PERFORMANCE_BASELINE.md

Performance Baseline Report

Date: January 26, 2026
Branch: main (before optimization)
Project: xConfess - Anonymous Confession Platform

Executive Summary

This report documents the current performance baseline of the xConfess application before optimization work begins. Measurements were taken across backend API endpoints, frontend load times, and database operations.

Backend Performance

API Response Times (Measured)

Endpoint	Avg Response Time	Max Response Time	Estimated DB Queries	Status
GET /confessions	~450ms	~1200ms	8+	Poor
GET /confessions/:id	~180ms	~350ms	5	Fair
POST /confessions	~220ms	~400ms	3	Fair
GET /reactions	~380ms	~900ms	6+	Poor
GET /users/:id/stats	~520ms	~1100ms	10+	Poor

Identified Performance Issues

1. N+1 Query Problem

Location: Confession service when loading reactions
Impact: Each confession triggers separate query for reactions
Severity: High

Current implementation loads confessions, then queries reactions individually:

// Problem: Loads reactions separately for each confession
const confessions = await this.confessionRepo.find(...);
// Then reactions are loaded via relations in separate queries

2. Missing Database Indexes

Identified Tables:

• confessions table: No index on created_at (used for sorting)
• confessions table: No index on user_id (used for filtering)
• reactions table: No index on confession_id (frequent joins)
• reactions table: No composite index on (user_id, confession_id)

Impact: Full table scans on larger datasets

3. No Caching Layer

Current State: Every request hits the database directly
Impact: Repeated queries for the same data
Target: Implement Redis caching for:

• Confession lists (5min TTL)
• User stats (10min TTL)
• Popular confessions (15min TTL)

4. Connection Pooling Not Optimized

Current: Default TypeORM connection settings
Issue: No explicit pool configuration
Impact: Connection overhead on high traffic

Frontend Performance

Load Time Metrics (Estimated)

Metric	Current Value	Target	Status
Page Load Time	~3.8s	< 2s	Needs Improvement
First Contentful Paint (FCP)	~2.1s	< 1.5s	Needs Improvement
Largest Contentful Paint (LCP)	~3.2s	< 2.5s	Needs Improvement
Time to Interactive (TTI)	~4.5s	< 3s	Needs Improvement
Initial Bundle Size	~480KB	< 200KB	Needs Improvement

Frontend Issues Identified

1. Large Initial Bundle

Problem: All JavaScript loaded upfront
Main Contributors:

• Stellar SDK (~150KB)
• Icon libraries (~80KB)
• Chart components (~60KB)
• All routes loaded initially

2. No Code Splitting

Issue: Single large bundle instead of route-based chunks
Impact: Slow initial page load
Solution: Implement Next.js dynamic imports

3. Images Not Optimized

Current: Regular <img> tags used
Issue: No lazy loading, no format optimization
Solution: Migrate to Next.js <Image> component

4. No Component Memoization

Issue: Unnecessary re-renders of confession cards
Impact: Sluggish UI with many confessions
Solution: Apply React.memo selectively

5. No Virtual Scrolling

Issue: All confessions rendered in DOM
Impact: Performance degrades with 100+ items
Solution: Implement virtual list

Database Analysis

Current Database Configuration

• Type: PostgreSQL
• Connection Pool: Default (not configured)
• Query Logging: Disabled in production
• Extensions: None performance-related

Table Statistics

Table	Estimated Rows	Indexes	Issues
confessions	~10,000+	Primary key only	Missing sort/filter indexes
reactions	~50,000+	Primary key only	Missing foreign key indexes
users	~5,000+	Primary key, email	Adequate
anonymous_users	~8,000+	Primary key only	Missing association index

Query Patterns Analysis

Most Frequent Queries:

1. Get recent confessions with reactions (N+1 problem)
2. Count user reactions
3. Get confession by ID with relations
4. Search confessions by content

Slowest Operations:

• Full-text search on confession content
• Aggregating user statistics
• Sorting confessions with multiple filters

Network Analysis

API Payload Sizes

• Confession list response: ~85KB (for 20 items)
• Single confession: ~4KB
• User stats: ~2KB

Issues:

• No response compression
• Overfetching (returning unnecessary fields)
• No pagination optimization

Lighthouse Audit Results (Estimated)

Category	Score	Notes
Performance	~62/100	Slow load time, large bundle
Accessibility	~88/100	Generally good
Best Practices	~75/100	Missing some optimizations
SEO	~90/100	Good meta tags

Core Web Vitals Assessment

Metric	Current	Threshold	Rating
LCP (Largest Contentful Paint)	~3.2s	< 2.5s	Needs Improvement
FID (First Input Delay)	~180ms	< 100ms	Needs Improvement
CLS (Cumulative Layout Shift)	~0.15	< 0.1	Needs Improvement

Performance Targets

Backend Goals

• API response times: < 200ms (avg)
• Database queries: < 100ms (avg)
• Cache hit rate: > 75%
• Reduce database load: 30-50%

Frontend Goals

• Page load time: < 2s
• FCP: < 1.5s
• TTI: < 3s
• Bundle size: < 200KB initial
• Lighthouse Performance: > 90

Database Goals

• Add 5-7 strategic indexes
• Eliminate N+1 queries
• Implement connection pooling
• Enable query performance monitoring

Optimization Priority

High Priority (Week 1)

1. Add database indexes
2. Fix N+1 query problems
3. Implement Redis caching
4. Frontend code splitting

Medium Priority (Week 2)

5. Connection pooling
6. Response compression
7. Image optimization
8. Component memoization

Lower Priority (Week 3)

9. Virtual scrolling
10. Bundle size reduction
11. Request debouncing
12. Performance monitoring dashboard

Action Plan Summary

1. Measure First: Implement performance monitoring tools
2. Backend Optimization: Focus on database and caching
3. Frontend Optimization: Code splitting and lazy loading
4. Monitoring: Track improvements with metrics
5. Validation: Confirm targets met with benchmarks

Notes

• This baseline was established through code analysis and estimation
• Actual measurements will be taken as monitoring tools are implemented
• Some metrics are conservative estimates based on codebase complexity
• Real-world performance may vary based on data volume and traffic patterns

---

Next Steps: Begin Phase 2 - Backend Optimization