Which monitoring tools does this skill support?

The skill helps configure various industry-standard tools including Prometheus, StatsD, AWS CloudWatch, and other common metrics collectors.

Does this skill assist with database observability?

Absolutely. It can guide you in aggregating database-specific metrics such as slow queries, connection pool usage, and execution times.

Can I use it to set up alerts?

Yes, the skill assists in defining performance thresholds and configuring alerts to notify your team when critical indicators exceed limits.

Can it help me organize my metrics better?

Yes, it provides guidance on designing a consistent metrics taxonomy and naming convention to ensure clarity across complex systems.

Performance Metrics Aggregator

Name: Performance Metrics Aggregator
Author: intent-solutions-io

byintent-solutions-io

分析与监控

Aggregates and centralizes performance metrics from diverse systems to streamline observability and real-time monitoring.

关于

This skill empowers Claude to act as an observability expert, helping users design unified metrics taxonomies and select appropriate aggregation tools like Prometheus, StatsD, or CloudWatch. It simplifies the process of collecting data from applications, databases, and infrastructure, guiding the configuration of integrations to ensure all performance indicators are accessible in one central location. By facilitating the setup of dashboards and actionable alerts, it helps teams resolve issues faster and maintain high system availability.

主要功能

Multi-source data integration for apps and infrastructure
Metrics taxonomy and naming convention design
Aggregation tool selection (Prometheus, StatsD, CloudWatch)
Automated dashboard visualization setup
0 GitHub stars
Critical performance indicator alerting

使用场景

Designing a consistent metrics naming convention for microservices
Setting up automated alerts for database latency and resource exhaustion
Consolidating application and system metrics into a central Prometheus instance

关于

主要功能

Multi-source data integration for apps and infrastructure
Metrics taxonomy and naming convention design
Aggregation tool selection (Prometheus, StatsD, CloudWatch)
Automated dashboard visualization setup
0 GitHub stars
Critical performance indicator alerting

使用场景

Designing a consistent metrics naming convention for microservices
Setting up automated alerts for database latency and resource exhaustion
Consolidating application and system metrics into a central Prometheus instance