setup-load-testing

---
allowed-tools: Read, Write, Edit, Bash
argument-hint: [testing-type] | --capacity | --stress | --spike | --endurance | --volume
description: Configure comprehensive load testing with performance metrics and bottleneck identification
---

# Setup Load Testing

Configure comprehensive load testing with performance analysis and bottleneck identification: **$ARGUMENTS**

## Current Performance Context

- Application type: !`find . -name "server.js" -o -name "app.py" -o -name "main.go" | head -1 && echo "Server application" || echo "Detect app type"`
- API endpoints: !`grep -r "app\\.get\\|app\\.post\\|@RequestMapping" . 2>/dev/null | wc -l` detected endpoints
- Database: !`find . -name "*.sql" -o -name "database.js" | head -1 && echo "Database detected" || echo "No database files"`
- Current monitoring: !`find . -name "prometheus.yml" -o -name "newrelic.js" | head -1 || echo "No monitoring detected"`

## Task

Implement comprehensive load testing with performance optimization and bottleneck analysis:

**Testing Type**: Use $ARGUMENTS to focus on capacity planning, stress testing, spike testing, endurance testing, or volume testing

**Load Testing Framework**:

1. **Strategy & Requirements** - Analyze application architecture, define testing objectives, determine scenarios, identify performance metrics
2. **Tool Selection & Setup** - Choose appropriate tools (k6, Artillery, JMeter, Gatling), install dependencies, configure environments
3. **Test Scenario Design** - Create realistic user scenarios, implement API test scripts, configure data generation, design load patterns
4. **Performance Metrics** - Configure response time monitoring, throughput measurement, error rate tracking, resource utilization monitoring
5. **Infrastructure Setup** - Configure test environments, setup monitoring dashboards, implement result collection, optimize test execution
6. **Analysis & Optimization** - Identify performance bottlenecks, analyze resource constraints, recommend optimizations, track improvements

**Advanced Features**: Distributed load generation, real-time monitoring, automated performance regression detection, CI/CD integration, chaos engineering.

**Quality Assurance**: Test reliability, result accuracy, environment consistency, monitoring completeness.

**Output**: Complete load testing setup with configured scenarios, performance monitoring, bottleneck analysis, and optimization recommendations.