Module Review

In this final module of the Kafka course, we looked at how to integrate Kafka into the wider enterprise and ensure long-term data quality:

  1. Kafka Connect: Moving data in and out of Kafka using pre-built Source and Sink connectors (e.g., Debezium, S3, Elasticsearch).
  2. Schema Registry: Enforcing formal data contracts with Avro/Protobuf to prevent “Topic Poisoning.”
  3. Evolution Rules: Understanding the difference between Backward, Forward, and Full compatibility to allow schemas to change over time without breaking applications.

1. Flash Quiz

1. What is the difference between a “Source Connector” and a “Sink Connector”?

  • Source: Moves data from an external system INTO Kafka. Sink: Moves data FROM Kafka into an external system.

2. Why is “Debezium” a popular choice for database ingestion?

  • Because it uses Change Data Capture (CDC) to read the database transaction logs, which is much faster and more accurate than periodic polling.

3. What happens if a producer tries to send a message that doesn’t match the registered schema?

  • The write is rejected by the producer client or the Schema Registry, preventing invalid data from entering the Kafka topic.

4. What is “Backward Compatibility”?

  • It means a new schema can be used to read data that was written using a previous version of the schema.

5. How do you ensure a new field is Backward Compatible in Avro?

  • By giving the new field a Default Value.

2. Final Congratulations!

You have completed the High-Performance Event Streaming with Kafka curriculum. You’ve gone from low-level broker internals and replication to high-level stream processing with Kafka Streams and enterprise integration with Connect and Schema Registry. You are now ready to design and build world-class event-driven architectures.