Which Qdrant Deployment Do I Need?

SkillCloud & infra

This skill helps your AI guide you through choosing the right way to run the Qdrant vector database. When you ask how to deploy Qdrant, it walks you through the options, from running it locally to hosting it in the cloud, so you can pick the setup that fits your project.

Available today. Use it from your connected AI after setup.

After adding the skill, ask your AI something like 'how should I deploy Qdrant' or 'Docker vs cloud for Qdrant'. Mention your needs, such as latency or a new project, and it will walk you through the choices.

Then ask your AI: use the Which Qdrant Deployment Do I Need? skill

What your AI can do with it

  • Explain the ways to deploy Qdrant, from local mode to cloud
  • Compare options like Docker, self-hosted, embedded Qdrant, Qdrant EDGE, and cloud
  • Recommend a deployment when you need the lowest latency
  • Help choose a deployment type for a new project
  • Answer questions like 'how to deploy Qdrant' or 'which deployment option'

What this skill tells your AI

The instructions your AI receives, as published by qdrant/skills in skills/qdrant-deployment-options/SKILL.md and read by ahel’s review.

Start with what you need: managed ops or full control? Network latency acceptable or not? Production or prototyping? The answer narrows to one of four options.

Getting Started or Prototyping

Use when: building a prototype, running tests, CI/CD pipelines, or learning Qdrant.

  • Use local mode (Python only): zero-dependency, in-memory or disk-persisted, no server needed Local mode
  • Local mode data format is NOT compatible with server. Do not use for production or benchmarking.
  • For a real server locally, use Docker Quick start

Going to Production (Self-Hosted)

Use when: you need full control over infrastructure, data residency, or custom configuration.

  • Docker is the default deployment. Full Qdrant Open Source feature set, minimal setup. Quick start
  • You own operations: upgrades, backups, scaling, monitoring
  • Must set up distributed mode manually for multi-node clusters Distributed deployment
  • Consider Hybrid Cloud if you want Qdrant Cloud management on your infrastructure Hybrid Cloud

Going to Production (Zero-Ops)

Use when: you want managed infrastructure with zero-downtime updates, automatic backups, and resharding without operating clusters yourself.

  • Qdrant Cloud handles upgrades, scaling, backups, and monitoring Qdrant Cloud
  • Supports multi-version upgrades automatically
  • Provides features not available in self-hosted: /sys_metrics, managed resharding, pre-configured alerts

Need Lowest Possible Latency

Use when: network round-trip to a server is unacceptable. Edge devices, in-process search, or latency-critical applications.

  • Qdrant EDGE: in-process bindings to Qdrant shard-level functions, no network overhead Qdrant EDGE
  • Same data format as server. Can sync with server via shard snapshots.
  • Single-node feature set only. No distributed mode.

What NOT to Do

  • Use local mode for production or benchmarking (not optimized, incompatible data format)
  • Self-host without monitoring and backup strategy (you will lose data or miss outages)
  • Choose EDGE when you need distributed search (single-node only)
  • Pick Hybrid Cloud unless you have data residency requirements (unnecessary Kubernetes complexity when Qdrant Cloud works)

Signals

GitHub stars
232
Forks
27
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
qdrant-deployment-options
Source
github.com/qdrant/skills