Does it handle PostgreSQL vacuuming issues?

Absolutely. It includes specific health checks for dead tuple percentages and autovacuum performance to prevent table bloat.

Can this skill help set up automated alerts?

Yes, it generates monitoring scripts and notification templates compatible with Slack, PagerDuty, and email integration.

Which databases are supported by this skill?

This skill provides specialized support and optimized queries for PostgreSQL, MySQL, and MongoDB environments.

How does it track database growth?

It monitors disk usage trends and provides projections to help you anticipate when additional storage or data archiving is required.

Database Health Monitor

Name: Database Health Monitor
Author: jeremylongshore

byjeremylongshore

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1,965

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분석 및 모니터링

Monitors and optimizes database performance across PostgreSQL, MySQL, and MongoDB through comprehensive observability metrics.

The Database Health Monitor skill empowers Claude Code to proactively manage database reliability by tracking critical performance indicators such as connection utilization, query throughput, replication lag, and disk growth. It provides automated health check queries and generates monitoring scripts tailored to specific database engines, helping developers identify performance bottlenecks, autovacuum issues, and lock contention before they impact production users. Whether you need to set up real-time alerting or diagnose slow query execution, this skill provides the necessary guidance and automation to maintain a healthy data layer.

주요 기능

01Generation of structured RAG (Red/Amber/Green) health summary dashboards

02Real-time monitoring of connection utilization and query throughput ratios

03Disk usage forecasting and cache hit ratio analysis for resource optimization

04Multi-engine support for PostgreSQL, MySQL, and MongoDB performance tracking

05Automated detection of replication lag and resource-intensive long-running queries

061,965 GitHub stars

사용 사례

01Optimizing PostgreSQL autovacuum settings to manage table bloat and dead tuples

02Diagnosing database performance degradation and identifying lock contention

03Setting up automated health alerts for production database environments

주요 기능

01Generation of structured RAG (Red/Amber/Green) health summary dashboards

02Real-time monitoring of connection utilization and query throughput ratios

03Disk usage forecasting and cache hit ratio analysis for resource optimization

04Multi-engine support for PostgreSQL, MySQL, and MongoDB performance tracking

05Automated detection of replication lag and resource-intensive long-running queries

061,965 GitHub stars

사용 사례

01Optimizing PostgreSQL autovacuum settings to manage table bloat and dead tuples

02Diagnosing database performance degradation and identifying lock contention

03Setting up automated health alerts for production database environments