# Monitoring and Cost — Vector Databases

Source: https://www.geekswithgeeks.com/en/vector-databases/s-monitor

> Watch quality, latency, freshness and spending.

## Four dashboards

Track **quality**: recall@k on a rolling golden set or sampled queries against exact search, "no result" rate, and user feedback. Track **performance**: p50/p95/p99 latency, queries per second, error rate, queue depth, CPU and memory, cache hit rate. Track **freshness**: ingestion lag and the delay between write and searchability. Track **cost**: memory per vector, embedding fees (indexing and per query), storage, replicas, and cost per 1,000 queries. Alert on regressions such as a recall drop after an upgrade, latency spikes at specific filters, memory approaching limits, replica lag, and failed ingestion batches. Review the slowest and worst-recall queries regularly; they point to missing indexes, bad filters or data problems. Before each engine or index parameter change, rerun the benchmark and the golden set.

**Quiz:** Which metric catches a silent loss of search quality after an upgrade?

- [x] Recall@k on a golden set or sampled queries vs exact search
- [ ] Server uptime alone
- [ ] CPU temperature
- [ ] Number of tables

*Answer:* Recall@k on a golden set or sampled queries vs exact search. Uptime can be perfect while results quietly get worse.