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.
Install with the open skills CLI (global, non-interactive — available in every Claude Code session):
npx skills add wshobson/agents --skill "prometheus-configuration" -g -a claude-code -yOr manually — clone and copy the skill directory (SKILL.md + companion files):
git clone --depth 1 https://github.com/wshobson/agents /tmp/agents && cp -r /tmp/agents/plugins/observability-monitoring/skills/prometheus-configuration ~/.claude/skills/prometheus-configuration-wshobsonThis skill is a directory: SKILL.md is the entry point; the files below ship with it.
---
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
Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes
Use when implementing any feature or bugfix, before writing implementation code