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.
Profile →npx skills add github/awesome-copilot --skill memory-usage-optimization --agent copilot
Same command for any agent — swap --agent for claude-code, codex, cursor.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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/). <!-- ToDo: Talk about memory usage of each components once API is available --> ## How much memory is needed for Qdrant? Optimal memory usage depends on the use case. - For regular search scenarios, general guidelines are provided in the [Capacity planning docs](https://search.qdrant.tech/md/documentation/operations/capacity-planning/). For a detailed breakdown of memory usage at large
- Memory usage monitoring
- How much memory is needed for Qdrant?
- When to put HNSW index on disk
- How to minimize memory footprint
What does the qdrant-memory-usage-optimization skill do?
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.
How do I install it?
Run `npx skills add github/awesome-copilot --skill memory-usage-optimization --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From github/awesome-copilot, a repository with 37,432 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.