Does it set up real-time alerts?

The skill provides guidance on setting up alerts based on specific metric thresholds, allowing for proactive incident management.

How does this skill assist with capacity planning?

By aggregating and visualizing resource utilization metrics over time, it helps teams identify trends and predict when infrastructure upgrades will be necessary.

Does it support container monitoring?

Absolutely, the skill is designed to identify and configure metrics collection specifically for container layers and orchestration environments.

Which monitoring platforms are supported by this skill?

This skill currently supports automated configuration and integration for Prometheus, Datadog, and AWS CloudWatch.

Can it help diagnose slow databases?

Yes, the skill identifies database-specific KPIs such as replication lag, connection pool usage, and cache hit rates to help pinpoint performance issues.

Infrastructure Metrics Collector

Name: Infrastructure Metrics Collector
Author: BbgnsurfTech

byBbgnsurfTech

•

Analytics & Monitoring

Automates the collection and visualization of performance metrics across compute, storage, network, and database layers.

About

This skill empowers developers to gain deep visibility into their systems by automating the configuration of metrics collection for servers, databases, containers, and networks. By integrating with leading tools like Prometheus, Datadog, and AWS CloudWatch, it streamlines the setup of real-time monitoring dashboards, identifies performance bottlenecks, and assists in capacity planning, ensuring that infrastructure remains healthy and responsive under load.

Key Features

Centralized metrics aggregation for unified observability
Multi-layer monitoring for compute, storage, network, and databases
Automated dashboard generation for health and capacity tracking
Native support for Prometheus, Datadog, and AWS CloudWatch configurations
3 GitHub stars
Automated identification of critical Key Performance Indicators (KPIs)

Use Cases

Configuring comprehensive observability and resource tracking for containerized environments
Troubleshooting database latency by monitoring connection pools and replication lag
Setting up real-time performance monitoring for a new web server fleet

About

Key Features

Centralized metrics aggregation for unified observability
Multi-layer monitoring for compute, storage, network, and databases
Automated dashboard generation for health and capacity tracking
Native support for Prometheus, Datadog, and AWS CloudWatch configurations
3 GitHub stars
Automated identification of critical Key Performance Indicators (KPIs)

Use Cases

Configuring comprehensive observability and resource tracking for containerized environments
Troubleshooting database latency by monitoring connection pools and replication lag
Setting up real-time performance monitoring for a new web server fleet