# TellerPro Scalability Optimization Guide

## Overview
This guide provides comprehensive optimization recommendations for deploying TellerPro at scale with 200 tenants, each managing 10,000+ products over 10 years of operation.

## System Requirements for Large-Scale Deployment

### Minimum Production Specifications
- **CPU**: 4+ cores (8+ recommended)
- **RAM**: 16GB+ (32GB+ recommended)
- **Storage**: 500GB+ SSD with RAID 10
- **Database**: MySQL 8.0+ or MariaDB 10.6+
- **PHP**: 8.1+ with OPcache enabled
- **Web Server**: Nginx or Apache with proper caching
- **Redis**: For caching and session management

## Database Optimization

### 1. Performance Indexes
Run the performance indexes migration to add critical indexes for large-scale operations:

```bash
mysql -u root -p tellerpro < database/migrations/add_performance_indexes.sql
```

### 2. Database Configuration (my.cnf / my.ini)
```ini
[mysqld]
# InnoDB Configuration
innodb_buffer_pool_size = 8G  # 70-80% of available RAM
innodb_log_file_size = 512M
innodb_flush_log_at_trx_commit = 2
innodb_flush_method = O_DIRECT
innodb_file_per_table = 1

# Query Cache (MySQL 5.7 and below)
query_cache_type = 1
query_cache_size = 256M

# Connection Management
max_connections = 500
max_user_connections = 200
wait_timeout = 600
interactive_timeout = 600

# Performance Optimization
tmp_table_size = 256M
max_heap_table_size = 256M
sort_buffer_size = 4M
read_buffer_size = 2M
read_rnd_buffer_size = 8M
join_buffer_size = 4M

# Binary Logging (for replication/backup)
log_bin = mysql-bin
binlog_format = ROW
expire_logs_days = 7
```

### 3. Table Partitioning Strategy
For tables that will grow significantly over 10 years, implement partitioning:

```sql
-- Partition stock_movements by year
ALTER TABLE stock_movements 
PARTITION BY RANGE (YEAR(created_at)) (
    PARTITION p2024 VALUES LESS THAN (2025),
    PARTITION p2025 VALUES LESS THAN (2026),
    PARTITION p2026 VALUES LESS THAN (2027),
    PARTITION p2027 VALUES LESS THAN (2028),
    PARTITION p2028 VALUES LESS THAN (2029),
    PARTITION p2029 VALUES LESS THAN (2030),
    PARTITION p2030 VALUES LESS THAN (2031),
    PARTITION p_future VALUES LESS THAN MAXVALUE
);

-- Partition sales by year
ALTER TABLE sales 
PARTITION BY RANGE (YEAR(created_at)) (
    PARTITION p2024 VALUES LESS THAN (2025),
    PARTITION p2025 VALUES LESS THAN (2026),
    PARTITION p2026 VALUES LESS THAN (2027),
    PARTITION p2027 VALUES LESS THAN (2028),
    PARTITION p2028 VALUES LESS THAN (2029),
    PARTITION p2029 VALUES LESS THAN (2030),
    PARTITION p2030 VALUES LESS THAN (2031),
    PARTITION p_future VALUES LESS THAN MAXVALUE
);

-- Partition purchases by year
ALTER TABLE purchases 
PARTITION BY RANGE (YEAR(created_at)) (
    PARTITION p2024 VALUES LESS THAN (2025),
    PARTITION p2025 VALUES LESS THAN (2026),
    PARTITION p2026 VALUES LESS THAN (2027),
    PARTITION p2027 VALUES LESS THAN (2028),
    PARTITION p2028 VALUES LESS THAN (2029),
    PARTITION p2029 VALUES LESS THAN (2030),
    PARTITION p2030 VALUES LESS THAN (2031),
    PARTITION p_future VALUES LESS THAN MAXVALUE
);
```

### 4. Data Archival Strategy
Implement automated archival for data older than 3 years:

```sql
-- Create archival tables
CREATE TABLE sales_archive LIKE sales;
CREATE TABLE sale_items_archive LIKE sale_items;
CREATE TABLE purchases_archive LIKE purchases;
CREATE TABLE purchase_items_archive LIKE purchase_items;
CREATE TABLE stock_movements_archive LIKE stock_movements;

-- Archive old data (run monthly via cron)
INSERT INTO sales_archive SELECT * FROM sales WHERE created_at < DATE_SUB(NOW(), INTERVAL 3 YEAR);
DELETE FROM sales WHERE created_at < DATE_SUB(NOW(), INTERVAL 3 YEAR);
```

## Caching Strategy

### 1. Redis Configuration
```ini
# redis.conf
maxmemory 2gb
maxmemory-policy allkeys-lru
save 900 1
save 300 10
save 60 10000
```

### 2. Cache Implementation
The following reports now have caching implemented (5-minute cache):
- Stock Valuation Report
- Sales Report
- Purchase Items Report
- Inventory Report

Cache keys are based on: `{report_type}_{tenant_id}_{page}_{per_page}_{filter_hash}`

### 3. Cache Invalidation
Implement cache invalidation on critical operations:
- After stock adjustments
- After sales/purchases
- After product updates
- After location changes

## PHP Optimization

### 1. OPcache Configuration (php.ini)
```ini
opcache.enable=1
opcache.memory_consumption=256
opcache.interned_strings_buffer=16
opcache.max_accelerated_files=10000
opcache.revalidate_freq=60
opcache.fast_shutdown=1
opcache.enable_cli=1
```

### 2. Memory Limit
```ini
memory_limit = 512M
```

### 3. Execution Time
```ini
max_execution_time = 300
max_input_time = 300
```

## Web Server Configuration

### Nginx Configuration
```nginx
server {
    listen 80;
    server_name yourdomain.com;
    root /var/www/tellerpro/public;
    index index.php;

    # Enable gzip compression
    gzip on;
    gzip_types text/plain text/css application/json application/javascript text/xml application/xml application/xml+rss text/javascript;
    gzip_min_length 1000;

    # Enable caching for static assets
    location ~* \.(jpg|jpeg|png|gif|ico|css|js)$ {
        expires 30d;
        add_header Cache-Control "public, immutable";
    }

    # PHP-FPM configuration
    location ~ \.php$ {
        try_files $uri =404;
        fastcgi_pass unix:/var/run/php/php8.1-fpm.sock;
        fastcgi_index index.php;
        fastcgi_param SCRIPT_FILENAME $document_root$fastcgi_script_name;
        include fastcgi_params;
        fastcgi_buffer_size 128k;
        fastcgi_buffers 4 256k;
        fastcgi_busy_buffers_size 256k;
    }
}
```

### PHP-FPM Configuration (www.conf)
```ini
pm = dynamic
pm.max_children = 50
pm.start_servers = 10
pm.min_spare_servers = 5
pm.max_spare_servers = 20
pm.max_requests = 500
```

## Monitoring and Maintenance

### 1. Database Monitoring
Monitor these metrics regularly:
- Query execution time
- Slow query log
- Table sizes
- Index usage
- Connection count

### 2. Application Monitoring
- Response times
- Memory usage
- Cache hit rates
- Error rates

### 3. Regular Maintenance Tasks
```bash
# Weekly database optimization
mysql -u root -p tellerpro -e "OPTIMIZE TABLE sales, purchase_items, stock_movements;"

# Monthly index analysis
mysql -u root -p tellerpro -e "ANALYZE TABLE sales, purchase_items, stock_movements;"

# Quarterly archival of old data
# Implement automated archival script
```

## Load Balancing (Optional for High Traffic)

For very high traffic scenarios, implement load balancing:

### 1. Database Read Replicas
- Set up MySQL read replicas
- Configure application to read from replicas for reporting queries
- Write operations go to master

### 2. Application Load Balancing
- Use Nginx as load balancer
- Deploy multiple application servers
- Use Redis for shared sessions and cache

## Backup Strategy

### 1. Database Backups
```bash
# Daily full backup
mysqldump -u root -p tellerpro > backup_$(date +%Y%m%d).sql

# Incremental backups (binlog)
# Configure binlog retention for point-in-time recovery
```

### 2. Application Backups
- Code repository (Git)
- Configuration files
- Uploaded files (images, documents)

## Security Considerations

### 1. Database Security
- Use strong passwords
- Restrict database user privileges
- Enable SSL/TLS for database connections
- Regular security updates

### 2. Application Security
- Keep PHP and dependencies updated
- Implement rate limiting
- Use HTTPS everywhere
- Regular security audits

## Performance Testing

### 1. Load Testing
Use tools like Apache JMeter or Locust to test:
- Concurrent user capacity
- Report generation performance
- API response times
- Database query performance

### 2. Benchmark Results
Target performance metrics:
- Page load time: < 2 seconds
- Report generation: < 5 seconds
- API response: < 200ms
- Database queries: < 100ms (average)

## Troubleshooting

### Common Issues and Solutions

#### 1. Slow Report Generation
**Symptoms**: Reports taking > 10 seconds
**Solutions**:
- Check query execution plan with EXPLAIN
- Verify indexes are being used
- Increase cache duration
- Implement query result caching

#### 2. High Database CPU Usage
**Symptoms**: Database CPU consistently > 80%
**Solutions**:
- Check for missing indexes
- Optimize slow queries
- Increase innodb_buffer_pool_size
- Consider read replicas

#### 3. Memory Issues
**Symptoms**: PHP out of memory errors
**Solutions**:
- Increase PHP memory_limit
- Optimize data fetching (use pagination)
- Implement result streaming for large datasets
- Check for memory leaks in custom code

## Deployment Checklist

Before going to production with large-scale deployment:

- [ ] Run performance indexes migration
- [ ] Configure database settings for production
- [ ] Implement table partitioning
- [ ] Set up Redis for caching
- [ ] Configure OPcache
- [ ] Set up automated backups
- [ ] Implement monitoring
- [ ] Configure load balancing (if needed)
- [ ] Set up archival strategy
- [ ] Perform load testing
- [ ] Document disaster recovery plan
- [ ] Train operations team

## Support and Maintenance

### Recommended Support Team Structure
- Database Administrator
- DevOps Engineer
- PHP Developer
- System Administrator

### Escalation Procedures
1. Performance degradation > 20%: Investigate within 1 hour
2. Service outage: Immediate response, target < 15 min resolution
3. Data integrity issues: Immediate response, engage DBA

## Conclusion

Following this optimization guide will ensure TellerPro can handle:
- 200 concurrent tenants
- 10,000+ products per tenant (2M+ total products)
- 10 years of data accumulation
- High transaction volumes

Regular monitoring and maintenance are essential for sustained performance at scale.
