# Phase 6: Performance & Optimization - Detailed Implementation (Weeks 11-12, 80 hours)

## Overview

Database optimization, API optimization, and FinOps monitoring for production.

## Week 1: Database & API Optimization (40 hours)

### Day 1-2: Database Optimization (16 hours)

**Tasks:**
1. Create `backend/internal/db/optimization.go`:
   - Query optimization
   - Index tuning
   - Partition strategy
   - Connection pooling

2. Implement optimizations:
   - Analyze slow queries
   - Create missing indexes
   - Optimize joins
   - Add partitioning

3. Add monitoring:
   - Query performance metrics
   - Index usage metrics
   - Connection pool metrics

### Day 3-4: API Optimization (16 hours)

**Tasks:**
1. Create `backend/internal/api/optimization.go`:
   - Response compression
   - Pagination
   - Lazy loading
   - Batch operations

2. Implement optimizations:
   - Gzip compression
   - Cursor-based pagination
   - Lazy field loading
   - Batch endpoints

3. Add rate limiting:
   - Per-user limits
   - Per-endpoint limits
   - Burst handling

### Day 5: Testing & Validation (8 hours)

**Tasks:**
1. Write optimization tests
2. Performance benchmarking
3. Load testing
4. Stress testing
5. Verify improvements

## Week 2: FinOps & Monitoring (40 hours)

### Day 1-2: Cost Tracking (16 hours)

**Tasks:**
1. Create `backend/internal/finops/cost_tracker.go`:
   - Track API costs
   - Track database costs
   - Track storage costs
   - Track compute costs

2. Implement cost calculation:
   - VoyageAI embeddings
   - Claude API calls
   - PostgreSQL usage
   - Redis usage

3. Add cost optimization:
   - Identify expensive operations
   - Suggest optimizations
   - Set budgets & alerts

### Day 3-4: Monitoring & Dashboards (16 hours)

**Tasks:**
1. Create `backend/internal/monitoring/dashboards.go`:
   - Performance dashboards
   - Cost dashboards
   - Error dashboards
   - Usage dashboards

2. Implement metrics:
   - Request latency
   - Error rate
   - Success rate
   - Cost per request

3. Add alerting:
   - Performance alerts
   - Cost alerts
   - Error alerts
   - SLA alerts

### Day 5: Integration & Testing (8 hours)

**Tasks:**
1. Integrate cost tracking
2. Integrate monitoring
3. Setup dashboards
4. Write tests
5. Verify metrics

## Implementation Details

### Database Optimization

```go
type QueryOptimizer struct {
    db *pgxpool.Pool
}

func (qo *QueryOptimizer) AnalyzeSlowQueries(ctx context.Context) ([]SlowQuery, error) {
    // Query pg_stat_statements
    // Identify slow queries
    // Suggest indexes
}

func (qo *QueryOptimizer) CreateIndex(ctx context.Context, table, column string) error {
    // Create index if not exists
    // Analyze table
    // Update statistics
}
```

### Cost Tracker

```go
type CostTracker struct {
    db *pgxpool.Pool
}

type CostEntry struct {
    Service     string // "voyage", "claude", "postgres", "redis"
    Operation   string
    Cost        float64
    Timestamp   time.Time
}

func (ct *CostTracker) Track(ctx context.Context, entry CostEntry) error {
    // Store cost entry
    // Update totals
    // Check budgets
}
```

### Monitoring Dashboard

```go
type Dashboard struct {
    Name    string
    Metrics []Metric
}

type Metric struct {
    Name        string
    Description string
    Query       string
    Unit        string
    Threshold   float64
}
```

## Success Criteria

✅ Database optimized
✅ API optimized
✅ Cost tracking working
✅ Monitoring working
✅ Dashboards working
✅ Alerts working
✅ All tests passing

## Expected Results

- **Performance:** <100ms latency (p99)
- **Uptime:** 99.9% availability
- **Cost:** <$100/month
- **Scalability:** 10k req/s

## Optimization Checklist

**Database:**
- [ ] Analyze slow queries
- [ ] Create missing indexes
- [ ] Optimize joins
- [ ] Add partitioning
- [ ] Tune connection pool

**API:**
- [ ] Enable compression
- [ ] Add pagination
- [ ] Implement caching
- [ ] Add rate limiting
- [ ] Batch operations

**Monitoring:**
- [ ] Setup dashboards
- [ ] Configure alerts
- [ ] Track costs
- [ ] Monitor SLAs
- [ ] Review metrics

## Troubleshooting

**Issue:** Queries still slow
- Check index usage
- Check query plans
- Review optimization
- Consider partitioning

**Issue:** High costs
- Identify expensive operations
- Optimize queries
- Use caching
- Batch operations

**Issue:** Monitoring overhead
- Adjust sampling
- Optimize metrics
- Review instrumentation

## Production Readiness

✅ All phases complete
✅ All tests passing
✅ Performance optimized
✅ Costs optimized
✅ Monitoring in place
✅ Documentation complete
✅ Ready for production

## Next Steps

1. Deploy to production
2. Monitor metrics
3. Gather feedback
4. Iterate on improvements
5. Scale as needed

