Private Connectivity logo

Private Connectivity

Organization
grafana
private-connectivity

Set up private network connectivity to Grafana Cloud — AWS PrivateLink, Azure Private Link, GCP Private Service Connect, and Private Data Source Connect (PDC). Provisions VPC endpoints, private endpoints, or PSC forwarding rules per signal type (metrics / logs / traces / profiles); wires Alloy to push to the private DNS endpoint instead of the public one; verifies private DNS resolution + endpoint approval state. Use when sending telemetry to Grafana Cloud without traversing the public internet, eliminating cloud egress costs, meeting PCI-DSS / HIPAA / data-residency compliance, configuring PDC for private data-source queries, or connecting AWS / Azure / GCP workloads to Grafana — even when the user says "stop paying egress", "keep our telemetry off the public internet", or "PCI compliance for Grafana" without naming PrivateLink.

Overview

Publishergrafana
Repositoryskills
Skill nameprivate-connectivity
Stars
289
Forks
27
Bundled files
2
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.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Private Connectivity 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/grafana/skills/tree/main/skills/grafana-cloud/private-connectivity
  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/grafana/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/grafana-cloud/private-connectivity .claude/skills/private-connectivity
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Private Connectivity 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 Private Connectivity 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 Private Connectivity 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.

Grafana Cloud Private Connectivity

Docs: https://grafana.com/docs/grafana-cloud/send-data/

Send metrics, logs, traces, and profiles to Grafana Cloud entirely over your cloud provider's private backbone — no public internet exposure, no egress fees.

Common Workflows

Setting up AWS PrivateLink (most common)

  1. Find your service names. Grafana Cloud → Stack Details → "Send using AWS PrivateLink". Note one service name per signal type (metrics / logs / traces / profiles).

  2. Create an Interface VPC Endpoint per signal type:

    bash
    aws ec2 create-vpc-endpoint \
      --vpc-id vpc-12345 \
      --service-name com.amazonaws.vpce.us-east-1.vpce-svc-0abc123 \
      --vpc-endpoint-type Interface \
      --subnet-ids subnet-12345 \
      --security-group-ids sg-12345 \
      --private-dns-enabled
  3. Verify private DNS resolves (CRITICAL — if this returns a public IP, Alloy will silently keep using the public path and you'll keep paying egress):

    bash
    dig +short prometheus-private.us-east-0.grafana.net
    # Expected: a 10.x.x.x / 172.16-31.x.x / 192.168.x.x address
    # Public IP returned → check `private_dns_enabled = true` was set and the VPC has DNS hostnames enabled
  4. Update Alloy to use the private endpoint:

    alloy
    prometheus.remote_write "cloud_private" {
      endpoint {
        url = "https://prometheus-private.us-east-0.grafana.net/api/prom/push"
        basic_auth {
          username = sys.env("PROM_USER")
          password = sys.env("GRAFANA_CLOUD_API_KEY")
        }
      }
    }
    
    loki.write "cloud_private" {
      endpoint {
        url = "https://logs-private.us-east-0.grafana.net/loki/api/v1/push"
        basic_auth {
          username = sys.env("LOKI_USER")
          password = sys.env("GRAFANA_CLOUD_API_KEY")
        }
      }
    }
  5. Confirm traffic is flowing over PrivateLink: check the VPC endpoint's CloudWatch metrics for BytesProcessed after Alloy starts pushing.

Full Terraform + per-signal-type endpoint resources in references/aws.md.

Setting up Azure Private Link / GCP Private Service Connect

Different provider, same shape: create the private endpoint → wait for approval → verify private DNS → update Alloy URLs. Full CLI + verification steps in references/azure-gcp.md.

Azure-specific prereq: Pre-register your Subscription IDs with Grafana Support before starting — without this the endpoint creation hangs at "Pending".

Prerequisites (all providers)

  • Grafana Cloud stack must be hosted on the same cloud provider (check: My Account → Stack → Details)
  • Create separate private endpoints for each signal type (metrics / logs / traces / profiles) — they have distinct service names
  • Same region only for AWS PrivateLink. Cross-region requires VPC peering first.

Choosing the right option

ScenarioSolution
Push from AWSAWS PrivateLink
Push from AzureAzure Private Link
Push from GCPGCP Private Service Connect
Query private DB / Prometheus from GrafanaPrivate Data Source Connect (PDC) — see references/azure-gcp.md § PDC

References

  • references/aws.md — full AWS PrivateLink Terraform per signal type + endpoint verification (state + DNS)
  • references/azure-gcp.md — Azure Private Link + GCP Private Service Connect setup (Portal + CLI) + verification + Private Data Source Connect (PDC) for reverse-direction private data source queries

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Private Connectivity AI skill do?

Set up private network connectivity to Grafana Cloud — AWS PrivateLink, Azure Private Link, GCP Private Service Connect, and Private Data Source Connect (PDC). Provisions VPC endpoints, private endpoints, or PSC forwarding rules per signal type (metrics / logs / traces / profiles); wires Alloy to push to the private DNS endpoint instead of the public one; verifies private DNS resolution + endpoint approval state. Use when sending telemetry to Grafana Cloud without traversing the public internet, eliminating cloud egress costs, meeting PCI-DSS / HIPAA / data-residency compliance, configuring...

Why use Private Connectivity on TypingMind?

Because you install it once and use it with any model. Private Connectivity 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 Private Connectivity in TypingMind?

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

Which AI models can use Private Connectivity?

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 Private Connectivity?

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

Is the Private Connectivity AI skill free?

Yes. It is published on GitHub by grafana 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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