2.Kafka

A version-neutral Kafka local setup guide that distinguishes modern KRaft deployments from historical ZooKeeper-based instructions.

Kafka as a distributed durable event log for messaging, storage, replay, and stream processing.

A compact Kafka workflow for topics, producers, consumers, groups, offsets, and administration without freezing the note to one old CLI syntax.

Kafka producers, partition leaders/followers, brokers, consumers, KRaft metadata quorum, replication, failover, and partitioned scaling.

Kafka producer batching, serialization, partitioning, acknowledgements, retries, idempotent production, transactions, and their exact scope.

Kafka broker responsibilities, modern controllers, ISR/min.insync.replicas, producer acknowledgements, leader election, and durability trade-offs.

Kafka consumer groups, partition assignment, offsets, rebalancing, at-least-once processing, idempotency, and modern cooperative rebalancing considerations.

Kafka partition log segments, sparse indexes, retention vs. compaction, page cache, sequential I/O, batching, and zero-copy-related transport efficiency.

Kafka topic/partition semantics, per-partition ordering, offsets, replication, ISR, high watermark, retention, and reassignment.

Kafka tuning as a balance among throughput, latency, durability, batching, compression, partition count, storage, and consumer lag.

How to benchmark Kafka producer, broker, and consumer capacity with realistic record sizes, partitions, replication, acknowledgements, compression, and end-to-end lag.

What managed Kafka services operate for you, what semantics remain your responsibility, and how to evaluate compatibility, networking, scaling, and cost.

A value-first route through Kafka source: protocol requests, producer batching, broker append/fetch, replication, group coordination, and KRaft metadata.