Hi everyone, Has anyone benchmarked memory usage for a MySQL → Flink CDC → Iceberg pipeline at scale? I’m trying to establish a baseline for estimating Flink TaskManager memory requirements per table, considering factors such as: • Number of columns and their data types • Peak CDC throughput (records/sec) I’m curious how others in production or large-scale deployments approach this. Do you use any rule of thumb or estimation model based on these metrics, or is load testing the only reliable way to determine memory requirements? If anyone has done similar benchmarking or has shared benchmark results, it would be great to hear about your approach and findings. Thanks!

I haven’t done this kind of benchmarking, but in principle, since Flink CDC processes data split by split, the key factor is the memory required for a single split. Therefore, you should pay particular attention to memory usage for the widest large tables—that is, tables with the most columns or the most memory-intensive data types.