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Apache Kafka Deep Dive

🌐 Apache Kafka Deep Dive

Apache Kafka is a distributed event store and stream-processing platform. It is the backbone of modern, real-time data architectures.

🟢 Level 1: Foundations (Topics & Partitions)

1. The Core Entities

  • Topic: A category or feed name to which records are published.
  • Partition: A topic is split into multiple partitions for scalability and parallelism.
  • Producer: Sends data to topics.
  • Consumer: Reads data from topics.

2. The Log Model

Kafka is essentially a distributed, append-only log. Once data is written to a partition, it is assigned a unique Offset and cannot be changed.

🟡 Level 2: Scalability & Reliability

3. Replication

Each partition has multiple copies across different brokers. One is the Leader, others are Followers. This ensures zero data loss if a server fails.

4. Consumer Groups

Allows a group of consumers to divide the work of reading from a topic. Kafka ensures each partition is only read by one consumer in the group.

🔴 Level 3: Advanced Streaming

5. Kafka Streams & KSQL

Process data in real-time as it flows through Kafka.

  • Kafka Streams: A Java/Scala library for stream processing.
  • KSQL: A SQL-like interface to run queries on top of Kafka topics.

6. Schema Registry

Ensures that Producers and Consumers agree on the data format (Avro, Protobuf, or JSON Schema) to prevent broken pipelines.