This DEV Community guide presents 33 essential Kafka interview questions for aspiring data engineers, AI, and backend developers. Structured by difficulty, it covers core concepts like distributed event-streaming, topics, partitions, and consumer groups. The guide addresses critical operational aspects including delivery semantics (at-least-once vs. exactly-once), fault tolerance via replication and leader election, and performance optimization techniques like zero-copy and sequential writes.

Real-world scenarios focus on ensuring message ordering, handling duplicates, and reprocessing data, while the AI section explains Kafka's role in ML pipelines for real-time feature ingestion and streaming inference. This resource is vital for mastering the de facto standard for real-time data pipelines.