Qdrant Horizontal Scaling Agent Skill
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.
Install
one command, takes just this skill from the repositorynpx skills add https://github.com/qdrant/skills --skill qdrant-horizontal-scalingThe instruction itself
5 sections, as written by the authorWhat 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: 2for 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_numberthat isn't a multiple of node count (uneven distribution) - Do not use
replication_factor: 1in 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)
Other skills for the same job
different authors, same section of the catalogue
Configure, explore, and optimize Nx monorepo workspaces. Use when setting up Nx, exploring workspace structure, configuring project boundaries, analyzing affected projects, optimizing build caching, or implementing CI/CD with affected commands. Keywords — nx, monorepo, workspace, projects, targets, affected. Do NOT use for running tasks (use nx-run-tasks) or code generation with generators (use nx-generate).
> Design, validate, and optimize schema.org structured data for eligibility, correctness, and measurable SEO impact. Use when the user wants to add, fix, audit, or scale schema markup (JSON-LD) for rich results. This skill evaluates whether schema should be implemented, what types are valid, and how to deploy safely according to Google guidelines.
Fetches real-time Azure retail pricing using the Azure Retail Prices API (prices.azure.com) and estimates Copilot Studio agent credit consumption. Use when the user asks about the cost of any Azure service, wants to compare SKU prices, needs pricing data for a cost estimate, mentions Azure pricing, Azure costs, Azure billing, or asks about Copilot Studio pricing, Copilot Credits, or agent usage estimation. Covers compute, storage, networking, databases, AI, Copilot Studio, and all other Azure service families.
Monitor paid-ad account pacing, delivery, performance, creative fatigue, tracking, policy, and data quality across supported platforms. Use for daily or weekly checks, anomaly review, budget pacing, post-launch verification, or campaign monitoring.
Audit server-side paid-media measurement including server-side tag management, platform conversion APIs, event taxonomy, browser/server deduplication, consent, hashing, data quality, observability, and privacy. Use for server-side tracking, sGTM, server-side tagging, CAPI, Events API, event_id, pixel debugging, first-party measurement, or conversion data loss.
Use when building Next.js 14+ applications with App Router, server components, or server actions. Invoke for full-stack features, performance optimization, SEO implementation, production deployment.
Coordinate the end-to-end CAD/source-asset to SimReady workflow. Use for broad requests such as CAD to SimReady, source asset to simulation-ready USD, or prop packaging that require conversion, material/physics assignment, SimReady conformance, validation, and optional package creation; deploy or verify Content Agents services first when property assignment is enabled; route single-stage work through nested references.
Convert Kanchi-style dividend investing into a repeatable US-stock operating procedure. Use when users ask for かんち式配当投資, dividend screening, dividend growth quality checks, PERxPBR adaptation for US sectors, pullback limit-order planning, or one-page stock memo creation. Covers screening, deep dive, entry planning, and post-purchase monitoring cadence.
How to use it
Take qdrant/qdrant-horizontal-scaling from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.