How should I configure clustering for IVF to balance indexing time vs query performance?

The clustering overhead is a one-time cost that pays dividends at query time, but configure it wrong and you'll either waste compute or get poor results. Use k = sqrt(N) clusters as your baseline where N is your dataset size. However, adjust based on your update patterns: If you rebuild indexes nightly, use k = N/50 for better query performance (more clusters = smaller search spaces). If you're doing incremental updates throughout the day, use k = sqrt(N)/2 to reduce reindexing overhead.

Critical implementation detail: when your clusters become imbalanced (some have 10x more vectors than others), your worst-case query time approaches flat indexing. Monitor cluster sizes and trigger rebalancing when max_cluster_size > 3 * average_cluster_size. Also set nprobe (number of clusters to search) dynamically: start with nprobe=1 for speed, but if recall drops below your threshold, increment until you hit your accuracy target.