CQRS

Introduction

What is CQRS? CQRS separates command writes from query reads.

Understanding the topic

What happens — CQRS:

• Define RPO/RTO and data sovereignty.
• Replicate selected topics cross-cluster.
• Plan failover and conflict handling.
• Capacity-plan for peak + replay.

Visual explanation

Pipeline view:

Region A Kafka
  ↓ replicate selected topics
Region B Kafka
  ↓
local consumers + DR plan
Trade-off: latency, cost, consistency

Step-by-step explanation

1. Design — Clusters, topics, mapping.
2. Replicate — MM2 or cluster link.
3. Failover — Test DR runbooks.
4. Govern — Schema and ownership.

Informative example

Example:

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

Execution workflow

Best practices

• Define RPO/RTO before choosing replication design.
• Replicate only topics with clear ownership and purpose.
• Document failover and failback procedures.
• Model event sourcing around immutable business facts.

Common mistakes

• Bi-directional replication without loop/conflict strategy.
• Event sourcing every table instead of meaningful domain events.
• Ignoring replay cost during capacity planning.

Summary

CQRS — Make trade-offs explicit: RPO/RTO, ordering, sovereignty, replay cost, schema governance, and operational ownership.