>