What It Is
Producers write events to named topics, which are split into partitions and replicated across brokers. Consumers read at their own pace, and many applications can read or replay the same stream.
Key Points
- Topics and partitions: the unit of organization and parallel scale.
- Replication: fault tolerance across brokers.
- Retention: data stays available for replay.
- Throughput: a single cluster can handle millions of messages per second.
Why It Matters
Kafka is the backbone of event-driven systems, from log collection to change data capture. Good operation needs careful choices about partitions, replication, retention, and consumer groups.
How ClearLeaff Applies It
Kafka is central to the streaming platforms we design and operate. Paired with Apache Flink, it moves more than one million events per second while keeping data quality and observability in place from the first event to the final dashboard.