Cost Management logo

Cost Management

Organization
grafana
cost-management

Cut your Grafana Cloud bill by attributing spend to teams and reducing telemetry volume. Covers FOCUS-compliant billing dashboards, cost-attribution labels in Alloy, Adaptive Metrics (cardinality reduction), Adaptive Logs (drop/sample), Adaptive Traces (tail sampling), usage alerts, and an optimization checklist. Use when investigating a high Grafana Cloud bill, attributing observability cost to a team or service, reducing active series / log bytes / trace spans, or setting up usage / quota alerts — even when the user says "our Grafana bill is too high", "who's burning the most metrics", "drop debug logs", "sample our traces", or "alert me before we hit quota" without naming Cost Management.

Overview

Publishergrafana
Repositoryskills
Skill namecost-management
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 Cost Management 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/cost-management
  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/cost-management .claude/skills/cost-management
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cost Management 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 Cost Management 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 Cost Management 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 Cost Management

Docs: https://grafana.com/docs/grafana-cloud/cost-management-and-billing/

Reduce metric / log / trace spend with Adaptive signals + cost-attribution labels.

Prerequisites

  • A Grafana Cloud stack with Adaptive Metrics / Logs / Traces enabled (visible under Cost Management)
  • Alloy (or Grafana Agent) ingesting telemetry, with API key in scope metrics:write + logs:write (+ traces:write)
  • Admin access to the stack to apply Adaptive recommendations

Common Workflows

1. Attribute cost to a team / service

alloy
# 1. Add external labels in Alloy (metrics + logs configs)
prometheus.remote_write "cloud" {
  endpoint { url = sys.env("PROMETHEUS_URL") /* ... */ }
  external_labels = { team = "platform", project = "checkout-service" }
}
bash
# 2. Reload Alloy
curl -X POST http://localhost:12345/-/reload

# 3. Verify labels arrived in Grafana Cloud
#    In Explore, run:  count by (team, project) ({__name__=~".+"})
#    Then visit Cost Management → group by `team` / `project`

See references/adaptive-signals.md for the full Alloy snippet.

2. Cut metric cardinality with Adaptive Metrics

bash
# 1. Pull recommendations
curl https://<stack>.grafana.net/api/plugins/grafana-adaptive-metrics-app/resources/v1/recommendations \
  -H "Authorization: Bearer <token>" | jq '.recommendations | length'

# 2. In the UI: Grafana Cloud → Adaptive Metrics → review rules sorted by series-reduction impact
# 3. Test in "Preview" mode before applying
# 4. Apply (takes effect within 5 min)

# 5. Verify — series count should drop on the affected metrics
#    Before applying, capture baseline:
#      count({__name__="http_request_duration_seconds_bucket"})
#    Wait 10 min after apply, run again — expect 10x+ reduction for high-card metrics.

# Rollback if needed: open the rule in the UI → Disable, or DELETE /v1/rules/<id>.

3. Drop noisy logs in Alloy

alloy
# 1. Add a filter stage (see references/adaptive-signals.md for the full block)
loki.process "filter_logs" {
  forward_to = [loki.write.cloud.receiver]
  stage.drop { expression = ".*GET /health.*" }
}
bash
# 2. Reload Alloy
curl -X POST http://localhost:12345/-/reload

# 3. Verify the filter — health logs should NOT appear in Logs Drilldown
#    LogQL check (should return 0):
#      sum(rate({app="my-app"} |= "GET /health" [5m]))
#    Bytes-ingested should also drop. Compare 24h before/after:
#      sum(increase(loki_ingester_chunk_size_bytes_sum[24h])) by (namespace)

4. Set a usage alert before you hit quota

See references/alerts-and-queries.md for ready-to-paste rules (MetricsUsageHigh, LogsIngestionHigh).

Optimization checklist

  • Apply Adaptive Metrics recommendations — typically reduces series 40-60%
  • Drop health/readiness probe logs in Alloy
  • Tail-sample traces to 5-10% + keep errors / slow spans
  • Add team + project external labels to every Alloy config
  • Set usage alerts at 80% of quota
  • Replace expensive ad-hoc queries with recording rules

References

Resources

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 Cost Management AI skill do?

Cut your Grafana Cloud bill by attributing spend to teams and reducing telemetry volume. Covers FOCUS-compliant billing dashboards, cost-attribution labels in Alloy, Adaptive Metrics (cardinality reduction), Adaptive Logs (drop/sample), Adaptive Traces (tail sampling), usage alerts, and an optimization checklist. Use when investigating a high Grafana Cloud bill, attributing observability cost to a team or service, reducing active series / log bytes / trace spans, or setting up usage / quota alerts — even when the user says "our Grafana bill is too high", "who's burning the most metrics", "d...

Why use Cost Management on TypingMind?

Because you install it once and use it with any model. Cost Management 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 Cost Management in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/grafana/skills/tree/main/skills/grafana-cloud/cost-management. 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 Cost Management?

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 Cost Management?

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

Is the Cost Management 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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