Why traditional Kafka tuning fails at financial scale and how ML can automate it on AWS MSK

Most Kafka tuning guides assume you can manually adjust configs like num.partitions, replication.factor, and consumer lag thresholds. That works fine at moderate scale. But in high-volume financial systems processing millions of transactions per second, manual tuning breaks down for a few reasons: **The core problems:** - Financial workloads are bursty and unpredictable by nature - By the time a human notices l