Can I use this for production systems?

Yes, the skill is specifically designed to help implement production-grade observability, high availability, and proactive alerting strategies.

How does this skill help with data quality?

It includes specific patterns for monitoring data integrity, detecting schema drift, and ensuring the accuracy of data as it moves through your pipelines.

What tools does this skill support?

It provides guidance and implementation patterns for industry-standard tools including Prometheus, Grafana, and various centralized logging frameworks.

Does it cover both metrics and logs?

Yes, the skill addresses the full observability landscape, including metrics collection, log management, and visualization.

Monitoring & Observability

Name: Monitoring & Observability
Author: pluginagentmarketplace

bypluginagentmarketplace

分析と監視

Implements comprehensive monitoring, logging, and observability solutions for data infrastructure and production pipelines.

概要

The Monitoring & Observability skill empowers Claude to architect and implement robust tracking systems using industry-standard tools like Prometheus and Grafana. It focuses on maintaining high data quality, setting up proactive alerting mechanisms, and managing structured logs to ensure the reliability of complex data pipelines. By providing domain-specific patterns and best practices, this skill helps developers gain deep visibility into system performance, automate issue detection, and maintain production-grade infrastructure.

主な機能

Design of proactive alerting systems for real-time incident response
Implementation of automated data quality monitoring and validation rules
Integration of structured logging across distributed data systems
Standardization of observability patterns for ETL and data processing
Configuration of Prometheus metrics and Grafana visualization dashboards
0 GitHub stars

ユースケース

Detecting and alerting on data quality issues or schema drift in production
Building real-time performance dashboards for data engineering pipelines
Troubleshooting complex system failures through centralized logging and metrics

概要

主な機能

Design of proactive alerting systems for real-time incident response
Implementation of automated data quality monitoring and validation rules
Integration of structured logging across distributed data systems
Standardization of observability patterns for ETL and data processing
Configuration of Prometheus metrics and Grafana visualization dashboards
0 GitHub stars

ユースケース

Detecting and alerting on data quality issues or schema drift in production
Building real-time performance dashboards for data engineering pipelines
Troubleshooting complex system failures through centralized logging and metrics