The interface is localized. Skill descriptions and documents are machine-translated by AI into your language; code, commands, paths and technical terms stay in the original, and the author's document governs.
Explore skills
Data & research · SKILL.md

qdrant-scaling

qdrant-scaling

Guides Qdrant scaling decisions. Use when someone asks 'how many nodes do I need', 'data doesn't fit on one node', 'need more throughput or QPS', 'CPU is pegged / can't keep up with the request rate', 'one query is slow / p99 or tail latency too high', 'cluster is slow', 'too many tenants', 'vertical or horizontal', 'how to shard', 'need to add capacity', '…

Independent GitHub snapshot · Automated classification · Original documentation governs

Qqdrant / skillsApache-2.0

Skill documentation

GitHub

name: qdrant-scaling description: "Guides Qdrant scaling decisions. Use when someone asks 'how many nodes do I need', 'data doesn't fit on one node', 'need more throughput or QPS', 'CPU is pegged / can't keep up with the request rate', 'one query is slow / p99 or tail latency too high', 'cluster is slow', 'too many tenants', 'vertical or horizontal', 'how to shard', 'need to add capacity', 'large limit / pagination / scroll is slow', or 'only recent data matters / expiring old vectors / retention window'." allowed-tools:

  • Read
  • Grep
  • Glob

Qdrant Scaling

Route first, then answer. Match the user's symptom in the table, Read that file, and answer from it. Do not answer from this page alone: it contains routing only, not the guidance. If two rows match, read both.

The user saysRead
Data does not fit on a single node, running out of disk or memory as the dataset growsscaling-data-volume/SKILL.md
Need to shard the collection across more nodes, data outgrew one nodescaling-data-volume/SKILL.md
Cannot handle enough parallel queries, need higher QPS or throughputscaling-qps/SKILL.md
Can't hold the request rate, CPU is peggedscaling-qps/SKILL.md
A single query is too slow, need to cut the tail latency of individual requestsminimize-latency/SKILL.md
p99 or tail latency too high, but traffic/QPS is fineminimize-latency/SKILL.md
Queries return very large result sets and slow downscaling-query-volume/SKILL.md
Large limit, top-1000 queries, pagination, scroll across shardsscaling-query-volume/SKILL.md
Many tenants or customers, one collection each, tenant isolationscaling-data-volume/tenant-scaling/SKILL.md
Only recent data matters, retention, expiring old vectors, time-based rotationscaling-data-volume/sliding-time-window/SKILL.md
Single node no longer fits the workload, before deciding to shardscaling-data-volume/vertical-scaling/SKILL.md
Already vertically maxed out, need more nodes, reshardingscaling-data-volume/horizontal-scaling/SKILL.md

Latency and throughput pull opposite ways on segment count. For latency, increase segments toward the CPU core count (default_segment_number: 16). For throughput, use fewer and larger segments (default_segment_number: 2). Applying the wrong direction makes the reported problem worse.

Saved skills