performance-monitoring

name	performance-monitoring
description	Performance metrics, SLAs, dashboards, latency tracking for Resource-Adda. Use when tracking service metrics, setting SLOs, monitoring latency, or identifying bottlenecks.

Performance Monitoring

When to Use

• Tracking response times and throughput
• Monitoring resource usage
• Setting performance budgets
• Identifying performance degradation

Procedure

Phase 1: Performance Targets

Backend Response Times:

Endpoint Type	Target	P95	P99
Read (GET)	100ms	200ms	500ms
Write (POST)	200ms	400ms	800ms
Search	300ms	600ms	1000ms
Aggregation	500ms	1s	2s

Frontend Core Web Vitals:

• FCP: < 1.5s
• LCP: < 2.5s
• CLS: < 0.1
• TTI: < 3.0s

Bundle Size:

• Initial chunk: < 150KB gzipped
• Total: < 250KB gzipped

Phase 2: Backend Monitoring

The request logger middleware tracks per-request timing:

• Method, path, status code, duration in ms
• Use req.id to trace slow requests

Monitor database performance:

mongoose.set("debug", true); // Log all queries with timing

Connection pool settings to watch:

• maxPoolSize: 10, minPoolSize: 2
• serverSelectionTimeoutMS: 5000
• socketTimeoutMS: 45000

Phase 3: Frontend Monitoring

# Bundle analysis
ANALYZE=true pnpm build

# Lighthouse audit
npx lighthouse http://localhost:3000 --output=json

# Find unused packages
npx depcheck

Phase 4: Load Testing

# Install autocannon for load testing
pnpm add -D autocannon

# Test backend endpoint
npx autocannon http://localhost:4000/api/v1/vendors -c 100 -d 60

Common Issues

Issue	Solution
Slow endpoint	Check MongoDB indexes; use .lean() for read queries
High memory usage	Check for event listener leaks; monitor process.memoryUsage()
Bundle too large	Dynamic imports for below-fold components; tree-shake unused deps
Poor Lighthouse score	Optimize images with next/image; preload fonts