How to schedule periodic operations in a Kafka Streams application

You'd like to have some periodic functionality execute in your Kafka Streams application. In this tutorial, you'll learn how to use punctuations in Kafka Streams to execute work at regular intervals.

To schedule operations in Kafka Streams, you'll need to use the Processor API. In this example, you will use the KStream.process method which mixes the Processor API into the Kafka Streams DSL.

 final KStream<String, LoginTime> loginTimeStream = builder.stream(INPUT_TOPIC, Consumed.with(Serdes.String(), loginTimeSerde));

        loginTimeStream
                .process(new PunctationProcessorSupplier(), Named.as("max-login-time-transformer"), LOGIN_TIME_STORE)
                      .to(OUTPUT_TOPIC, Produced.with(Serdes.String(), Serdes.Long()));

When you call the KStream.process method, you'll pass in a ProcessorSupplier, which returns your Processor implementation.

It's in the Process.init method where you'll schedule arbitrary actions with the ProcessorContext

 public void init(ProcessorContext<String, Long> context) {
    this.context = context;
    this.context.schedule(Duration.ofSeconds(5), PunctuationType.STREAM_TIME, this::streamTimePunctuator);
    this.context.schedule(Duration.ofSeconds(20), PunctuationType.WALL_CLOCK_TIME, this::wallClockTimePunctuator);
}

Here you're scheduling two actions, one using stream time and another on wall-clock time. With stream time, the event timestamps of the incoming records advance the internal time tracked by Kafka Streams. Wall-clock time is the system time of the machine running the Kafka Streams application. Kafka Streams measures wall-clock during its poll interval so executing punctuation based on wall-clock time is best effort only. Here the code uses method handles instead of concrete Punctuator instances.

The following steps use Confluent Cloud. To run the tutorial locally with Docker, skip to the Docker instructions section at the bottom.

Prerequisites

• A Confluent Cloud account
• The Confluent CLI installed on your machine
• Apache Kafka or Confluent Platform (both include the Kafka Streams application reset tool)
• Clone the confluentinc/tutorials repository and navigate into its top-level directory:

  git clone git@github.com:confluentinc/tutorials.git
  cd tutorials

Create Confluent Cloud resources

Login to your Confluent Cloud account:

confluent login --prompt --save

Install a CLI plugin that will streamline the creation of resources in Confluent Cloud:

confluent plugin install confluent-quickstart

Run the plugin from the top-level directory of the tutorials repository to create the Confluent Cloud resources needed for this tutorial. Note that you may specify a different cloud provider (gcp or azure) or region. You can find supported regions in a given cloud provider by running confluent kafka region list --cloud <CLOUD>.

confluent quickstart \
  --environment-name kafka-streams-schedule-operations-env \
  --kafka-cluster-name kafka-streams-schedule-operations-cluster \
  --create-kafka-key \
  --kafka-java-properties-file ./kafka-streams-schedule-operations/kstreams/src/main/resources/cloud.properties

The plugin should complete in under a minute.

Create topics

Create the input and output topics for the application:

confluent kafka topic create punctuation-input
confluent kafka topic create punctuation-output

Start a console producer:

confluent kafka topic produce punctuation-input --parse-key --delimiter :

Enter a few JSON-formatted login events:

user-1:{"logInTime":5, "userId":"user-1", "appId":"app-1"}
user-2:{"logInTime":5, "userId":"user-2", "appId":"app-1"}
user-1:{"logInTime":5, "userId":"user-1", "appId":"app-1"}
user-3:{"logInTime":5, "userId":"user-3", "appId":"app-1"}
user-2:{"logInTime":5, "userId":"user-2", "appId":"app-1"}

Enter Ctrl+C to exit the console producer.

Compile and run the application

Compile the application from the top-level tutorials repository directory:

./gradlew kafka-streams-schedule-operations:kstreams:shadowJar

Navigate into the application's home directory:

cd kafka-streams-schedule-operations/kstreams

Run the application, passing the Kafka client configuration file generated when you created Confluent Cloud resources:

java -cp ./build/libs/kafka-streams-schedule-operations-standalone.jar \
    io.confluent.developer.KafkaStreamsPunctuation \
    ./src/main/resources/cloud.properties

Validate that you see a punctuated max login event in the punctuation-output topic.

confluent kafka topic consume punctuation-output -b \
  --print-key --delimiter : --value-format integer

You should see output like:

user-1 @Tue Sep 16 11:36:01 EDT 2025:5

Clean up

When you are finished, delete the kafka-streams-schedule-operations-env environment by first getting the environment ID of the form env-123456 corresponding to it:

confluent environment list

Delete the environment, including all resources created for this tutorial:

confluent environment delete <ENVIRONMENT ID>

docker compose -f ./docker/docker-compose-kafka.yml up -d

docker exec -it broker /bin/bash

kafka-topics --bootstrap-server localhost:9092 --create --topic punctuation-input
kafka-topics --bootstrap-server localhost:9092 --create --topic punctuation-output

kafka-console-producer --bootstrap-server localhost:9092 --topic punctuation-input \
    --property "parse.key=true" --property "key.separator=:"

user-1:{"logInTime":5, "userId":"user-1", "appId":"app-1"}
user-2:{"logInTime":5, "userId":"user-2", "appId":"app-1"}
user-1:{"logInTime":5, "userId":"user-1", "appId":"app-1"}
user-3:{"logInTime":5, "userId":"user-3", "appId":"app-1"}
user-2:{"logInTime":5, "userId":"user-2", "appId":"app-1"}

./gradlew kafka-streams-schedule-operations:kstreams:shadowJar

cd kafka-streams-schedule-operations/kstreams

java -cp ./build/libs/kafka-streams-schedule-operations-standalone.jar \
    io.confluent.developer.KafkaStreamsPunctuation \
    ./src/main/resources/local.properties

kafka-console-consumer --bootstrap-server localhost:9092 --topic punctuation-output --from-beginning \
  --property "print.key=true" --property "key.separator=:" \
  --property "value.deserializer=org.apache.kafka.common.serialization.IntegerDeserializer"

user-1 @Tue Sep 16 11:36:01 EDT 2025:5

docker compose -f ./docker/docker-compose-kafka.yml down