Does it provide real-time visualization?

While the skill configures the data collection, it specifically assists in setting up central aggregation and generating dashboards for real-time monitoring.

Can it help diagnose specific database issues?

Yes, it can identify and monitor database-specific metrics such as connection pool usage, replication lag, and cache hit rates to help find bottlenecks.

Which monitoring platforms does this skill support?

The skill currently supports configuration and setup for Prometheus, Datadog, and AWS CloudWatch.

How do I activate this skill in Claude Code?

Simply ask Claude to 'collect infrastructure metrics', 'monitor server performance', or 'set up performance dashboards' to trigger the automated workflow.

What infrastructure layers can I monitor?

It provides comprehensive coverage for compute, storage, network, containers, load balancers, and various database types.

Infrastructure Metrics Collector

Name: Infrastructure Metrics Collector
Author: intent-solutions-io

byintent-solutions-io

Analíticas y Monitorización

Automates the collection and visualization of comprehensive infrastructure performance metrics across multi-layer systems and cloud services.

Acerca de

The Infrastructure Metrics Collector skill empowers Claude to architect and implement robust observability frameworks. It identifies critical KPIs across compute, storage, network, containers, and database layers, automating the configuration of monitoring agents like Prometheus, Datadog, and AWS CloudWatch. By bridging the gap between raw system data and actionable insights, this skill helps developers and SREs identify performance bottlenecks, track capacity trends, and generate real-time health dashboards through natural language commands.

Características Principales

Multi-layer monitoring across compute, network, storage, and databases
Real-time infrastructure health and capacity dashboard generation
0 GitHub stars
Automated agent configuration for Prometheus, Datadog, and CloudWatch
Smart identification of key performance indicators (KPIs) per layer
Centralized metrics aggregation and visualization setup

Casos de Uso

Setting up full-stack monitoring for web servers and load balancers
Troubleshooting database performance bottlenecks and replication lag
Automating observability setup during the deployment of new cloud infrastructure

Acerca de

Características Principales

Multi-layer monitoring across compute, network, storage, and databases
Real-time infrastructure health and capacity dashboard generation
0 GitHub stars
Automated agent configuration for Prometheus, Datadog, and CloudWatch
Smart identification of key performance indicators (KPIs) per layer
Centralized metrics aggregation and visualization setup

Casos de Uso

Setting up full-stack monitoring for web servers and load balancers
Troubleshooting database performance bottlenecks and replication lag
Automating observability setup during the deployment of new cloud infrastructure