Explain how Kafka works
Quick Overview
This question evaluates understanding of Kafka and distributed streaming system concepts, covering core entities (broker, topic, partition, producer, consumer, consumer group), append-only message storage and offsets, scalability via partitioning, fault tolerance via replication and leader/follower roles, delivery semantics (at-most-once, at-least-once, effectively/exactly-once), ordering guarantees, and failure behaviors like broker/consumer failures and rebalancing. It is commonly asked to assess architectural reasoning about durability, throughput, ordering, and failure handling within the Software Engineering Fundamentals and distributed systems/messaging domain, testing both high-level conceptual understanding and practical application details.
Prompt
Explain how Apache Kafka works at a high level and then in more detail.
Cover at least:
- Core entities: broker , topic , partition , producer , consumer , consumer group
- How messages are stored (append-only log) and how offsets work
- How Kafka achieves scalability (partitioning) and fault tolerance (replication, leader/follower)
- Delivery semantics: at-most-once , at-least-once , and what is required for effectively/exactly-once processing
- Ordering guarantees (what is ordered and what is not)
- What happens during failures (broker failure, consumer failure, rebalance)
You may assume a typical multi-broker Kafka cluster.