What specific metrics are tracked?

It monitors CPU usage, memory, disk/network I/O, file descriptors, database connections, and thread/process counts.

Can it detect memory leaks?

Yes, it monitors memory patterns like heap and RSS over time to identify anomalies and growth patterns indicative of memory leaks.

Is it suitable for production environments?

Yes, it is designed to provide observability and insights for application stacks to ensure stability and detect performance regressions.

Does it work with specific databases?

The skill monitors general database connection pool metrics, making it useful for optimizing connection overhead across various SQL and NoSQL systems.

How does this skill help with cloud costs?

It analyzes resource utilization to suggest right-sizing for your instances, ensuring you don't pay for unused capacity while maintaining performance.

Resource Usage Tracker

Name: Resource Usage Tracker
Author: BbgnsurfTech

byBbgnsurfTech

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分析与监控

Monitors and optimizes application resource consumption including CPU, memory, and database connections to improve performance and reduce costs.

关于

The Resource Usage Tracker skill empowers Claude to provide deep visibility into your application stack's performance metrics. By monitoring real-time data for CPU, memory, disk/network I/O, and database connections, it identifies hidden bottlenecks and provides actionable recommendations for right-sizing infrastructure and optimizing code efficiency. This skill is essential for developers and DevOps engineers looking to maintain high-performance applications while minimizing cloud infrastructure expenses through data-driven insights.

主要功能

Cost optimization through infrastructure right-sizing recommendations
3 GitHub stars
Automated identification of performance bottlenecks and leaks
Granular process-level resource tracking
Real-time monitoring of CPU, memory, and I/O metrics
Database connection pool utilization analysis

使用场景

Optimizing database connection limits to prevent service contention
Detecting and resolving memory leaks in long-running processes
Right-sizing cloud instances to reduce monthly infrastructure costs

关于

主要功能

Cost optimization through infrastructure right-sizing recommendations
3 GitHub stars
Automated identification of performance bottlenecks and leaks
Granular process-level resource tracking
Real-time monitoring of CPU, memory, and I/O metrics
Database connection pool utilization analysis

使用场景

Optimizing database connection limits to prevent service contention
Detecting and resolving memory leaks in long-running processes
Right-sizing cloud instances to reduce monthly infrastructure costs