Individual skill
qdrant-memory-usage-optimization
Diagnoses and reduces Qdrant memory usage. Use when someone reports 'memory too high', 'RAM keeps growing', 'node crashed', 'out of memory', 'memory leak', or asks 'why is memory usage so high?', 'how to reduce RAM?'. Also use when memory doesn't match calculations, quantization didn't help, or nodes crash during recovery.
skills/qdrant-performance-optimization/memory-usage-optimization/SKILL.md
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- Last checked
- Nov 4, 2026
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- Repository last updated
- Nov 6, 2026
- License
- MIT
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# 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 must stay in RAM, such as quantized vectors when `always_ram=true` and payload indexes.
- 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.
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](https://search.qdrant.tech/md/documentation/operations/monitoring/).
