qdrant-memory-usage-optimization

Installation
SKILL.md

Understanding memory usage

Qdrant operates with two types of memory:

  • Resident memory (aka RSSAnon) - memory used for internal data structures like the ID tracker, plus components that stay fully in RAM. On Qdrant 1.19 or newer this is controlled per-component with memory: pinned (e.g. quantized vectors, payload indexes); on 1.18 or older the equivalent is always_ram: true.

  • OS page cache - memory used for caching disk reads, which can be released when needed. Original vectors are normally stored in page cache, so the service won't crash if RAM is full, but performance may degrade. On Qdrant 1.19 or newer this corresponds to memory: cached (pre-warmed into page cache at startup) or memory: cold (lazy disk reads, not pre-warmed); on 1.18 or older it's controlled via the on_disk boolean on vectors, HNSW config, sparse vector index, and payload index. See Memory Tiers docs (available on 1.19+).

It is normal for the OS page cache to occupy all available RAM, but if resident memory is above 80% of total RAM, it is a sign of a problem.

Memory usage monitoring

  • Qdrant exposes memory usage through the /metrics endpoint. See Monitoring docs.

How much memory is needed for Qdrant?

Installs
8
Repository
qdrant/skills
GitHub Stars
220
First Seen
Apr 12, 2026
qdrant-memory-usage-optimization — qdrant/skills