Media Platform: Handling 50M Daily Requests with Edge Computing

The Challenge

StreamMedia Pro's platform was experiencing:

• High Latency: 250ms average, up to 500ms+ for international users
• Scalability Issues: Couldn't handle traffic spikes during peak hours
• High Costs: Every request hitting origin server = expensive bandwidth
• Poor User Experience: Buffering, timeouts, slow image loading
• Single Point of Failure: All traffic through one data center

Edge Computing Architecture

Global CDN Network

200+ Edge Locations

• Deployed edge functions in 200+ locations worldwide
• Automatic routing to nearest edge location
• Failover to secondary locations if primary fails
• Real-time health monitoring of all edge nodes

Intelligent Caching Strategy

• Cache-aside pattern for API responses
• Write-through caching for frequently updated content
• Cache invalidation based on content type and update frequency
• Edge-side includes for dynamic content assembly

API Edge Functions

Serverless Edge Computing

• Cloudflare Workers for API logic at the edge
• Edge functions handle authentication, rate limiting, and routing
• Data fetching from origin only when cache misses
• Response compression and optimization at the edge

Smart Routing

• Geographic routing to nearest data center
• Load balancing across edge locations
• Automatic failover and retry logic
• Request coalescing to reduce origin hits

Media Optimization

Image Optimization

• Automatic format conversion (JPEG → WebP → AVIF)
• Responsive image generation at the edge
• Lazy loading and progressive image loading
• Image compression with quality optimization

Video Streaming

• Adaptive bitrate streaming (ABR)
• Edge caching for video segments
• Prefetching next segments based on user behavior
• Multi-CDN strategy for redundancy

Caching Strategy

Multi-Layer Caching

1. Browser Cache: Long-term caching for static assets
2. Edge Cache: CDN-level caching for all content
3. Origin Cache: Application-level caching
4. Database Cache: Query result caching

Cache Policies

• Static assets: 1 year cache
• API responses: 5-60 minutes based on update frequency
• Images: 30 days cache
• Video segments: 7 days cache

Performance Improvements

| Metric | Before | After | Improvement | |--------|--------|-------|-------------| | Global Average Latency | 250ms | 45ms | 80% faster | | Cache Hit Rate | 12% | 94% | 7.8x increase | | Origin Server Load | 100% | 10% | 90% reduction | | Bandwidth Costs | $X | $X * 0.4 | 60% reduction | | Peak Request Capacity | 10M/day | 50M+/day | 5x increase | | 95th Percentile Latency | 800ms | 120ms | 85% faster |

Technical Implementation

Edge Functions Architecture

// Example: Edge function for API routing
addEventListener('fetch', event => {
  event.respondWith(handleRequest(event.request))
})

async function handleRequest(request) {
  // Check cache first
  const cache = caches.default
  const cachedResponse = await cache.match(request)
  if (cachedResponse) {
    return cachedResponse
  }
  
  // Fetch from origin if cache miss
  const response = await fetch(request)
  
  // Cache the response
  event.waitUntil(cache.put(request, response.clone()))
  
  return response
}

Caching Headers Strategy

• Static Assets: Cache-Control: public, max-age=31536000, immutable
• API Responses: Cache-Control: public, max-age=300, s-maxage=600
• Images: Cache-Control: public, max-age=2592000
• Dynamic Content: Cache-Control: public, max-age=60, must-revalidate

Geographic Distribution

• North America: 50+ edge locations
• Europe: 40+ edge locations
• Asia Pacific: 60+ edge locations
• South America: 20+ edge locations
• Africa: 15+ edge locations
• Middle East: 15+ edge locations

Cost Optimization

Bandwidth Cost Reduction

Before Edge Computing

• 100% of requests hitting origin server
• High bandwidth costs for international traffic
• Expensive data transfer between regions

After Edge Computing

• 94% of requests served from edge (cache hit)
• Only 6% of requests hit origin server
• Bandwidth costs reduced by 60%

Infrastructure Cost Savings

• Origin Server Load: Reduced by 90%, allowing for smaller infrastructure
• Database Load: Reduced by 85% due to edge caching
• CDN Costs: Offset by reduced origin bandwidth costs
• Total Infrastructure Cost: Reduced by 45%

User Experience Improvements

Latency Improvements by Region

| Region | Before | After | Improvement | |--------|--------|-------|-------------| | North America | 80ms | 25ms | 69% faster | | Europe | 120ms | 35ms | 71% faster | | Asia Pacific | 350ms | 60ms | 83% faster | | South America | 280ms | 55ms | 80% faster | | Africa | 450ms | 85ms | 81% faster |

User Metrics

• Page Load Time: Improved by 75%
• Time to First Byte (TTFB): Improved by 85%
• Video Buffering: Reduced by 90%
• Image Load Time: Improved by 80%
• API Response Time: Improved by 70%

Monitoring & Analytics

Edge Analytics

• Real-time performance monitoring at each edge location
• Geographic performance heatmaps
• Cache hit rate tracking
• Origin server load monitoring
• Error rate tracking by region

Key Metrics Tracked

• Request volume by edge location
• Cache hit/miss rates
• Latency percentiles (p50, p95, p99)
• Error rates and types
• Bandwidth usage
• Cost per request

Technologies Used

• CDN: Cloudflare (200+ edge locations)
• Edge Computing: Cloudflare Workers
• Caching: Cloudflare Cache API, Redis
• Image Optimization: Cloudflare Images
• Video Streaming: HLS, DASH with edge caching
• Monitoring: Cloudflare Analytics, Datadog
• Origin: AWS (EC2, S3, CloudFront)

Key Learnings

1. Edge computing is essential for global scale: Latency matters for user experience
2. Caching strategy is critical: 94% cache hit rate dramatically reduces costs
3. Geographic distribution matters: Users closer to edge = better performance
4. Monitoring is crucial: Need visibility into edge performance
5. Cost optimization: Edge computing can reduce costs while improving performance

Future Enhancements

With the edge infrastructure in place, we're now working on:

• AI-Powered Caching: Predictive caching based on user behavior
• Edge Machine Learning: Content personalization at the edge
• Advanced Analytics: Real-time insights from edge data
• WebRTC Optimization: Edge-based WebRTC for real-time features
• Edge Database: Read replicas at edge locations

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This case study demonstrates how edge computing can transform global performance and reduce costs simultaneously. If you're serving a global audience, edge computing should be part of your strategy.