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monitoring-stack-deployer

Deploy Prometheus, Grafana, and SLO-driven alerting on Kubernetes clusters.

2|Updated Feb 11, 2026
Search Tags:#monitoring#kubernetes#observability#grafana#prometheus#alerting#slo
One-click install
npx skills add https://github.com/curiositech/port-daddy --skill monitoring-stack-deployer
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: monitoring-stack-deployer
Source: https://github.com/curiositech/port-daddy/tree/main/skills/monitoring-stack-deployer
Command: npx skills add https://github.com/curiositech/port-daddy --skill monitoring-stack-deployer

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Many teams struggle to reliably deploy a production-grade monitoring and alerting stack that provides accurate, low-noise signals tied to user impact. This Skill streamlines provisioning Prometheus, Grafana, ServiceMonitors, recording rules, and SLO-driven alerting so monitoring is scalable, maintainable, and actionable.

Core Features & Use Cases

  • SLO-driven alerting: Configure burn-rate alerts and multi-window policies to reduce alert fatigue and align notifications with user impact.
  • Kubernetes-native discovery: Deploy kube-prometheus-stack and use ServiceMonitor/PodMonitor to automatically discover application metrics endpoints.
  • Recording rules & performance: Precompute expensive queries with Prometheus recording rules to improve alert evaluation speed and reliability.
  • Dashboard-as-code: Provision Grafana dashboards (RED for services, USE for infrastructure) and expose dashboards as code for reproducible observability.
  • Operational patterns: Includes guidance on alert routing, runbooks, retention policy, and long-term storage integrations (Mimir/Thanos/VictoriaMetrics).

Quick Start

Set up kube-prometheus-stack in your Kubernetes cluster, create ServiceMonitors for your services, define SLOs and recording rules, and provision a Grafana dashboard that surfaces RED metrics and SLO burn-rate alerts.

Frequently Asked Questions about monitoring-stack-deployer

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I deploy Prometheus and Grafana on Kubernetes for production monitoring?▼

Deploy a production monitoring stack by installing kube-prometheus-stack on Kubernetes, configuring ServiceMonitors for metrics autodiscovery, and provisioning Grafana dashboards as code for reproducible observability.

What is SLO burn-rate alerting and how does it reduce alert fatigue?▼

SLO burn-rate alerting reduces alert fatigue by configuring multi-window policies that align notifications with actual user impact. This ensures alerts trigger based on service level objective consumption rather than raw threshold breaches.

How do I set up ServiceMonitor autodiscovery for Kubernetes application metrics?▼

Set up ServiceMonitor autodiscovery by deploying kube-prometheus-stack and defining ServiceMonitor or PodMonitor resources. This automatically discovers application metrics endpoints across your Kubernetes cluster without manual scrape configuration.

Why do I need Prometheus recording rules for expensive queries?▼

Prometheus recording rules precompute expensive queries to improve alert evaluation speed and reliability. By recording results ahead of time, you reduce the computational load during alert evaluation and ensure consistent dashboard performance.

Can I use this monitoring stack with long-term storage backends like Mimir or Thanos?▼

Yes, this monitoring stack supports long-term storage integrations with Mimir, Thanos, or VictoriaMetrics. The deployment includes operational patterns for configuring retention policies and routing metrics to these remote storage backends.

What is the best way to provision Grafana dashboards as code for RED and USE metrics?▼

Provision Grafana dashboards as code to surface RED metrics for services and USE metrics for infrastructure. This approach ensures reproducible observability by defining dashboard configurations declaratively rather than through manual UI changes.

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