How to Scale Kafka (for your System Design Interview)

🚨 𝗧𝗵𝗲 big 𝗱𝗮𝘆 is coming! Your e-commerce system processes 1,000 orders/second on a normal day and suddenly it's 50,000 orders/second. How do you scale Kafka?

🧩 𝗔𝗱𝗱 𝗽𝗮𝗿𝘁𝗶𝘁𝗶𝗼𝗻𝘀 𝗳𝗼𝗿 𝗽𝗮𝗿𝗮𝗹𝗹𝗲𝗹 𝗽𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴

Partitions are independent, ordered logs. Each partition guarantees order within itself. Customer A's orders in partition 7 stay in sequence, while Customer B's orders in partition 23 process in parallel. More partitions = more throughput.

👥 𝗦𝗰𝗮𝗹𝗲 𝗰𝗼𝗻𝘀𝘂𝗺𝗲𝗿 𝗴𝗿𝗼𝘂𝗽𝘀

You can have up to one consumer per partition. With 50 partitions, you can run up to 50 parallel consumers. Each sees events in order within their partition. Need more parallelism? Add partitions.

🖥️ 𝗦𝗰𝗮𝗹𝗲 𝗯𝗿𝗼𝗸𝗲𝗿𝘀 𝗵𝗼𝗿𝗶𝘇𝗼𝗻𝘁𝗮𝗹𝗹𝘆

Brokers are Kafka servers that host partitions. Running 50 partitions on 3 brokers? Add more brokers to spread the load. Kafka automatically rebalances partitions across all brokers.

𝗧𝗵𝗲 𝗸𝗲𝘆 𝘁𝗿𝗮𝗱𝗲𝗼𝗳𝗳: More partitions = more throughput BUT ordering only within each partition, not globally. Don't forget this!