deploying-monitoring-stacks

# Monitoring Stack Deployer

This skill provides automated assistance for monitoring stack deployer tasks.

## Overview

Deploys monitoring stacks (Prometheus/Grafana/Datadog) including collectors, scraping config, dashboards, and alerting rules for production systems.

## Prerequisites

Before using this skill, ensure:
- Target infrastructure is identified (Kubernetes, Docker, bare metal)
- Metric endpoints are accessible from monitoring platform
- Storage backend is configured for time-series data
- Alert notification channels are defined (email, Slack, PagerDuty)
- Resource requirements are calculated based on scale

## Instructions

1. **Select Platform**: Choose Prometheus/Grafana, Datadog, or hybrid approach
2. **Deploy Collectors**: Install exporters and agents on monitored systems
3. **Configure Scraping**: Define metric collection endpoints and intervals
4. **Set Up Storage**: Configure retention policies and data compaction
5. **Create Dashboards**: Build visualization panels for key metrics
6. **Define Alerts**: Create alerting rules with appropriate thresholds
7. **Test Monitoring**: Verify metrics flow and alert triggering

## Output

**Prometheus + Grafana (Kubernetes):**
```yaml
# {baseDir}/monitoring/prometheus.yaml


## Overview

This skill provides automated assistance for the described functionality.

## Examples

Example usage patterns will be demonstrated in context.
apiVersion: v1
kind: ConfigMap
metadata:
  name: prometheus-config
data:
  prometheus.yml: |
    global:
      scrape_interval: 15s
      evaluation_interval: 15s
    scrape_configs:
      - job_name: 'kubernetes-pods'
        kubernetes_sd_configs:
          - role: pod
        relabel_configs:
          - source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_scrape]
            action: keep
            regex: true
---
apiVersion: apps/v1
kind: Deployment
metadata:
  name: prometheus
spec:
  replicas: 1
  template:
    spec:
      containers:
      - name: prometheus