Scaling Considerations

📖 3 min read 📄 Part 6 of 10

Web Cache - Scaling Considerations

Horizontal Scaling

Adding Cache Nodes

  • Add nodes to handle increased traffic
  • Consistent hashing for request distribution
  • No data migration needed (stateless)
  • Gradual traffic shift to new nodes
  • Time to add node: <5 minutes

Load Balancing Strategies

  • Geographic routing (GeoDNS)
  • Round-robin with health checks
  • Least connections
  • Weighted distribution
  • Sticky sessions for cache affinity

Cache Hit Rate Optimization

Improving Hit Rate

  1. Increase Cache Size: More storage = higher hit rate
  2. Optimize TTL: Longer TTL = more hits (trade-off: freshness)
  3. Cache Warming: Pre-populate popular content
  4. Request Coalescing: Reduce duplicate origin requests
  5. Compression: Store more content in same space

Hit Rate by Content Type

  • Static assets: 95%+ (long TTL)
  • HTML pages: 85%+ (moderate TTL)
  • API responses: 70%+ (short TTL)
  • Personalized content: 50%+ (user-specific caching)

Performance Optimization

Latency Reduction

  • Multi-tier caching (memory + SSD)
  • Compression (gzip, brotli)
  • Connection pooling to origin
  • HTTP/2 and HTTP/3 support
  • Edge deployment (closer to users)

Throughput Improvement

  • Parallel request processing
  • Async I/O operations
  • Zero-copy data transfer
  • Efficient serialization
  • Batch operations

Storage Scaling

Tiered Storage

  • Hot tier (NVMe): <1ms, expensive
  • Warm tier (SSD): <5ms, moderate cost
  • Cold tier (HDD): <50ms, cheap
  • Archive (S3): <100ms, very cheap

Storage Optimization

  • Compression (3-5x space savings)
  • Deduplication for identical content
  • Automatic tier migration
  • Cleanup of expired content
  • Efficient metadata storage

Geographic Distribution

Multi-Region Deployment

  • Deploy cache nodes in multiple regions
  • Route users to nearest node
  • Reduce cross-region latency
  • Improve availability
  • Comply with data residency

Cross-Region Coordination

  • Invalidation propagation (<1s)
  • Configuration synchronization
  • Monitoring aggregation
  • Failover between regions

Cache Stampede Prevention

Strategies

  1. Request Coalescing: Single origin fetch for duplicate requests
  2. Stale-While-Revalidate: Serve stale, refresh async
  3. Probabilistic Early Expiration: Refresh before TTL
  4. Cache Locking: First request fetches, others wait

Monitoring and Alerting

Key Metrics

  • Hit rate, miss rate
  • Latency (P50, P95, P99)
  • Throughput (requests/sec)
  • Error rate
  • Resource utilization

Alerts

  • Hit rate < 85%
  • P99 latency > 10ms
  • Error rate > 1%
  • Disk usage > 90%
  • Origin errors > 5%

This scaling guide ensures the web cache can handle growth while maintaining performance and reliability.