Which documents remain resident after Couchbase Server reaches its low-water mark?

Which documents remain resident after Couchbase Server reaches its low-water mark?

The goal is to understand the residency behavior of documents in a Couchbase bucket when memory pressure triggers the managed cache ejection policy.

Couchbase Server keeps keys and metadata resident while values may be ejected based on an NRU policy once the bucket’s low‑water mark is exceeded. However, the server does not expose a per‑document guarantee about which values stay in RAM, and the effective working set is further reduced by metadata and service overhead, making the relationship between bucket quota and resident data non‑trivial.

Operators must decide whether to increase the RAM quota, reduce the working set, or accept higher read latency, but the decision is complicated by version‑dependent water‑mark defaults, varying overhead, and the lack of a deterministic residency rule.

Which document characteristics (size, access frequency, mutation pattern) affect the likelihood of staying resident after ejection?
Can operators predict the resident set using only bucket‑level counters and workload metrics?
Does raising the RAM quota proportionally increase the number of resident documents, or does the ejection policy shift the threshold in a non‑linear way?