Data Engineering · Streaming

Apache Kafka Tutorials

Learn Apache Kafka from the ground up — how topics, partitions, producers and consumers work, how to build event-driven pipelines, and how Kafka fits alongside Apache Spark in a modern real-time data stack.

Core concepts

  • Topics, partitions & offsets
  • Producers and consumer groups
  • Replication, brokers & the commit log
  • Delivery guarantees (at-least-once, exactly-once)

Streaming & processing

  • Kafka Streams & ksqlDB basics
  • Windowing & stateful processing
  • Schema Registry & Avro
  • Structured Streaming from Kafka in PySpark

Real-world pipelines

  • Event-driven architecture patterns
  • Change data capture (CDC) with Debezium
  • Kafka → Spark → data lake ingestion
  • Monitoring, lag & scaling consumers