Kafka Use Cases

Introduction

What is Kafka Use Cases? Kafka is used for event-driven microservices, activity streams, CDC pipelines, analytics ingestion, audit logs, fraud detection, notifications, and data integration.

Understanding the topic

What happens — Kafka Use Cases:

• Microservices decouple via events.
• Analytics ingests streams in real time.
• CDC syncs databases to data lakes.
• Audit and fraud pipelines retain immutable logs.

Visual explanation

Pipeline view:

Input topic
  ↓
filter/map/join/window
  ↓
state store + changelog
  ↓
output topic

Step-by-step explanation

1. Identify pattern — Match use case to pub/sub, CDC, or streaming.
2. Design topics — Name events and pick keys.
3. Integrate — Connect producers and consumers.
4. Operate — Monitor lag, retention, and schemas.

Informative example

Example:

kafka-topics --bootstrap-server localhost:9092 --create --topic kafka-use-cases --partitions 6 --replication-factor 3
kafka-console-producer --bootstrap-server localhost:9092 --topic kafka-use-cases
kafka-console-consumer --bootstrap-server localhost:9092 --topic kafka-use-cases --from-beginning
kafka-consumer-groups --bootstrap-server localhost:9092 --describe --group kafka-use-cases-service

Execution workflow

Best practices

• Choose keys before joins and aggregations.
• Name internal topics and state stores clearly.
• Test topology with realistic ordering and late events.
• Monitor processing latency, commit rate, and restore time.

Common mistakes

• Unexpected repartition topics from wrong key choices.
• Ignoring late-arriving events in windows.
• Underestimating state-store disk and restore time.

Summary

Kafka Use Cases — Design topology around keys, state stores, window boundaries, changelog topics, and exactly-once needs.