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Qdrant Hybrid Cloud Setup

Organization
qdrant
qdrant-hybrid-cloud-setup

Setting up and running Qdrant Hybrid Cloud on your own Kubernetes cluster (managed, on-prem, or edge): prerequisites, storage/CSI and backups, installing the Qdrant Cloud agent and operator, creating/exposing/securing clusters, registry mirroring, and secret rotation. Use when someone wants to set up, install, deploy, or configure Hybrid Cloud on their own infrastructure; is running Qdrant on their own EKS, GKE, AKS, OpenShift, or other Kubernetes; asks about the agent or operator, a storage class or volume snapshots for Hybrid Cloud, exposing a cluster, mirroring Qdrant images, or rotating secrets; or when a Hybrid Cloud install is failing on storage or connectivity.

Overview

Publisherqdrant
Repositoryskills
Skill nameqdrant-hybrid-cloud-setup
Stars
262
Forks
31
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by qdrant on GitHub. Read the source before you install it.

Installation

Install the Qdrant Hybrid Cloud Setup AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/qdrant/skills/tree/main/skills/qdrant-hybrid-cloud-setup
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/qdrant/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/qdrant-hybrid-cloud-setup .claude/skills/qdrant-hybrid-cloud-setup
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Qdrant Hybrid Cloud Setup in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Qdrant Hybrid Cloud Setup on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Qdrant Hybrid Cloud Setup is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Setting Up Qdrant Hybrid Cloud

You've already chosen Hybrid Cloud (managed control plane on your own infra). If you're still deciding, that's the qdrant-deployment-options skill. Most setup failures trace to one of two things: storage (the CSI driver can't do what Qdrant needs) or connectivity (the agent can't reach Qdrant Cloud). Diagnose which before touching anything else.

Preparing the Kubernetes cluster (do this first)

Use when: about to create the environment, or the install/cluster provisioning failed on storage.

  • Qdrant needs a block-storage CSI driver. Network storage (NFS) and object storage (S3) are unsupported: a cluster wired to those will fail, not degrade Prerequisites.
  • Create the StorageClass (with allowVolumeExpansion: true) and the VolumeSnapshotClass beforehand, not after. Without volume expansion you can't grow disk later; without a VolumeSnapshotClass and the CSI snapshot controller you can't take backups.
  • Any standards-compliant Kubernetes works, and there's platform-specific setup guidance for the managed ones: Akamai (Linode/LKE), AWS (EKS), Civo, DigitalOcean (DOKS), Gcore, GCP (GKE), Azure (AKS), Oracle (OKE), OVHcloud, Red Hat OpenShift, Scaleway, STACKIT, and Vultr Deployment Platforms.
  • Platform matters for what storage supports: some (e.g. Linode/LKE, Vultr) don't support CSI volume snapshots at all, so backups are unavailable there. Check your provider's snapshot page and prefer its recommended instance and disk types (e.g. gp3 on EKS, Premium SSD v2 on AKS) before committing.
  • Confirm outbound connectivity: the agent opens connections to grpc.cloud.qdrant.io and api.cloud.qdrant.io on 443. Firewalls/egress proxies block this silently: a "stuck installing" agent is usually this.
  • You need cluster-admin plus kubectl and helm configured against the target cluster.

Creating the environment

Use when: running the install wizard in the Cloud Console.

  • The Kubernetes namespace is permanent: it's the one choice you can't change later. Everything else (node selectors, tolerations, registry URLs, proxy) is editable after creation, so don't over-think them now.
  • The wizard generates a one-time install command that creates secrets and installs the agent + operator via Helm. You only need it for the initial install; updates happen from the Console afterward Setup guide.
  • Advanced operator behavior (pod scheduling, security context, ingress, networking, and snapshot management) is tuned in the operator configuration at the environment level, and can be changed after install Operator configuration.
  • Air-gapped or registry-restricted? Mirror the /qdrant/ images and /qdrant-charts/ charts into your own registry and set the container + chart URLs in the environment's advanced section. Sync all architectures (or the right one) or ARM/x86 nodes will fail to pull.

Creating a cluster in the environment

Use when: the environment exists and you're provisioning a database.

  • Pick the Database Storage Class and Volume Snapshot Class here. Setting Volume Snapshot Class to None disables backups; emptyDir for the snapshot volume makes it ephemeral (lost on pod restart): deliberate choices, not defaults to accept blindly Cluster creation.
  • By default Qdrant Cloud reserves ~20% CPU/memory per pod for the OS and system components. Small nodes may need more reserved; large nodes less. Aim for one database pod per node.
  • Use node selectors / tolerations / topology spread constraints to keep databases on dedicated nodes and spread across zones.

Exposing and securing a cluster

Use when: apps outside the Kubernetes cluster need to reach Qdrant, or asked about API keys/TLS.

  • Default is a ClusterIP service: internal-only, no API key. The moment you expose it (LoadBalancer, NodePort, or Ingress) you MUST configure an API key, supplied as a Kubernetes secret referenced in the cluster config Networking & security.
  • Internal node-to-node gRPC uses port 6335 and is never protected by API key or TLS. It must never be publicly reachable; Hybrid Cloud ships a NetworkPolicy restricting it, so don't loosen that.
  • TLS: offload at the ingress/LB, or terminate in Qdrant via a TLS secret. Don't do both by accident.

Logging

Use when: setting log levels or wiring cluster logs into your stack. (For metrics/Prometheus/Grafana, use the qdrant-monitoring skill instead.)

  • Log levels are set in two different places: per-database in the Cluster detail page, but for the Agent and Operator in the Hybrid Cloud Environment config, not per-cluster Networking, Logging & Monitoring.
  • Logs are plain pod logs with no Qdrant-specific format. Point any Kubernetes-aware log collector at all pods in the Qdrant namespace; nothing Qdrant-specific to configure.

What NOT to Do

  • Provision on NFS, S3, or any non-block storage: it's unsupported and will fail outright, not just run slowly.
  • Create the StorageClass/VolumeSnapshotClass (or enable allowVolumeExpansion) after the fact, then discover you can't scale disk or take backups. They must exist beforehand.
  • Assume backups "just work" on Linode or Vultr: verify CSI snapshot support for your platform first.
  • Expose a cluster via LoadBalancer/Ingress without setting an API key, or leave port 6335 publicly reachable.
  • Regenerate the install command (or rotate secrets) and forget to reapply it: the agent-to-Cloud link breaks silently until you do.
  • Delete a Hybrid Cloud environment before deleting its clusters: tear down clusters first, then the environment, then run the cleanup script, or you'll strand resources in the cluster.

Frequently asked questions

What does the Qdrant Hybrid Cloud Setup AI skill do?

Setting up and running Qdrant Hybrid Cloud on your own Kubernetes cluster (managed, on-prem, or edge): prerequisites, storage/CSI and backups, installing the Qdrant Cloud agent and operator, creating/exposing/securing clusters, registry mirroring, and secret rotation. Use when someone wants to set up, install, deploy, or configure Hybrid Cloud on their own infrastructure; is running Qdrant on their own EKS, GKE, AKS, OpenShift, or other Kubernetes; asks about the agent or operator, a storage class or volume snapshots for Hybrid Cloud, exposing a cluster, mirroring Qdrant images, or rotating...

Why use Qdrant Hybrid Cloud Setup on TypingMind?

Because you install it once and use it with any model. Qdrant Hybrid Cloud Setup is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Qdrant Hybrid Cloud Setup in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/qdrant/skills/tree/main/skills/qdrant-hybrid-cloud-setup. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Qdrant Hybrid Cloud Setup?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Qdrant Hybrid Cloud Setup?

As many as you like. As long as a model supports skills, you can use Qdrant Hybrid Cloud Setup with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Qdrant Hybrid Cloud Setup AI skill free?

Yes. It is published on GitHub by qdrant under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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