How does this skill help with N+1 query detection?

It monitors for patterns where multiple identical queries are executed within a single request context, triggering alerts when the count exceeds a specific threshold (e.g., 10 queries) and suggesting eager loading fixes.

How does it handle sensitive data in SQL logs?

The skill enforces an anti-pattern check against full SQL statements with values, promoting the use of parameterized queries only to prevent PII from entering logs.

Does this skill support different database systems?

Yes, it provides standardized attributes for various systems including PostgreSQL, MySQL, and SQL Server, ensuring consistent telemetry across your stack.

What connection pool metrics are tracked?

Following the USE methodology, it tracks active and idle connections (Utilization), wait counts and durations (Saturation), and failed connection attempts (Errors).

Database Observability

Name: Database Observability
Author: nexus-labs-automation

bynexus-labs-automation

Analytics & Monitoring

Instruments database queries and connection pools to identify performance bottlenecks and architectural anti-patterns.

About

This skill enables developers to implement comprehensive database monitoring by providing standardized patterns for query tracing and connection pool metrics. It helps automate the detection of common issues like N+1 query patterns and slow SQL statements while ensuring data privacy through parameterized query logging. By applying the USE (Utilization, Saturation, and Errors) methodology to database interactions, it provides deep visibility into backend performance across multiple languages including Go, Python, Node.js, and Java.

Key Features

Automated N+1 query detection and remediation guidance
Standardized OpenTelemetry query span attributes for consistent tracing
Real-time connection pool monitoring using the USE methodology
Slow query identification with p95 threshold alerting
Secure query logging patterns to prevent PII leakage
0 GitHub stars

Use Cases

Debugging latent database performance issues in production environments
Implementing comprehensive connection pool metrics for load testing and scaling
Refactoring legacy codebases to eliminate inefficient N+1 query patterns

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add nexus-labs-automation/backend-observability database-observability

For use in Claude.ai and ChatGPT

Download Skill

GitHub