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Prometheus

ASecurity

> Powering metrics and alerting.

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  • Added September 5, 2026
ai-agentsbashnodedockerkubernetesawsapidatabasesecurity

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Scanned September 5, 2026

npx -y skills add ashish7802/awesome-api-skills --skill prometheus --agent claude-code

Installs into .claude/skills of the current project.

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SKILL.md
# Prometheus Skill

> Powering metrics and alerting.

## Ecosystem Graph

```mermaid
graph LR
  prometheus["Prometheus"]
  prometheus -- "works well with" --> grafana
  prometheus -- "monitors" --> kubernetes
```

## Quick Start
Prometheus is a pull-based time-series database. It scrapes `/metrics` endpoints across your infrastructure at regular intervals and stores them.

```bash
docker run -p 9090:9090 prom/prometheus
```

## Production Patterns
### Exporters
Do not manually instrument standard infrastructure. Use Exporters (e.g., `node_exporter` for Linux stats, `postgres_exporter` for DB stats) which automatically expose standard metrics in the Prometheus format.

## Architecture & Scaling
### Pull vs Push
Prometheus pulls metrics. In serverless environments (like AWS Lambda) where services are ephemeral and cannot be scraped, you must push metrics to a Prometheus Pushgateway, which Prometheus then scrapes.

## Error Recovery
Prometheus is heavily memory-bound. If it OOMs, check your label cardinality. High cardinality (e.g., tracking a user ID as a label on every metric) will exponentially explode the TSDB and crash the server.

## Security Notes
Prometheus scrape endpoints (`/metrics`) often contain sensitive infrastructure data. Ensure these endpoints are strictly inaccessible from the public internet (e.g., via internal Kubernetes network policies).

## Relationships
**Works Well With**: [grafana](/skills/grafana)

## References
- [Prometheus Docs](https://prometheus.io/docs/introduction/overview/)

## Why use this skill
Use this when your agent works with **prometheus** — structured patterns beat pasted docs and prevent common hallucinations.

## AI pitfalls
- Using outdated SDK or API versions from training data
- Inventing environment variable names
- Omitting error handling and retry logic

## Production checklist
- [ ] Secrets in environment variables, not source code
- [ ] Error handling and logging in place
- [ ] Rate limits and timeouts configured

## Related skills
- [`grafana`](../grafana/SKILL.md) — works well with
- [`kubernetes`](../kubernetes/SKILL.md) — monitors

---
> **Last Verified:** 2026-07-02

Files in this skill

  • SKILL.md2.1 KB
  • examples/config.yml209 B

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