Intermediate LevelSystem Design & Architecture
How do Apache Kafka Partitions, Log Segments, and Consumer Groups scale message streaming?
❓ Interview Prompt: Explain Apache Kafka, Topics, Partitions, Consumer Groups, Message Keys, offset tracking, and strict ordering guarantees.
Apache Kafka is a distributed, append-only event streaming platform:
Scaling Mechanics:
1
Topic Partitions: Topics are divided into partitions distributed across brokers. Messages with the same key route to the same partition, guaranteeing strict message ordering per partition.
2
Consumer Groups: Multiple consumers share topic reading load. Kafka assigns each partition to exactly ONE consumer within a consumer group to parallelize consumption.
Code Implementation Example
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Kafka Partitioning and Consumer Group Architecture:
[Topic: 'payment_events']
├── [Partition 0] ──> [Consumer 1 (Group A)]
├── [Partition 1] ──> [Consumer 2 (Group A)]
└── [Partition 2] ──> [Consumer 3 (Group A)]💡Kafka topic partitions assigned to parallel consumers in a Consumer Group.
🎯 Interview Key Takeaway
Design Kafka topics with message keys to guarantee per-partition ordering while scaling processing across consumer groups.
#System Design#Kafka#Partitions#Consumer Groups#Intermediate
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