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How to build Apache Kafka

Distributed event streaming platform for real-time data pipelines, message queues, and event sourcing.

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Features (10)

Publish-subscribe messaging

Distributed partitioned log

Consumer groups

Kafka Streams (stream processing)

Kafka Connect (integrations)

Schema Registry

Exactly-once semantics

Compacted topics

Mirror Maker (replication)

KSQL (streaming SQL)

User Stories (5)

As a developer, I can publish events to topics

As a data engineer, I can build real-time data pipelines

As a developer, I can process streams with Kafka Streams

As a team, I can connect to databases with Kafka Connect

As an architect, I can implement event sourcing patterns

Suggested Tech Stack

JavaScalaZooKeeperKRaftJVMREST ProxySchema RegistryDockerKubernetes

Non-Functional Requirements

Category	Requirement	Target
Performance	Throughput	1M+ messages/sec per broker
Performance	Latency	< 5ms P99 for produce acknowledgment
Scalability	Cluster	1000+ brokers, petabytes of data
Availability	Cluster	99.999% with replication factor 3

Release Milestones

MVPMessage Broker

TopicsPartitionsConsumer groupsReplicationLog compaction

v1.0Streaming

Kafka StreamsKafka ConnectSchema RegistryExactly-onceREST Proxy

v2.0Self-Managed

KRaft (no ZooKeeper)Tiered storageKSQLMirror Maker 2Quotas

Success Metrics

Adoption: > 80% of Fortune 100

Messages processed per day: > 7T (LinkedIn alone)

Confluent Cloud revenue: > $500M ARR

Community contributors: > 1K

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