Tutorials System Design Tutorial
Kafka for Event Streaming — Complete Guide
Kafka for Event Streaming — Complete Guide: free step-by-step lesson with examples, common mistakes, and interview tips — part of System Design Tutorial on Toolliyo Academy.
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System Design Tutorial · Lesson 47 of 100
Kafka for Event Streaming
Basics ✓ → Scale → Interview
Scale · 2 — Distributed · ~6 min · Module 5: Microservices and Event-Driven Systems
What is this?
Kafka is a durable, partitioned log for high-throughput events — producers append, consumers read at their pace with offsets.
Why should you care?
ShopNest needs many subscribers to order_placed (inventory, email, analytics) without coupling them in one request.
See it live — copy this example
Sketch the architecture on paper. These lessons focus on concepts and trade-offs.
Topic: shopnest.orders.v1 partitions=12 key=userId
Producer: order_placed JSON
Consumers: inventory-group, email-group, analytics-group
Replay: reset offsets to reprocess (carefully)Run Example »
This lesson uses terminal or setup steps. Run commands on your computer — the live editor appears on coding lessons.
What happened?
- Keys keep a user’s events ordered in a partition.
- Consumer groups scale readers.
- Retention lets you replay.
- Compaction helps changelog topics.
Practice next
- Create an orders topic keyed by userId.
- Add two consumer groups.
- Document payload schema version.
- Compact a product-changelog topic.
- Add dead-letter topic for poison messages.
Remember
Kafka = durable event log. Partition for scale + ordering key. Lag is a first-class metric.
ShopNest order stream
Multiple groups consume order_placed independently.
Outcome: Email outage does not block inventory updates.
Interview prep for this lesson
Practice these questions aloud after reading—each links to a full structured answer.
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