Platform Improvements

Continuous platform improvements ensure YeboLearn scales reliably while maintaining exceptional performance. This document tracks infrastructure upgrades, performance optimizations, and technical debt paydown.

Last Updated: November 22, 2025

Active Platform Work

1. API Performance Optimization (Sprint 26 - In Progress)

Status: 20% Complete, Stretch Goal

Business Impact:

Faster page loads = better user experience
Reduced bounce rate
Lower infrastructure costs (fewer resources needed)
Competitive advantage (fastest platform in Africa)

Current Performance Baseline:

Student Dashboard (Most Critical):
- Load time: 2.2s (target: <1.5s)
- API response: 450ms p95 (target: <200ms)
- Database queries: 12 queries, 380ms total
- Largest query: 180ms (student progress aggregation)

Quiz Page:
- Load time: 1.2s (target: <1s) ✓
- API response: 220ms p95 (target: <200ms)
- Database queries: 6 queries, 120ms total

Course Library:
- Load time: 1.6s (target: <1.5s)
- API response: 310ms p95 (target: <200ms)
- Database queries: 8 queries, 180ms total

Optimization Strategies:

1. Database Query Optimization (3 points - In Progress)

sql

-- Problem: Student progress query taking 180ms
SELECT
  c.id, c.title,
  COUNT(DISTINCT q.id) as total_quizzes,
  COUNT(DISTINCT qa.id) as completed_quizzes,
  AVG(qa.score) as average_score
FROM courses c
LEFT JOIN quizzes q ON q.course_id = c.id
LEFT JOIN quiz_attempts qa ON qa.quiz_id = q.id
  AND qa.student_id = $1
WHERE c.id IN (SELECT course_id FROM enrollments WHERE student_id = $1)
GROUP BY c.id;

-- Execution time: 180ms
-- Rows scanned: 45,000

Solution: Add composite indexes

sql

-- Add indexes for common query patterns
CREATE INDEX idx_quiz_attempts_student_quiz
  ON quiz_attempts(student_id, quiz_id);

CREATE INDEX idx_enrollments_student_course
  ON enrollments(student_id, course_id);

CREATE INDEX idx_quizzes_course
  ON quizzes(course_id);

-- Execution time after: 35ms ✓
-- Rows scanned: 1,200
-- Improvement: 80% faster

Progress:

✅ Identified slow queries (profiling)
✅ Added indexes (deployed Nov 21)
✅ Tested performance improvement
🚧 Monitoring production impact
⏳ Additional query optimizations

Expected Impact:

Dashboard load: 2.2s → 1.5s
API p95: 450ms → 180ms
Database load: -30%

2. Redis Caching Implementation (2 points - Not Started)

Caching Strategy:

typescript

// Cache student dashboard data
export async function getStudentDashboard(studentId: string) {
  const cacheKey = `dashboard:${studentId}`;

  // Check cache first
  const cached = await redis.get(cacheKey);
  if (cached) {
    return JSON.parse(cached);
  }

  // Fetch from database
  const data = await db.student.findUnique({
    where: { id: studentId },
    include: {
      enrollments: {
        include: {
          course: true,
          quizAttempts: true,
        },
      },
    },
  });

  const dashboard = transformToDashboard(data);

  // Cache for 5 minutes
  await redis.set(
    cacheKey,
    JSON.stringify(dashboard),
    'EX',
    300
  );

  return dashboard;
}

// Invalidate cache on updates
export async function updateQuizAttempt(attempt: QuizAttempt) {
  await db.quizAttempt.update(attempt);

  // Invalidate student's dashboard cache
  await redis.del(`dashboard:${attempt.studentId}`);
}

Cache Patterns:

Cache Layer:
├─ Student Dashboards (5 min TTL)
├─ Course Listings (15 min TTL)
├─ Quiz Content (1 hour TTL)
├─ AI Responses (24 hours TTL)
└─ User Sessions (30 min TTL)

Invalidation Strategy:
- Time-based (TTL)
- Event-based (on updates)
- Manual (admin flush)

Expected Impact:

70% cache hit rate
API response: 450ms → 150ms (cached requests)
Database load: -60%
Cost savings: $100/month (fewer database resources)

Deferred to Sprint 27 (not blocking, stretch goal)

2. Frontend Bundle Optimization (Sprint 25 - Completed)

Status: Complete ✓

Results:

Before Optimization:
- Main bundle: 420 KB (gzipped)
- Initial load: 3.2s on 3G
- Time to Interactive: 4.1s

After Optimization:
- Main bundle: 280 KB (gzipped) ⬇ 33%
- Initial load: 2.2s on 3G ⬇ 31%
- Time to Interactive: 2.8s ⬇ 32%

Techniques Applied:

Code Splitting

typescript

// Lazy load AI features (large dependencies)
const AIQuizGenerator = lazy(() => import('./features/ai/QuizGenerator'));
const AIEssayGrader = lazy(() => import('./features/ai/EssayGrader'));

// Load on demand
<Suspense fallback={<Loading />}>
  <AIQuizGenerator />
</Suspense>

Tree Shaking

typescript

// Import only needed functions
import { format } from 'date-fns/format'; // Before: entire library
import { debounce } from 'lodash-es/debounce'; // Before: entire lodash

Image Optimization

typescript

// Next.js Image component (automatic optimization)
<Image
  src="/course-thumbnail.jpg"
  width={300}
  height={200}
  loading="lazy"
  quality={75}
/>

// Savings: 60% smaller images

Impact:

Better mobile experience (faster on 3G/4G)
Improved SEO (page speed is ranking factor)
Lower bounce rate (faster = more engagement)

3. Database Migration to Cloud SQL HA (Sprint 27 - Planned)

Status: Planning Phase

Current Setup:

Cloud SQL PostgreSQL 15
- Instance: db-n1-standard-2 (2 vCPU, 7.5 GB RAM)
- Storage: 100 GB SSD
- Backups: Daily automated
- High Availability: No (single instance)
- Region: africa-south1
- Cost: $150/month

Problem:

Single point of failure (no HA)
Downtime during maintenance windows
Slow failover (manual restore from backup)
Risk of data loss (up to 1 minute)

Proposed Upgrade:

Cloud SQL HA Configuration
- Primary: africa-south1-a
- Standby: africa-south1-b
- Automatic failover: <1 minute
- Synchronous replication
- Zero data loss (RPO: 0)
- 99.95% SLA (vs 99.5% current)
- Cost: $300/month (+$150)

Migration Plan (Sprint 27):

Week 1: Preparation
- [ ] Provision HA instance
- [ ] Test replication
- [ ] Verify performance (should be same)
- [ ] Plan cutover window

Week 2: Migration
- [ ] Announce maintenance window (Saturday 2 AM)
- [ ] Enable replication (30 min)
- [ ] Verify data consistency
- [ ] Update application connection string
- [ ] Monitor for issues
- [ ] Decommission old instance

Rollback Plan:
- Keep old instance for 48 hours
- Can switch back if issues

ROI Analysis:

Cost: +$150/month = $1,800/year

Benefits:
- Prevent downtime: 99.5% → 99.95% uptime
- Savings from avoided incidents: ~$5,000/year
- Customer trust and retention: Priceless
- Peace of mind: ✓

Decision: Approved for Sprint 27

4. Monitoring and Observability Enhancements (Ongoing)

Status: Continuous Improvement

Current Monitoring Stack:

Infrastructure:
✓ Google Cloud Monitoring (CPU, memory, disk)
✓ Uptime Robot (external endpoint monitoring)
✓ Cloud SQL Insights (database performance)

Application:
✓ Sentry (error tracking)
✓ Custom metrics (Prometheus)
✓ Grafana dashboards

Logging:
✓ Cloud Logging (structured logs)
✓ Log-based metrics and alerts

Recent Improvements (Sprint 25-26):

1. Custom Dashboards

YeboLearn Operations Dashboard
├─ System Health
│   ├─ API Response Time (p50, p95, p99)
│   ├─ Error Rate (%)
│   ├─ Database Performance
│   └─ Active Users
├─ Business Metrics
│   ├─ Quiz Completions (hourly)
│   ├─ AI Feature Usage
│   ├─ Payment Transactions
│   └─ User Signups
├─ Infrastructure
│   ├─ CPU/Memory Usage
│   ├─ Database Connections
│   ├─ Cloud Run Instances
│   └─ Cost Tracking
└─ AI Performance
    ├─ Gemini API Latency
    ├─ AI Feature Response Times
    ├─ Token Usage
    └─ Cost per Request

2. Proactive Alerting

yaml

# Critical Alerts (PagerDuty)
- name: API Error Rate High
  threshold: error_rate > 5% for 3 minutes
  notify: oncall-engineer

- name: Database CPU High
  threshold: cpu > 90% for 5 minutes
  notify: oncall-engineer

- name: Payment Processing Failed
  threshold: payment_failure_rate > 10% for 2 minutes
  notify: oncall-engineer + cto

# Warning Alerts (Slack)
- name: Slow API Response
  threshold: p95_latency > 1s for 10 minutes
  notify: #engineering

- name: High Memory Usage
  threshold: memory > 80% for 15 minutes
  notify: #engineering

- name: Elevated Error Rate
  threshold: error_rate > 2% for 10 minutes
  notify: #engineering

3. Real User Monitoring (RUM)

typescript

// Track real user performance
analytics.track('page_load', {
  page: window.location.pathname,
  loadTime: performance.timing.loadEventEnd - performance.timing.navigationStart,
  ttfb: performance.timing.responseStart - performance.timing.requestStart,
  domReady: performance.timing.domContentLoadedEventEnd - performance.timing.navigationStart,
  userId: user.id,
  connection: navigator.connection?.effectiveType,
});

// Aggregate and alert on degraded performance
// "p95 page load time > 3s for 15 minutes" → Alert

Impact:

Mean Time to Detect (MTTD): 10 min → 2 min
Mean Time to Resolve (MTTR): 45 min → 25 min
False positive rate: 15% → 5%

Technical Debt Paydown

Current Technical Debt Inventory

High Priority (Blocking or Risky):

1. Authentication System Refactor (8 points - Sprint 28)

Problem: Legacy auth code lacks tests, hard to extend
Impact: Blocking SSO integration, OAuth providers
Risk: Security vulnerabilities, hard to maintain
Plan: Refactor to use Passport.js, add comprehensive tests

2. Payment Idempotency (8 points - Sprint 26)

Problem: No idempotency keys, risk of duplicate charges
Impact: Customer support overhead, refund costs
Risk: User trust, financial loss
Plan: Add idempotency key validation, migration strategy
Status: In Progress (40% complete)

3. API Rate Limiting (5 points - Sprint 27)

Problem: No rate limiting on public endpoints
Impact: Vulnerable to abuse, DDoS
Risk: Service degradation, cost overruns
Plan: Implement rate limiting middleware (Redis-based)

Medium Priority (Quality of Life):

4. Code Duplication in Quiz Module (5 points - Sprint 28)

Problem: Quiz logic duplicated across 4 components
Impact: Maintenance burden, inconsistent behavior
Plan: Extract shared logic, create reusable hooks

5. Database Migration Testing (3 points - Sprint 27)

Problem: No automated migration testing
Impact: Risk of production migration failures
Plan: Add migration tests to CI pipeline

6. Outdated Dependencies (3 points - Sprint 28)

Problem: 12 dependencies >6 months old
Impact: Security vulnerabilities, missing features
Plan: Systematic update and testing

Debt Paydown Strategy

20% Sprint Capacity for Debt:

Sprint 26 (32 points total):
- New Features: 21 points (65%)
- Technical Debt: 8 points (25%) - Payment idempotency
- Bug Fixes: 3 points (10%)

Sprint 27 (28 points total):
- New Features: 16 points (57%)
- Technical Debt: 8 points (29%) - Rate limiting + DB migration tests
- Bug Fixes: 4 points (14%)

Debt Tracking:

Total Debt: 42 story points
Sprint Debt Capacity: 6-8 points
Paydown Timeline: ~6 sprints (3 months)

High Priority Debt: 21 points (target: 2 months)
Medium Priority Debt: 21 points (target: 4 months)

Infrastructure Upgrades

Completed Upgrades (Sprint 24-25)

1. Node.js 18 → 20 Upgrade

Before: Node.js 18.12
After: Node.js 20.10 LTS
Benefits:
- Performance: 10% faster V8 engine
- Security: Latest patches
- Features: Fetch API built-in
- Support: LTS until 2026

2. PostgreSQL 14 → 15 Upgrade

Before: PostgreSQL 14.8
After: PostgreSQL 15.5
Benefits:
- Performance: 15% faster queries
- Features: MERGE statement, JSON improvements
- Compression: Better storage efficiency
- Support: 5 years support

3. React 18 → 19 Upgrade

Before: React 18.2
After: React 19.0
Benefits:
- Performance: Improved rendering
- Features: Server Components, Actions
- Bundle size: 5% smaller
- DX: Better error messages

Planned Upgrades (Q1 2026)

1. TypeScript 5.2 → 5.5 (Sprint 27)

Current: 5.2.2
Target: 5.5.4
Benefits:
- Type inference improvements
- Better IDE performance
- New utility types
Effort: 2 story points
Risk: Low (mostly compatible)

2. Prisma 5.0 → 5.8 (Sprint 28)

Current: 5.0.0
Target: 5.8.0
Benefits:
- Query performance improvements
- Better TypeScript types
- New features (driver adapters)
Effort: 3 story points
Risk: Medium (test thoroughly)

3. Docker Image Optimization (Sprint 27)

Current Image: 850 MB
Target: <400 MB
Approach:
- Multi-stage builds (already done)
- Alpine base image (from debian)
- Remove dev dependencies
- Optimize layer caching
Benefits:
- 50% faster deployments
- Lower bandwidth costs
- Faster cold starts
Effort: 3 story points

Performance Benchmarks

Current Performance (November 2025)

API Performance:

Endpoint: GET /api/student/dashboard
p50: 145ms ✓ (target: <200ms)
p95: 380ms ⚠️ (target: <500ms)
p99: 820ms ✓ (target: <1s)

Endpoint: POST /api/quiz/submit
p50: 210ms ✓
p95: 450ms ✓
p99: 980ms ✓

Endpoint: POST /api/ai/generate-quiz
p50: 32s (AI latency)
p95: 48s
p99: 68s

Database Performance:

Connections:
- Active: 12 / 25 (48% utilization)
- Max: 25 (connection pool)
- Peak: 18 (during heavy load)

Query Performance:
- Average query time: 35ms
- Slowest query (p99): 280ms
- Queries per second: 45 avg, 120 peak

Index Hit Rate: 98.5% ✓ (target: >95%)
Cache Hit Rate: 94% ✓ (target: >90%)

Frontend Performance:

Lighthouse Scores (Mobile):
- Performance: 87 ⚠️ (target: >90)
- Accessibility: 95 ✓
- Best Practices: 92 ✓
- SEO: 100 ✓

Core Web Vitals:
- LCP: 2.1s ⚠️ (target: <2.5s)
- FID: 45ms ✓ (target: <100ms)
- CLS: 0.05 ✓ (target: <0.1)

Infrastructure:

Cloud Run:
- Avg instances: 2
- Max instances: 8 (during peak)
- CPU usage: 35% avg
- Memory usage: 68% avg
- Cold starts: <1% of requests

Database:
- CPU: 45% avg, 78% peak
- Memory: 62% avg
- Storage: 38 GB / 100 GB
- IOPS: 120 avg, 450 peak

Performance Targets (Q1 2026)

API Response Time:
Current p95: 380ms
Target p95: 200ms
Gap: -47%

Page Load Time:
Current LCP: 2.1s
Target LCP: 1.5s
Gap: -29%

Database Efficiency:
Current avg query: 35ms
Target avg query: 25ms
Gap: -29%

AI Response Time:
Current avg: 35s
Target avg: 20s
Gap: -43%

Achievement Plan:

Sprint 26-27: Database and caching optimization
Sprint 28-29: AI performance improvements
Sprint 30-31: Frontend optimization
Q2: Advanced optimization (CDN, edge caching)

Platform Reliability

Uptime Metrics

Current (Last 30 Days):

Uptime: 99.97%
Downtime: 13 minutes
Incidents: 2 (both resolved <1 hour)

Monthly Uptime History:
- October: 99.96%
- September: 99.91%
- August: 99.98%
- July: 99.95%

Target: 99.9% (three nines)
Achievement: ✓ Exceeding target

Incident Breakdown:

Nov 21: Database connection spike (20 min)
- Cause: Connection pool exhaustion
- Fix: Increased pool size, added monitoring
- Prevention: Alert on 80% pool usage

Nov 19: Quiz submission timeout (45 min)
- Cause: Slow query without index
- Fix: Added index, optimized query
- Prevention: Query performance monitoring

Lessons Learned:
- Need better connection pool monitoring
- Database query profiling in CI
- Faster incident response (improved monitoring)

Disaster Recovery

Backup Strategy:

Database Backups:
- Automated daily: 30 day retention
- Pre-deployment: 7 day retention
- Weekly full: 90 day retention
- Point-in-time recovery: 7 days

Application State:
- Docker images: Indefinite retention
- Git history: All commits
- Configuration: Version controlled
- Secrets: Google Secret Manager (versioned)

Recovery Objectives:

RTO (Recovery Time Objective): 1 hour
RPO (Recovery Point Objective): 1 minute

Current Achievement:
- RTO: 30 minutes (tested quarterly)
- RPO: <1 minute (continuous backups)

Current Work Overview - Sprint status
AI Features - AI development work
Integration Work - Third-party integrations
Quality Monitoring - Monitoring setup
Infrastructure - Architecture

Platform Improvements ​

Active Platform Work ​

1. API Performance Optimization (Sprint 26 - In Progress) ​

2. Frontend Bundle Optimization (Sprint 25 - Completed) ​

3. Database Migration to Cloud SQL HA (Sprint 27 - Planned) ​

4. Monitoring and Observability Enhancements (Ongoing) ​

Technical Debt Paydown ​

Current Technical Debt Inventory ​

Debt Paydown Strategy ​

Infrastructure Upgrades ​

Completed Upgrades (Sprint 24-25) ​

Planned Upgrades (Q1 2026) ​

Performance Benchmarks ​

Current Performance (November 2025) ​

Performance Targets (Q1 2026) ​

Platform Reliability ​

Uptime Metrics ​

Disaster Recovery ​

Related Documentation ​

Platform Improvements

Active Platform Work

1. API Performance Optimization (Sprint 26 - In Progress)

2. Frontend Bundle Optimization (Sprint 25 - Completed)

3. Database Migration to Cloud SQL HA (Sprint 27 - Planned)

4. Monitoring and Observability Enhancements (Ongoing)

Technical Debt Paydown

Current Technical Debt Inventory

Debt Paydown Strategy

Infrastructure Upgrades

Completed Upgrades (Sprint 24-25)

Planned Upgrades (Q1 2026)

Performance Benchmarks

Current Performance (November 2025)

Performance Targets (Q1 2026)

Platform Reliability

Uptime Metrics

Disaster Recovery

Related Documentation