Kafka Connect Patterns for Data Engineering on AWS

Key Definitions

• Connector: A component that defines how data is imported or exported from Kafka.
• Task: A unit of work that performs the actual data movement. There can be multiple tasks for a connector.
• Transformations: Operations that modify records before they are written to Kafka or external systems.

Common Patterns

1. Batch Ingestion: Suitable for bulk loading data at scheduled intervals.
2. Streaming Ingestion: Continuous data flow, ideal for real-time analytics.
3. Change Data Capture (CDC): Captures database changes and streams them to Kafka.

Implementing CDC with Kafka Connect

CDC can be achieved using connectors like Debezium, which captures changes from databases and streams them to Kafka.

Example Configuration

{
  "name": "mysql-cdc-connector",
  "config": {
    "connector.class": "io.debezium.connector.mysql.MySqlConnector",
    "tasks.max": "1",
    "database.hostname": "mysql-server",
    "database.port": "3306",
    "database.user": "debezium",
    "database.password": "dbz",
    "database.server.id": "184054",
    "database.server.name": "dbserver1",
    "table.whitelist": "inventory.products",
    "database.history.kafka.bootstrap.servers": "kafka:9092",
    "database.history.kafka.topic": "dbhistory.fullfillment"
  }
}

Tips for Effective Usage

• Monitor connector tasks and performance regularly.
• Use transformations to ensure data quality and structure.
• Implement error handling and logging to capture any issues during ingestion.