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This guide will walk you through installing Kanal and building your first streaming pipeline.

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Installation

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Option 1: Docker Compose

Create a docker-compose.yml file with your Kafka configuration: 
services:
  kanal:
    image: streemlined/kanal:latest
    ports:
      - "8080:8080"
    environment:
      KAFKA_BOOTSTRAP_SERVERS: localhost:9092
      # Authentication (optional)
      KAFKA_SECURITY_PROTOCOL: SASL_PLAINTEXT
      KAFKA_SASL_MECHANISM: PLAIN
      KAFKA_SASL_JAAS_CONFIG: >
        org.apache.kafka.common.security.plain.PlainLoginModule required
        username="admin"
        password="secret";
Run Kanal with Docker Compose: 
docker compose up -d

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Option 2: Download the JAR

Download the latest release and run it directly: 
# Download the latest release
curl -LO https://github.com/streemlined/kanal/releases/latest/download/kanal.jar
Before running Kanal, you need to configure your Kafka cluster. Create an application.yml file: 
kafka:
  bootstrap.servers: localhost:9092
  
  # Authentication (optional)
  security.protocol: SASL_PLAINTEXT
  sasl.mechanism: PLAIN
  sasl.jaas.config: >
    org.apache.kafka.common.security.plain.PlainLoginModule required
    username="admin"
    password="secret";
Then run Kanal with the configuration file: 
java -jar kanal.jar -Dmicronaut.config.files=application.yml

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Access the Editor

Once Kanal is running, open your browser and navigate to: 
http://localhost:8080/ui
You should see the visual pipeline editor.

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Build Your First Pipeline

Let’s create a simple pipeline that reads from a Kafka topic, transforms the data, and writes to a database.
1

Add a Kafka Consumer

Drag a Kafka Consumer node onto the canvas from the left sidebar.Configure it:
  • Topic: orders
  • Schema Type: JSON or AVRO_SR if using Schema Registry
2

Add a Transform Node

Drag a Transform node onto the canvas and connect it to your Kafka Consumer.Add a JSONata expression to transform the data:
{
  "order_id": id,
  "customer_name": customer.name,
  "total_amount": items.price ~> $sum(),
  "processed_at": $now()
}
See Transformations for more on JSONata.
3

Add a JDBC Sink

Drag a JDBC Sink node onto the canvas and connect it to the Transform node.Configure it:
  • Database: Select your configured database
  • Table: processed_orders
4

Run the Pipeline

Click the Play button in the toolbar to start the pipeline.Monitor the throughput and any errors in the metrics panel.

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Verify It’s Working

You can verify your pipeline is working by:
  1. Producing test messages to your Kafka topic
  2. Checking the metrics in the Kanal UI
  3. Querying your database to see the processed records
# Produce a test message (using kafka-console-producer)
echo '{"id": 1, "customer": {"name": "Alice"}, "items": [{"price": 10}, {"price": 20}]}' | \
  kafka-console-producer --topic orders --bootstrap-server localhost:9092

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What’s Next?

Core Concepts

Understand pipelines, nodes, and JSONata

Visual Editor

Master the pipeline editor

Nodes Reference

Explore all available nodes