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.
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).
replication_factor: 2 for zero-downtime scalingMinimum 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.
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.
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.
Better alternatives: over-provision shards initially, or spin up new cluster with correct config and migrate data.
shard_number that isn't a multiple of node count (uneven distribution)replication_factor: 1 in production if you need fault toleranceCopy a source-pinned command for your client. You run it yourself.
Destination: .claude/skills/horizontal-scaling · pinned to the source commit
# Run from your project root
git clone https://github.com/github/awesome-copilot.git .skillboard-tmp
git -C .skillboard-tmp checkout f11a4e441c5ff061b4f8ae37952be8c602e4034e
mkdir -p ".claude/skills"
cp -r ".skillboard-tmp/skills/qdrant-scaling/scaling-data-volume/horizontal-scaling" ".claude/skills/"
rm -rf .skillboard-tmpReview the source before running. This copies files into your project; it is not a one-click install and does not verify runtime safety.
sudo apt update && sudo apt install -y gitnpm install -g @anthropic-ai/claude-code# Run from your project root
git clone https://github.com/github/awesome-copilot.git .skillboard-tmp
git -C .skillboard-tmp checkout f11a4e441c5ff061b4f8ae37952be8c602e4034e
mkdir -p ".claude/skills"
cp -r ".skillboard-tmp/skills/qdrant-scaling/scaling-data-volume/horizontal-scaling" ".claude/skills/"
rm -rf .skillboard-tmpDestination: .claude/skills/horizontal-scaling
Scanner static-checks@0.1.0 · commit f11a4e441c5f. Static checks cannot prove runtime safety – review the source and the exact diff before installing. How checks work.
No static rules matched. This is not a safety guarantee.