Does it help with configuring Grafana alerts?

Yes, it provides JSON structures for defining alert conditions, evaluation frequencies, and notification channels (like Slack) directly within your dashboard definitions.

Does this skill support the RED and USE methods?

Yes, it provides specific guidance and JSON templates for implementing the RED (Rate, Errors, Duration) method for microservices and the USE (Utilization, Saturation, Errors) method for hardware and infrastructure resources.

Can I use this skill to automate dashboard deployment?

Absolutely. The skill includes patterns for Dashboard-as-Code using Terraform and Ansible, allowing you to treat your monitoring configuration as version-controlled source code.

What types of Grafana panels can this skill generate?

It supports a wide range of panels including Stat panels for single-value metrics, Time Series graphs for trends, Table panels for service status, and Heatmaps for analyzing latency distributions.

How does it handle dynamic data across multiple environments?

It utilizes Grafana templating and query variables, enabling you to create dynamic dashboards that can be filtered by namespace, instance, or service without manual configuration changes.

Grafana Dashboard Management

Name: Grafana Dashboard Management
Author: EngineerWithAI

byEngineerWithAI

Analíticas y Monitorización

Builds and manages production-grade Grafana dashboards for real-time observability of infrastructure and application metrics.

Acerca de

This skill empowers Claude to architect, configure, and maintain comprehensive Grafana dashboards using industry-standard observability patterns like RED (Rate, Errors, Duration) and USE (Utilization, Saturation, Errors). It provides detailed guidance on panel selection—including time series, heatmaps, and stat panels—while facilitating advanced configurations like templated variables, alerting rules, and Dashboard-as-Code provisioning through Terraform or Ansible. It is ideal for developers and SREs looking to transform raw Prometheus metrics into actionable operational insights and maintainable monitoring infrastructure.

Características Principales

Integrated alerting configuration for critical metric thresholds and notifications
JSON-based dashboard and panel configuration for Stat, Heatmap, and Time Series views
0 GitHub stars
Implementation of RED and USE monitoring methodologies
Dynamic templating with query variables for multi-environment and multi-service support
Automated provisioning patterns using Terraform and Ansible for version-controlled dashboards

Casos de Uso

Building service-level API monitoring dashboards with error rate tracking and latency alerting
Visualizing infrastructure health and resource utilization across distributed Kubernetes clusters
Implementing SLO/SLI tracking dashboards to monitor business-critical KPIs and operational stability

Acerca de

Características Principales

Integrated alerting configuration for critical metric thresholds and notifications
JSON-based dashboard and panel configuration for Stat, Heatmap, and Time Series views
0 GitHub stars
Implementation of RED and USE monitoring methodologies
Dynamic templating with query variables for multi-environment and multi-service support
Automated provisioning patterns using Terraform and Ansible for version-controlled dashboards

Casos de Uso

Building service-level API monitoring dashboards with error rate tracking and latency alerting
Visualizing infrastructure health and resource utilization across distributed Kubernetes clusters
Implementing SLO/SLI tracking dashboards to monitor business-critical KPIs and operational stability