A11 — Performance Analyzer

Name: A11 — Performance Analyzer
Availability: InStock
Author: shivpathakvw

Profile Java/Spring applications to identify performance bottlenecks and SQL inefficiencies.

2|Updated Apr 11, 2026

Search Tags:#performance #profiling #java #spring-boot #n+1 #thread-pool

Ready to run

npx skills add https://github.com/shivpathakvw/springinsight --skill a11-performance-analyzer

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: A11 — Performance Analyzer
Source: https://github.com/shivpathakvw/springinsight/tree/main/skills/a11-performance
Command: npx skills add https://github.com/shivpathakvw/springinsight --skill a11-performance-analyzer

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill helps identify performance bottlenecks, inefficient data access patterns, misconfigurations, and memory pressure points in Java and Spring Boot applications that cause latency spikes under production load.

Core Features & Use Cases

Detect N+1 query patterns, inefficient data access, and missing fetch strategies.
Identify misconfigured thread pools, memory pressure, and cache inefficiencies.
Use Case: Optimize a slow endpoint by pinpointing the root cause and proposing concrete fixes.

Quick Start

Run a production-like workload profile on a Spring Boot service to surface the top latency hotspots.

Frequently Asked Questions about A11 — Performance Analyzer

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I find N+1 query problems causing latency spikes in a Spring Boot microservice?▼

To identify N+1 queries in Spring Boot, profile data access patterns to detect missing fetch strategies and inefficient queries. This analysis surfaces SQL inefficiencies that cause latency spikes under production load.

Why does my Java application have memory pressure and slow endpoint response times?▼

Memory pressure and slow Java endpoints often stem from misconfigured thread pools and cache inefficiencies. Profiling the application under a production-like workload surfaces these top latency hotspots and data access bottlenecks.

What is the best way to profile thread pool misconfigurations in Java Spring Boot applications?▼

The best way to profile thread pool misconfigurations in Spring Boot is to run a production-like workload profile. This identifies misconfigured thread pools and memory pressure points, producing actionable metrics for tuning.

Can I get concrete metrics to optimize slow Spring Boot endpoints?▼

Yes, profiling a Spring Boot service with a production-like workload profile produces concrete metrics. These metrics identify cache misses, SQL inefficiencies, and thread pool issues to guide refactoring and tuning.

Does this performance analysis work for typical Spring Boot microservices?▼

Yes, the performance analysis is designed for typical Spring Boot microservices. It detects N+1 queries, cache misses, and thread pool misconfigurations, proposing concrete fixes to optimize slow endpoints.