Does this skill require specific PostgreSQL versions?

Yes, this skill is optimized for PostgreSQL 16 and above to ensure compatibility with modern monitoring functions and statistics views.

What types of metrics can be monitored using this skill?

The skill tracks connection states, query execution times, table sizes, cache hit ratios, dead tuples, and replication lag.

Do I need to install any extensions for this skill to work effectively?

Most monitoring features, particularly query analysis, require the pg_stat_statements extension to be enabled in your PostgreSQL database.

Can Claude help me set up a dashboard with this skill?

While Claude doesn't render visual dashboards, it provides the exact SQL queries, exporter configurations, and Prometheus patterns needed to populate Grafana dashboards.

PostgreSQL Monitoring

Name: PostgreSQL Monitoring
Author: pluginagentmarketplace

bypluginagentmarketplace

•

데이터베이스 관리

Monitors PostgreSQL database performance and health through automated metric collection, observability patterns, and diagnostic alerting.

The PostgreSQL Monitoring skill empowers Claude to oversee the health and performance of production-grade PostgreSQL databases. It provides automated patterns for collecting critical metrics such as connection counts, cache hit ratios, and replication lag, while also offering deep insights into slow queries using the pg_stat_statements extension. Ideal for DBAs and backend developers, this skill facilitates proactive observability through Prometheus and Grafana integrations and helps diagnose performance regressions by comparing real-time statistics against established industry thresholds for warning and critical states.

주요 기능

01Pre-defined warning and critical thresholds for database alerting

02Prometheus exporter configuration for streamlined observability

03Automated collection of connection, storage, and replication metrics

04Identification of slow-running queries via pg_stat_statements

05Real-time cache hit ratio analysis for performance optimization

061 GitHub stars

사용 사례

01Diagnosing production performance bottlenecks and high CPU usage caused by unoptimized SQL queries

02Setting up an observability stack to track replication lag across primary and standby nodes

03Monitoring connection pool health to prevent application downtime during traffic surges

주요 기능

01Pre-defined warning and critical thresholds for database alerting

02Prometheus exporter configuration for streamlined observability

03Automated collection of connection, storage, and replication metrics

04Identification of slow-running queries via pg_stat_statements

05Real-time cache hit ratio analysis for performance optimization

061 GitHub stars

사용 사례

01Diagnosing production performance bottlenecks and high CPU usage caused by unoptimized SQL queries

02Setting up an observability stack to track replication lag across primary and standby nodes

03Monitoring connection pool health to prevent application downtime during traffic surges