ipIterPrompt

Prometheus Configuration

Set up Prometheus for comprehensive metric collection, storage, and monitoring of infrastructure and applications. Use when implementing metrics collection, setting up monitoring i

wshobson · agentsUpdated 2026-05-19

Prometheus Configuration — Set up Prometheus for comprehensive metric collection, storage, and monitoring of infrastructure and applications. Use when implementing metrics collection, setting up monitoring infrastructure, or configuring alerting systems. Imported from wshobson/agents (MIT).

SKILL.md

---
name: prometheus-configuration
description: Set up Prometheus for comprehensive metric collection, storage, and monitoring of infrastructure and applications. Use when implementing metrics collection, setting up monitoring infrastructure, or configuring alerting systems.
---

# Prometheus Configuration

Complete guide to Prometheus setup, metric collection, scrape configuration, and recording rules.

## Purpose

Configure Prometheus for comprehensive metric collection, alerting, and monitoring of infrastructure and applications.

## When to Use

- Set up Prometheus monitoring
- Configure metric scraping
- Create recording rules
- Design alert rules
- Implement service discovery

## Detailed patterns and worked examples

Detailed pattern documentation lives in `references/details.md`. Read that file when the navigation tier above is insufficient.

## Best Practices

1. **Use consistent naming** for metrics (prefix_name_unit)
2. **Set appropriate scrape intervals** (15-60s typical)
3. **Use recording rules** for expensive queries
4. **Implement high availability** (multiple Prometheus instances)
5. **Configure retention** based on storage capacity
6. **Use relabeling** for metric cleanup
7. **Monitor Prometheus itself**
8. **Implement federation** for large deployments
9. **Use Thanos/Cortex** for long-term storage
10. **Document custom metrics**

## Troubleshooting

**Check scrape targets:**

```bash
curl http://localhost:9090/api/v1/targets
```

**Check configuration:**

```bash
curl http://localhost:9090/api/v1/status/config
```

**Test query:**

```bash
curl 'http://localhost:9090/api/v1/query?query=up'
```


## Related Skills

- `grafana-dashboards` - For visualization
- `slo-implementation` - For SLO monitoring
- `distributed-tracing` - For request tracing

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How to use

  1. 1Save the content below as SKILL.md in your agent's skills directory (e.g. .claude/skills/<name>/SKILL.md).
  2. 2Or paste it directly into the conversation as context before asking the agent to do the task.
  3. 3Adjust any project-specific paths or conventions mentioned in the skill to match your setup.

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