deploying-monitoring-stacks

•

184393 months ago

Monitor use when deploying monitoring stacks including Prometheus, Grafana, and Datadog. Trigger with phrases like "deploy monitoring stack", "setup prometheus", "configure grafana", or "install datadog agent". Generates production-ready configurations with metric collection, visualization dashboards, and alerting rules.

Quick Install

npxskills add majiayu000/claude-skill-registry--skill deploying-monitoring-stacks

Instructions

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

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

Output

Prometheus + Grafana (Kubernetes):

# {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
        image: prom/prometheus:latest
        args:
          - '--config.file=/etc/prometheus/prometheus.yml'
          - '--storage.tsdb.retention.time=30d'
        ports:
        - containerPort: 9090

Grafana Dashboard Configuration:

{
  "dashboard": {
    "title": "Application Metrics",
    "panels": [
      {
        "title": "CPU Usage",
        "type": "graph",
        "targets": [
          {
            "expr": "rate(container_cpu_usage_seconds_total[5m])"
          }
        ]
      }
    ]
  }
}

Error Handling

Metrics Not Appearing

Error: "No data points"
Solution: Verify scrape targets are accessible and returning metrics

High Cardinality

Error: "Too many time series"
Solution: Reduce label combinations or increase Prometheus resources

Alert Not Firing

Error: "Alert condition met but no notification"
Solution: Check Alertmanager configuration and notification channels

Dashboard Load Failure

Error: "Failed to load dashboard"
Solution: Verify Grafana datasource configuration and permissions

Examples

"Deploy Prometheus + Grafana on Kubernetes and add alerts for high error rate and latency."
"Install Datadog agents across hosts and configure a dashboard for CPU/memory saturation."

Resources

Prometheus documentation: https://prometheus.io/docs/
Grafana documentation: https://grafana.com/docs/
Example dashboards in {baseDir}/monitoring-examples/

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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

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

Output

Prometheus + Grafana (Kubernetes):

# {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
        image: prom/prometheus:latest
        args:
          - '--config.file=/etc/prometheus/prometheus.yml'
          - '--storage.tsdb.retention.time=30d'
        ports:
        - containerPort: 9090

Grafana Dashboard Configuration:

{
  "dashboard": {
    "title": "Application Metrics",
    "panels": [
      {
        "title": "CPU Usage",
        "type": "graph",
        "targets": [
          {
            "expr": "rate(container_cpu_usage_seconds_total[5m])"
          }
        ]
      }
    ]
  }
}

Error Handling

Metrics Not Appearing

Error: "No data points"
Solution: Verify scrape targets are accessible and returning metrics

High Cardinality

Error: "Too many time series"
Solution: Reduce label combinations or increase Prometheus resources

Alert Not Firing

Error: "Alert condition met but no notification"
Solution: Check Alertmanager configuration and notification channels

Dashboard Load Failure

Error: "Failed to load dashboard"
Solution: Verify Grafana datasource configuration and permissions

Examples

"Deploy Prometheus + Grafana on Kubernetes and add alerts for high error rate and latency."
"Install Datadog agents across hosts and configure a dashboard for CPU/memory saturation."

Resources

Prometheus documentation: https://prometheus.io/docs/
Grafana documentation: https://grafana.com/docs/
Example dashboards in {baseDir}/monitoring-examples/