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Dpm Finder

Organization
grafana
dpm-finder

Find the Prometheus metrics that drive your Grafana Cloud bill. `dpm-finder` is a Grafana Professional Services CLI that ranks metrics by Data Points per Minute (DPM) with per-label-set breakdown, optional `--cost-per-1000-series` pricing, and a Prometheus-exporter mode. Use when investigating high Grafana Cloud spend, hunting noisy / high-cardinality metrics, comparing pre/post recording-rule cardinality, or feeding cost data into dashboards — even when the user says "why is my Mimir bill so high?", "find the biggest metrics", "cardinality offenders", or "optimize Prometheus cost" without naming dpm-finder.

Overview

Publishergrafana
Repositoryskills
Skill namedpm-finder
Stars
289
Forks
27
Bundled files
1
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.

  • 1 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 Dpm Finder 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/dpm-finder
  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/dpm-finder .claude/skills/dpm-finder
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Dpm Finder 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 Dpm Finder 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 Dpm Finder 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.

dpm-finder

Grafana PS tool ranking Prometheus metrics by DPM with per-series breakdown. Source: https://github.com/grafana-ps/dpm-finder

Prerequisites

  • Python 3.9+
  • A Grafana Cloud Prometheus endpoint URL + numeric stack ID + API key (glc_…, metrics:read scope)

Common Workflows

One-shot analysis (most common)

bash
# 1. Clone + venv + install
git clone https://github.com/grafana-ps/dpm-finder.git
cd dpm-finder
python3 -m venv venv && source venv/bin/activate
pip install -r requirements.txt

# 2. Configure creds — copy .env_example → .env and fill in:
#    PROMETHEUS_ENDPOINT  https://prometheus-<cluster_slug>.grafana.net  (NOTHING after .net)
#    PROMETHEUS_USERNAME  <numeric stack id>
#    PROMETHEUS_API_KEY   glc_…

# 3. Verify creds before scanning — should return >0 series count
curl -s -u "$PROMETHEUS_USERNAME:$PROMETHEUS_API_KEY" \
  "$PROMETHEUS_ENDPOINT/api/v1/label/__name__/values" | jq '.data | length'

# 4. Run the scan (10-min lookback, 2.0 DPM minimum, top output)
./dpm-finder.py -f json -m 2.0 -t 8 --timeout 120 -l 10

# 5. Read the result — top 10 metrics by DPM
jq -r '.metrics | sort_by(-.dpm) | .[:10][] | "\(.dpm)\t\(.series_count)\t\(.metric_name)"' metric_rates.json

If step 5 is empty, lower -m or confirm the endpoint URL has no trailing path after .net.

Discover stack details with gcx

If gcx is installed it can derive the endpoint + username:

bash
gcx config check          # active stack context
gcx config list-contexts  # all configured stacks
gcx config view           # full config with endpoints

The Prometheus endpoint pattern is https://prometheus-{cluster_slug}.grafana.net. Username is the numeric stack ID.

Without gcx: look up in the Grafana Cloud portal, or query grafanacloud_instance_info{name=~"STACK_NAME.*"} on the usage datasource.

Multi-stack runs

Limit to max 3 concurrent runs to avoid GCloud rate limits. Batch the stacks and wait for each batch before the next.

Interpreting results

  • DPM = max data points per minute across that metric's series
  • series_count = active time-series count for that metric
  • series_detail[] (JSON / text only) = per-label-combination DPM breakdown — use this to spot the offending label
  • Sort by DPM descending → noisiest metrics; combine with --cost-per-1000-series to prioritize by spend

Troubleshooting

  • 401 / 403 — API key invalid or missing metrics:read; confirm PROMETHEUS_USERNAME is the numeric stack ID
  • Timeouts — bump --timeout to 120+ for stacks with thousands of metrics
  • HTTP 422 — metric has aggregation rules; tool warns + skips automatically
  • Empty results — lower -m; verify endpoint has no trailing path
  • Connection errors — exponential backoff retries up to 10 times; persistent failure usually = network/firewall

References

  • references/cli.md — full flag reference, output-format details, exporter mode, Docker invocation, auto-exclusion rules, retry behavior

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 Dpm Finder AI skill do?

Find the Prometheus metrics that drive your Grafana Cloud bill. `dpm-finder` is a Grafana Professional Services CLI that ranks metrics by Data Points per Minute (DPM) with per-label-set breakdown, optional `--cost-per-1000-series` pricing, and a Prometheus-exporter mode. Use when investigating high Grafana Cloud spend, hunting noisy / high-cardinality metrics, comparing pre/post recording-rule cardinality, or feeding cost data into dashboards — even when the user says "why is my Mimir bill so high?", "find the biggest metrics", "cardinality offenders", or "optimize Prometheus cost" without...

Why use Dpm Finder on TypingMind?

Because you install it once and use it with any model. Dpm Finder 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 Dpm Finder in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/grafana/skills/tree/main/skills/grafana-cloud/dpm-finder. 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 Dpm Finder?

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 Dpm Finder?

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

Is the Dpm Finder 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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