Important

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Confluent CLI

In this tutorial, you will use the Confluent CLI to messages to and consumes messages from an Apache Kafka® cluster.

After you run the tutorial, view the provided source code and use it as a reference to develop your own Kafka client application.

Note

The Confluent CLI is meant for development purposes only and isn’t suitable for a production environment.

Prerequisites

Client

• Download Confluent Platform 5.5.15, which includes the Confluent CLI.

Kafka Cluster

• You can use this tutorial with a Kafka cluster in any environment:
  • In Confluent Cloud
  • On your local host
  • Any remote Kafka cluster
• If you are running on Confluent Cloud, you must have access to a Confluent Cloud cluster
  • The first 20 users to sign up for Confluent Cloud and use promo code C50INTEG will receive an additional $50 free usage (details)

Setup

1. Clone the confluentinc/examples GitHub repository and check out the 5.5.15-post branch.

   git clone https://github.com/confluentinc/examples
   cd examples
   git checkout 5.5.15-post
   

2. Change directory to the example for Confluent CLI.

   cd clients/cloud/confluent-cli/
   

3. Create a local file (for example, at $HOME/.confluent/java.config) with configuration parameters to connect to your Kafka cluster. Starting with one of the templates below, customize the file with connection information to your cluster. Substitute your values for {{ BROKER_ENDPOINT }}, {{CLUSTER_API_KEY }}, and {{ CLUSTER_API_SECRET }} (see Connecting Clients to Confluent Cloud for instructions on how to create or find those values).

   • Template configuration file for Confluent Cloud

     # Kafka
     bootstrap.servers={{ BROKER_ENDPOINT }}
     security.protocol=SASL_SSL
     sasl.jaas.config=org.apache.kafka.common.security.plain.PlainLoginModule required username="{{ CLUSTER_API_KEY }}" password="{{ CLUSTER_API_SECRET }}";
     ssl.endpoint.identification.algorithm=https
     sasl.mechanism=PLAIN
     

   • Template configuration file for local host

     # Kafka
     bootstrap.servers=localhost:9092
     

Basic Producer and Consumer

In this example, the producer application writes Kafka data to a topic in your Kafka cluster. If the topic does not already exist in your Kafka cluster, the producer application will use the Kafka Admin Client API to create the topic. Each record written to Kafka has a key representing a username (for example, alice) and a value of a count, formatted as json (for example, {"count": 0}). The consumer application reads the same Kafka topic and keeps a rolling sum of the count as it processes each record.

Produce Records

1. Create the topic in Confluent Cloud.

   kafka-topics --bootstrap-server `grep "^\s*bootstrap.server" $HOME/.confluent/java.config | tail -1` --command-config $HOME/.confluent/java.config --topic test1 --create --replication-factor 3 --partitions 6
   

2. Run the Confluent CLI producer, writing messages to topic test1, passing in arguments for:

   • --cloud: write messages to a Confluent Cloud cluster
   • --config: file with Confluent Cloud connection info
   • --property parse.key=true --property key.separator=,: pass key and value, separated by a comma

   confluent local produce test1 -- --cloud --config $HOME/.confluent/java.config --property parse.key=true --property key.separator=,
   

3. At the > prompt, type a few messages, using a , as the separator between the message key and value:

   alice,{"count":0}
   alice,{"count":1}
   alice,{"count":2}
   

4. When you are done, press Ctrl-D.

5. View the producer code.

Consume Records

1. Run the Confluent CLI consumer, reading messages from topic test1, passing in additional arguments:

   • --cloud: write messages to a Confluent Cloud cluster
   • --config: file with Confluent Cloud connection info
   • --property print.key=true: print key and value (by default, it only prints value)
   • --from-beginning: print all messages from the beginning of the topic

   confluent local consume test1 -- --cloud --config $HOME/.confluent/java.config --property print.key=true --from-beginning
   

2. Verify that the consumer received all the messages. You should see:

   alice   {"count":0}
   alice   {"count":1}
   alice   {"count":2}
   

3. When you are done, press Ctrl-C.

4. View the consumer code.

Avro And Confluent Cloud Schema Registry

This example is similar to the previous example, except the value is formatted as Avro and integrates with the Confluent Cloud Schema Registry. Before using Confluent Cloud Schema Registry, check its availability and limits.

1. As described in the Schema Registry and Confluent Cloud in the Confluent Cloud GUI, enable Confluent Cloud Schema Registry and create an API key and secret to connect to it.

2. Verify that your VPC can connect to the Confluent Cloud Schema Registry public internet endpoint.

3. Update your local configuration file (for example, at $HOME/.confluent/java.config) with parameters to connect to Schema Registry.

   • Template configuration file for Confluent Cloud

     # Kafka
     bootstrap.servers={{ BROKER_ENDPOINT }}
     security.protocol=SASL_SSL
     sasl.jaas.config=org.apache.kafka.common.security.plain.PlainLoginModule required username="{{ CLUSTER_API_KEY }}" password="{{ CLUSTER_API_SECRET }}";
     ssl.endpoint.identification.algorithm=https
     sasl.mechanism=PLAIN
     
     # Confluent Cloud Schema Registry
     schema.registry.url=https://{{ SR_ENDPOINT }}
     basic.auth.credentials.source=USER_INFO
     schema.registry.basic.auth.user.info={{ SR_API_KEY }}:{{ SR_API_SECRET }}
     

   • Template configuration file for local host

     # Kafka
     bootstrap.servers=localhost:9092
     
     # Confluent Schema Registry
     schema.registry.url=http://localhost:8081
     

4. Verify your Confluent Cloud Schema Registry credentials work from your host. In the following example, substitute your values for {{ SR_API_KEY}}, {{SR_API_SECRET }}, and {{ SR_ENDPOINT }}.

   # View the list of registered subjects
   $ curl -u {{ SR_API_KEY }}:{{ SR_API_SECRET }} https://{{ SR_ENDPOINT }}/subjects
   
   # Same as above, as a single bash command to parse the values out of  $HOME/.confluent/java.config
   $ curl -u $(grep "^schema.registry.basic.auth.user.info"  $HOME/.confluent/java.config | cut -d'=' -f2) $(grep "^schema.registry.url"  $HOME/.confluent/java.config | cut -d'=' -f2)/subjects
   

Produce Avro Records

1. Verify your Confluent Cloud Schema Registry credentials work from your host. In the output below, substitute your values for <SR API KEY>, <SR API SECRET>, and <SR ENDPOINT>.

   # View the list of registered subjects
   curl -u <SR API KEY>:<SR API SECRET> https://<SR ENDPOINT>/subjects
   
   # Same as above, as a single bash command to parse the values out of $HOME/.confluent/java.config
   curl -u $(grep "^schema.registry.basic.auth.user.info" $HOME/.confluent/java.config | cut -d'=' -f2) $(grep "^schema.registry.url" $HOME/.confluent/java.config | cut -d'=' -f2)/subjects
   

2. View your local Confluent Cloud configuration file ($HOME/.confluent/java.config):

   cat $HOME/.confluent/java.config
   

3. In the configuration file, substitute values for <SR API KEY>, <SR API SECRET>, and <SR ENDPOINT> as displayed in the following example:

   ...
   basic.auth.credentials.source=USER_INFO
   schema.registry.basic.auth.user.info=<SR API KEY>:<SR API SECRET>
   schema.registry.url=https://<SR ENDPOINT>
   ...
   

4. Create the topic in Confluent Cloud.

   kafka-topics --bootstrap-server `grep "^\s*bootstrap.server" $HOME/.confluent/java.config | tail -1` --command-config $HOME/.confluent/java.config --topic test2 --create --replication-factor 3 --partitions 6
   

5. Run the Confluent CLI producer, writing messages to topic test2, passing in arguments for:

   • --value-format avro: use Avro data format for the value part of the message
   • --property value.schema: define the schema
   • --property schema.registry.url: connect to the Confluent Cloud Schema Registry endpoint http://<SR ENDPOINT>
   • --property basic.auth.credentials.source: specify USER_INFO
   • --property schema.registry.basic.auth.user.info: <SR API KEY>:<SR API SECRET>

   Important

   You must pass in the additional Schema Registry parameters as properties instead of a properties file due to https://github.com/confluentinc/schema-registry/issues/1052.

   confluent local produce test2 -- --cloud --config $HOME/.confluent/java.config --value-format avro --property value.schema='{"type":"record","name":"myrecord","fields":[{"name":"count","type":"int"}]}' --property schema.registry.url=https://<SR ENDPOINT> --property basic.auth.credentials.source=USER_INFO --property schema.registry.basic.auth.user.info='<SR API KEY>:<SR API SECRET>'
   

6. At the > prompt, type the following messages:

   {"count":0}
   {"count":1}
   {"count":2}
   

7. When you are done, press Ctrl-D.

8. View the producer Avro code.

Consume Avro Records

1. Run the Confluent CLI consumer, reading messages from topic test2, passing in arguments for:

   • --value-format avro: use Avro data format for the value part of the message
   • --property schema.registry.url: connect to the Confluent Cloud Schema Registry endpoint http://<SR ENDPOINT>
   • --property basic.auth.credentials.source: specify USER_INFO
   • --property schema.registry.basic.auth.user.info: <SR API KEY>:<SR API SECRET>

   Important

   You must pass in the additional Schema Registry parameters as properties instead of a properties file due to https://github.com/confluentinc/schema-registry/issues/1052.

   confluent local consume test2 -- --cloud --config $HOME/.confluent/java.config --value-format avro --property schema.registry.url=https://<SR ENDPOINT> --property basic.auth.credentials.source=USER_INFO --property schema.registry.basic.auth.user.info='<SR API KEY>:<SR API SECRET>' --from-beginning
   

2. Verify that the consumer received all the messages. You should see:

   {"count":0}
   {"count":1}
   {"count":2}
   

3. When you are done, press Ctrl-C.

4. View the consumer Avro code.