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Databases · Devops / AGENT SKILL
qdrant-scaling
0
Plan Qdrant capacity, sharding, and scaling to address throughput, latency, and retention needs.
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'.
Understand the trade-offs.
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The full skill.
Original instructions from the publisher’s SKILL.md
# 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 says | Read | |---|---| | Data does not fit on a single node, running out of disk or memory as the dataset grows | `scaling-data-volume/SKILL.md` | | Need to shard the collection across more nodes, data outgrew one node | `scaling-data-volume/SKILL.md` | | Cannot handle enough parallel queries, need higher QPS or throughput | `scaling-qps/SKILL.md` | | Can't hold the request rate, CPU is pegged | `scaling-qps/SKILL.md` | | A single query is too slow, need to cut the tail latency of individual requests | `minimize-latency/SKILL.md` | | p99 or tail latency too high, but traffic/QPS is fine | `minimize-latency/SKILL.md` | | Queries return very large result sets and slow down | `scaling-query-volume/SKILL.md` | | Large `limit`, top-1000 queries, pagination, scroll across shards | `scaling-query-volume/SKILL.md` | | Many tenants or customers, one collection each, tenant isolation | `scaling-data-volume/tenant-scaling/SKILL.md` | | Only recent data matters, retention, expiring old vectors, time-based rotation | `scaling-data-volume/sliding-time-window/SKILL.md` | | Single node no longer fits the workload, before deciding to shard | `scaling-data-volume/vertical-scaling/SKILL.md` | | Already vertically maxed out, need more nodes, resharding | `scaling-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.