Qdrant Horizontal Scaling

作者 qdrant6a03d0ce8f55無授權條款收錄於 2026年10月8日更新於 2026年10月8日

Diagnoses and guides Qdrant horizontal scaling decisions. Use when someone asks 'vertical or horizontal?', 'how many nodes?', 'how many shards?', 'how to add nodes', 'resharding', 'data doesn't fit', or 'need more capacity'. Also use when data growth outpaces current deployment.

僅含說明DevOps & Cloud
AI 產生的概覽

指導 Qdrant 橫向擴充決策:節點數、分片數、複寫因子以及重新分片的取捨。

功能
此技能為 Qdrant 向量資料庫的容量規劃提供諮詢式指引。它說明何時該垂直擴充、何時該橫向擴充,建議以三個節點、三個分片、複寫因子為二的基準分散式設定,並提供三到六個節點叢集的分片數量建議。它也說明何時適合重新分片、其限制以及應避免的做法。
適用情境
當有人詢問該垂直或橫向擴充、該使用多少節點或分片、如何新增節點或如何重新分片時使用。當資料成長超出目前 Qdrant 部署的承載能力或需要更多容量時也適用。
執行需求
不需要指令碼或工具,僅為說明性指引。套用這些建議需已有 Qdrant 部署;由於自架部署不支援重新分片,重新分片相關指引適用於 Qdrant Cloud。

What to Do When Qdrant Needs More Capacity

Vertical first: simpler operations, no network overhead, good up to ~100M vectors per node depending on dimensions and quantization. Horizontal when: data exceeds single node capacity, need fault tolerance, need to isolate tenants, or IOPS-bound (more nodes = more independent IOPS).

Most basic distributed configuration

  • 3 nodes, 3 shards with replication_factor: 2 for zero-downtime scaling

Minimum of 3 nodes is important for consensus and fault tolerance. With 3 nodes, you can lose 1 node without downtime. With 2 nodes, losing 1 node causes downtime for collection operations. Replication factor of 2 means each shard has 1 replica, so you have 2 copies of data. This allows for zero-downtime scaling and maintenance. With replication_factor: 1, zero-downtime is not guaranteed even for point-level operations, and cluster maintenance requires downtime.

Choosing number of shards

Shards are the unit of data distribution. More shards allows more nodes and better distribution, but adds overhead. Fewer shards reduces overhead but limits horizontal scaling.

For cluster of 3-6 nodes the recommended shard count is 6-12. This allows for 2-4 shards per node, which balances distribution and overhead.

Changing number of shards

Use when: shard count isn't evenly divisible by node count, causing uneven distribution, or need to rebalance.

Resharding is expensive and time-consuming, it should be used as a last resort if regular data distribution is not possible. Resharding is designed to be transparent for user operations, updates and searches should still work during resharding with some small performance impact.

But resharding operation itself is time-consuming and requires to move large amounts of data between nodes.

  • Available in Qdrant Cloud Resharding
  • Resharding is not available for self-hosted deployments.

Better alternatives: over-provision shards initially, or spin up new cluster with correct config and migrate data.

What NOT to Do

  • Do not jump to horizontal before exhausting vertical (adds complexity for no gain)
  • Do not set shard_number that isn't a multiple of node count (uneven distribution)
  • Do not use replication_factor: 1 in production if you need fault tolerance
  • Do not add nodes without rebalancing shards (use shard move API to redistribute)
  • Do not scale down RAM without load testing (cache eviction causes days-long latency incidents)
  • Do not hit the collection limit by using one collection per tenant (use payload partitioning)

來源與署名

來源:qdrant/skills位於skills/qdrant-scaling/scaling-data-volume/horizontal-scaling提交6a03d0c

授權條款: 無授權條款

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