News, guides, and engineering deep dives.
Practical guidance on Kafka, Flink, Iceberg, and real-time data.
Kafka topics
A Kafka topic is a named, append-only log, and in production it is the unit you operate on. The CLI verbs, partition and replication mechanics, retention, compaction and the troubleshooting moves.
A Kafka topic example, fully specified
A production Kafka topic example: the exact creation command with durability properties, the same topic as Terraform and Strimzi code, the naming convention that scales, and the schema contract.
Kafka topic vs partition
A topic is the logical name; a partition is the physical log. How replication, ordering, parallelism and key hashing follow the physical unit, and why keyed topics lock their count.
A production Kafka tutorial
A Kafka tutorial for people who run it in production: zero-downtime upgrades, broker tuning, layered security, troubleshooting signals, and the client settings that decide delivery guarantees.
Kafka use cases
The production Kafka use cases with the numbers behind them: real-time analytics, event-driven microservices, change data capture, event sourcing and log aggregation, plus the business case for each.
Kafka KRaft
KRaft replaces ZooKeeper with a Raft quorum built into Kafka. The migration path and deadlines, controller sizing, the real scale limits, and day-2 operations for KRaft clusters.
ksqlDB on Kafka
ksqlDB is the streaming SQL layer for Kafka: streams and tables in SQL, persistent queries with state in internal topics. The push-vs-pull trap, and where it stands as Confluent shifts to Flink.
Kafka with Spring Boot
Spring Boot integrates with Kafka through spring-kafka: KafkaTemplate, @KafkaListener and auto-configuration. Production setup, dead letter topics, non-blocking retries, and listener tuning.
Dead letter queues in Kafka: a consumer-side, Kafka-only approach
How to implement dead letter queues in Kafka: consumer-side, Kafka-only, scoped per consumer group, and why retry topics for transient failures are an anti-pattern.