[Verse 1] When planning Kafka clusters on Kubernetes ground Three factors multiply to keep your data sound Retention times throughput and replication too Storage requirements calculated just for you Days times gigabytes times copies that you make Equals total storage space your cluster needs to take [Chorus] ReTention Throughput Replication multiply Storage sizing made simple reach up to the sky Two gigs CPU four gigs RAM per broker start Network bandwidth doubles when replicas depart Plan your partitions wisely scale your Kafka heart [Verse 2] Each broker needs resources to handle all the load Two CPU cores minimum to walk the data road Four gigabytes of memory baseline for the game More producers more consumers fan the resource flame Scale up with your workload don't leave your brokers dry Monitor and adjust as traffic volumes fly [Chorus] ReTention Throughput Replication multiply Storage sizing made simple reach up to the sky Two gigs CPU four gigs RAM per broker start Network bandwidth doubles when replicas depart Plan your partitions wisely scale your Kafka heart [Bridge] Network flows between the brokers replication stream Double your producer bandwidth living the dream Partition count guidelines keep performance tight Ten thousand max per cluster keeps everything right Balance across your brokers spread the load around Strimzi makes it easier Kafka safe and sound [Verse 3] Start with topic size and growth rate that you see Multiply by replicas two or maybe three Cross-cluster traffic patterns network load design CPU spikes with compression memory aligns Test your calculations in development first Before production traffic puts you to the test [Chorus] ReTention Throughput Replication multiply Storage sizing made simple reach up to the sky Two gigs CPU four gigs RAM per broker start Network bandwidth doubles when replicas depart Plan your partitions wisely scale your Kafka heart [Outro] Capacity planning victory Strimzi shows the way Kafka clusters running strong every single day
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