Caching Configuration

CoAI.Dev's intelligent caching system optimizes performance and reduces costs by storing and reusing AI model responses for identical requests. This innovative feature significantly decreases API calls, improves response times, and provides substantial cost savings for repeated queries.

Overview

The caching system provides:

• 🎯 Smart Request Matching: Hash-based identification of identical requests
• 💰 Cost Reduction: Cached responses don't count toward usage quotas or billing
• ⚡ Performance Boost: Instant responses for cached queries
• 🔧 Flexible Configuration: Granular control over caching policies per model
• 📊 Cache Analytics: Detailed insights into cache performance and hit rates
• 🔄 Automatic Management: Intelligent cache expiration and cleanup

How Caching Works

Request Processing Pipeline

User Request → Hash Generation → Cache Lookup → Cache Hit → Instant Response
     ↓
No API Call, No Billing, Sub-second Response Time

Configuration Setup

Basic Cache Configuration

{
  "global_cache_settings": {
    "enabled": true,
    "cache_backend": "redis",
    "default_ttl": "24_hours",
    "max_memory_usage": "2GB",
    "compression_enabled": true
  }
}

Advanced Configuration

Redis Cache Backend:

{
  "redis_config": {
    "host": "localhost",
    "port": 6379,
    "password": "your-redis-password",
    "database": 1,
    "cluster_mode": false,
    "ssl_enabled": true,
    "connection_pool_size": 20
  }
}

Database Cache Backend:

{
  "database_config": {
    "table_name": "model_cache",
    "connection_pool": "cache_pool",
    "index_optimization": true,
    "automatic_cleanup": true,
    "partitioning": "monthly"
  }
}

Model-Specific Configuration

Cache Policies by Model Type

{
  "text_models": {
    "cache_enabled": true,
    "ttl": "12_hours",
    "max_entries_per_model": 15000,
    "cache_threshold": "exact_match",
    "exclude_parameters": ["user_id", "session_id"]
  }
}

Cache Analytics and Monitoring

Performance Metrics

Key Performance Indicators:

{
  "cache_metrics": {
    "hit_rate": "65.5%",
    "miss_rate": "34.5%",
    "avg_hit_response_time": "45ms",
    "avg_miss_response_time": "1250ms",
    "cost_savings": "$127.50",
    "api_calls_saved": 2847,
    "cache_size": "1.2GB",
    "cache_utilization": "78%"
  }
}

Analytics Dashboard Features:

• Real-time cache hit/miss ratios
• Cost savings calculations
• Performance improvement metrics
• Cache storage utilization
• Model-specific cache performance

Cache Health Monitoring

Health Indicators:

• Cache hit rate trends
• Response time improvements
• Storage efficiency metrics
• Error rates and cache failures
• Memory usage and optimization

Automated Alerts:

{
  "cache_alerts": {
    "low_hit_rate": {
      "threshold": "30%",
      "action": "review_cache_configuration"
    },
    "high_memory_usage": {
      "threshold": "90%",
      "action": "increase_cleanup_frequency"
    },
    "cache_errors": {
      "threshold": "5%",
      "action": "investigate_cache_backend"
    }
  }
}

Advanced Features

Cache Warm-up Strategies

Proactive Cache Population:

{
  "cache_warmup": {
    "enabled": true,
    "warmup_schedule": "daily_at_2am",
    "common_queries": [
      "most_frequent_queries_last_30_days",
      "seasonal_trending_topics",
      "business_specific_patterns"
    ],
    "parallel_warmup": true,
    "max_warmup_time": "30_minutes"
  }
}

Benefits of Cache Warm-up:

• Higher hit rates during peak hours
• Improved user experience from day one
• Reduced cold start penalties
• Better resource utilization

Cache Invalidation

Smart Invalidation Strategies:

{
  "invalidation_rules": {
    "content_updates": "invalidate_related_cache",
    "model_updates": "selective_invalidation",
    "policy_changes": "full_cache_clear",
    "user_request": "manual_invalidation"
  }
}

Invalidation Triggers:

• Content or knowledge base updates
• Model version changes
• Policy or configuration updates
• Manual administrator actions
• Time-based expiration

Multi-Tier Caching

Hierarchical Cache Strategy:

┌─────────────────┐    ┌─────────────────┐    ┌─────────────────┐
│   Memory Cache  │ ─→ │   Redis Cache   │ ─→ │ Database Cache  │
│   (L1 - Fast)   │    │  (L2 - Medium)  │    │  (L3 - Slow)    │
│   100ms TTL     │    │   1 hour TTL    │    │  24 hour TTL    │
└─────────────────┘    └─────────────────┘    └─────────────────┘

Multi-Tier Benefits:

• Optimal performance for different access patterns
• Cost-effective storage utilization
• Reduced load on backend systems
• Improved scalability

Best Practices

Cache Strategy Design

Effective Caching Strategies:

• Model Appropriateness: Cache deterministic models, not creative ones
• Parameter Inclusion: Include all relevant parameters in hash calculation
• TTL Optimization: Balance freshness with performance gains
• Size Management: Implement appropriate cleanup and eviction policies
• Monitoring: Continuously monitor and optimize cache performance

Cache Policy Template:

{
  "cache_policy_template": {
    "deterministic_models": {
      "cache_enabled": true,
      "ttl": "12_hours",
      "aggressive_caching": true
    },
    "creative_models": {
      "cache_enabled": false,
      "session_cache_only": true
    },
    "expensive_models": {
      "cache_enabled": true,
      "ttl": "24_hours",
      "max_cache_size": "large"
    }
  }
}

Performance Optimization

Cache Performance Tips:

• Use Redis for high-performance scenarios
• Implement cache preloading for common queries
• Monitor hit rates and adjust TTL accordingly
• Use compression for large responses
• Implement tiered caching for optimal cost/performance

Security Considerations

Cache Security:

• Encrypt sensitive cached content
• Implement access controls for cache management
• Regular security audits of cached data
• User data isolation in multi-tenant setups
• Secure cache key generation

Troubleshooting

Common Issues

Performance Issues

Slow Cache Operations:

• Optimize cache backend configuration
• Consider cache sharding for high volume
• Review network latency to cache backend
• Implement connection pooling
• Monitor cache backend performance

Cache Inconsistency:

• Verify cache invalidation rules
• Check for race conditions in cache updates
• Review cache key generation logic
• Implement proper locking mechanisms
• Regular cache integrity checks

Resource Preheating

Key Features

• Multi-Domain Support: Configure preheating for multiple custom domains
• Static Resource Optimization: Ideal for CSS, JS, and other static assets
• Post-Update Refresh: Refresh resources after each update to ensure stability
• CDN Performance Enhancement: Improves overall CDN service performance

Use Cases

Configuration

To enable resource preheating:

cache:
  preheating:
    enabled: true
    domains:
      - "cdn.example.com"
      - "assets.example.com"
    resources:
      - "*.css"
      - "*.js"
      - "*.png"
      - "*.jpg"
    priority: "high"
    schedule: "0 2 * * *"  # Daily at 2 AM

Important Considerations

Best Practices:

• Perform preheating during off-peak hours
• Plan preheating resources carefully to avoid unnecessary resource waste
• Monitor CDN and source server performance during preheating
• Set up alerts for high bandwidth usage

Operation Steps

1. Access CDN Console: Login to your CDN management interface
2. Select Preheating Function: Navigate to the "Resource Preheating" section
3. Configure URLs: Input the list of URLs that need preheating
4. Set Priority: Choose the preheating priority level
5. Submit Task: Submit the preheating task for execution

Monitoring and Analytics

Track preheating effectiveness through:

• Cache Hit Rates: Monitor improvement in cache performance
• Response Times: Measure reduction in resource load times
• Bandwidth Usage: Track source server load reduction
• User Experience Metrics: Monitor page load speed improvements

Intelligent caching significantly improves platform performance and reduces operational costs. Continue with Advanced Features for enterprise-grade capabilities, or explore System Settings for additional configuration options.