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Databases40k · #5309

qdrant-horizontal-scaling

Helps your agent decide how to add more nodes to Qdrant. Use when you need more capacity or data is growing too much.

What it does

Helps you decide whether to expand your Qdrant database by adding more machines (horizontal) or improving the current one (vertical). It guides on how many nodes and shards to use for good performance and reliability.

When to use it

  • ✓When your data grows too large for a single machine.
  • ✓If you need your system to keep running even if one machine fails.
  • ✓To divide your data and users into smaller groups for better management.

Example of what to ask your AI

“My data no longer fits on one machine, should I add more machines or upgrade the current one? How many nodes and shards should I use?”

Want more? Open the sections below.

How to use

The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.

Skill link

https://github.com/github/awesome-copilot/blob/main/skills/qdrant-scaling/scaling-data-volume/horizontal-scaling/SKILL.md

Ready-to-paste message

Use this skill to help me: https://github.com/github/awesome-copilot/blob/main/skills/qdrant-scaling/scaling-data-volume/horizontal-scaling/SKILL.md Read the SKILL.md file at that link and follow its instructions for my task.
How it works

This tool analyzes if you need more capacity and suggests the best way to scale your Qdrant. It considers whether you should add more machines or improve the existing one, and recommends the ideal number of shards and replicas to ensure your data is safe and accessible.

Installation

Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.

In the terminal (Claude Code, Codex, Cursor), in your project folder:

npx skills add github/awesome-copilot --skill qdrant-horizontal-scaling

Or download just the file:

curl -L https://raw.githubusercontent.com/github/awesome-copilot/main/skills/qdrant-scaling/scaling-data-volume/horizontal-scaling/SKILL.md -o SKILL.md
Technical content (original SKILL.md)

Original text by the author, straight from GitHub.

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)
FAQ

What is horizontal scaling?

It's when you add more machines (nodes) to distribute the workload and data, instead of just upgrading a single machine.

Why is 3 nodes the minimum recommended?

With 3 nodes, the system can continue operating even if one machine fails. With only 2, losing a machine causes downtime for operations.

What are shards and replicas?

Shards are parts of your data. Replicas are copies of these shards. Having multiple copies (replication) ensures your data isn't lost and the system keeps running if a machine fails.

Details

Original description by the author

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.

repo: github/awesome-copilot

Popularity

GitHub stars
40k
Ranking position
#5309
License
MIT
Updated
10/15/2026

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