Capacity Planning

Introduction

What is Capacity Planning? Capacity planning estimates throughput, retention, replication, partitions, broker count, disk, network, and growth headroom.

Understanding the topic

What happens — Capacity Planning:

• 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:

Topic partitions
  ↓
replicas across brokers
  ↓
ISR health
  ↓
disk + network + controller
  ↓
SLO dashboards

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

Execution workflow

Best practices

• Use replication factor 3 for critical topics.
• Set min.insync.replicas with acks=all.
• Alert on under-replicated partitions, offline partitions, disk usage, and lag.
• Document topic ownership and cleanup policy.

Common mistakes

• Changing partitions without understanding ordering impact.
• Ignoring hot partitions caused by skewed keys.
• Letting retention grow until disks become the outage.

Summary

Capacity Planning — Operate Kafka through SLOs: durability, availability, latency, lag, disk headroom, and recovery time.