Chapter 12: Content Delivery & Edge Computing
Overview
Content Delivery Networks (CDNs) and edge computing bring content and computation closer to users, reducing latency and improving user experience. This chapter covers CDN architecture, edge computing patterns, and global distribution strategies.
Content Delivery Networks (CDN)
CDN Architecture
CDN Implementation Example (Python)
python
import hashlib
import time
import asyncio
from typing import Dict, List, Optional, Tuple
from dataclasses import dataclass
from enum import Enum
import aiohttp
import json
class CacheStatus(Enum):
HIT = "hit"
MISS = "miss"
STALE = "stale"
EXPIRED = "expired"
@dataclass
class CacheEntry:
content: bytes
content_type: str
etag: str
last_modified: float
expires_at: float
cache_control: str
size_bytes: int
@dataclass
class EdgeLocation:
id: str
region: str
country: str
city: str
latitude: float
longitude: float
capacity_gbps: float
current_load: float
@dataclass
class CDNRequest:
url: str
method: str
headers: Dict[str, str]
client_ip: str
user_agent: str
timestamp: float
@dataclass
class CDNResponse:
status_code: int
headers: Dict[str, str]
content: bytes
cache_status: CacheStatus
edge_location: str
response_time_ms: float
class EdgeCache:
def __init__(self, max_size_gb: float = 100.0):
self.cache: Dict[str, CacheEntry] = {}
self.max_size_bytes = int(max_size_gb * 1024 * 1024 * 1024)
self.current_size_bytes = 0
self.access_times: Dict[str, float] = {}
def _generate_cache_key(self, url: str, headers: Dict[str, str]) -> str:
"""Generate cache key from URL and relevant headers"""
# Include headers that affect caching
cache_headers = {
'accept-encoding': headers.get('accept-encoding', ''),
'accept-language': headers.get('accept-language', ''),
'user-agent': headers.get('user-agent', '')
}
key_data = f"{url}:{json.dumps(cache_headers, sort_keys=True)}"
return hashlib.sha256(key_data.encode()).hexdigest()
def get(self, url: str, headers: Dict[str, str]) -> Tuple[Optional[CacheEntry], CacheStatus]:
"""Get content from cache"""
cache_key = self._generate_cache_key(url, headers)
current_time = time.time()
if cache_key not in self.cache:
return None, CacheStatus.MISS
entry = self.cache[cache_key]
# Check if content has expired
if current_time > entry.expires_at:
self._evict(cache_key)
return None, CacheStatus.EXPIRED
# Update access time for LRU
self.access_times[cache_key] = current_time
# Check if content is stale but still usable
if 'max-age' in entry.cache_control:
max_age = int(entry.cache_control.split('max-age=')[1].split(',')[0])
if current_time - entry.last_modified > max_age:
return entry, CacheStatus.STALE
return entry, CacheStatus.HIT
def put(self, url: str, headers: Dict[str, str], entry: CacheEntry) -> bool:
"""Store content in cache"""
cache_key = self._generate_cache_key(url, headers)
# Check if we need to make space
if self.current_size_bytes + entry.size_bytes > self.max_size_bytes:
if not self._make_space(entry.size_bytes):
return False # Cannot make enough space
# Remove old entry if exists
if cache_key in self.cache:
self._evict(cache_key)
# Add new entry
self.cache[cache_key] = entry
self.current_size_bytes += entry.size_bytes
self.access_times[cache_key] = time.time()
return True
def _make_space(self, required_bytes: int) -> bool:
"""Make space using LRU eviction"""
# Sort by access time (LRU first)
sorted_keys = sorted(self.access_times.keys(),
key=lambda k: self.access_times[k])
freed_bytes = 0
for cache_key in sorted_keys:
if freed_bytes >= required_bytes:
break
entry = self.cache[cache_key]
freed_bytes += entry.size_bytes
self._evict(cache_key)
return freed_bytes >= required_bytes
def _evict(self, cache_key: str):
"""Remove entry from cache"""
if cache_key in self.cache:
entry = self.cache[cache_key]
self.current_size_bytes -= entry.size_bytes
del self.cache[cache_key]
del self.access_times[cache_key]
def get_stats(self) -> Dict:
"""Get cache statistics"""
return {
'total_entries': len(self.cache),
'size_bytes': self.current_size_bytes,
'size_gb': self.current_size_bytes / (1024 * 1024 * 1024),
'utilization_percent': (self.current_size_bytes / self.max_size_bytes) * 100
}
class CDNEdgeServer:
def __init__(self, edge_location: EdgeLocation, origin_servers: List[str]):
self.edge_location = edge_location
self.origin_servers = origin_servers
self.cache = EdgeCache()
self.request_count = 0
self.cache_hit_count = 0
self.bandwidth_usage_mbps = 0.0
async def handle_request(self, request: CDNRequest) -> CDNResponse:
"""Handle incoming request"""
start_time = time.time()
self.request_count += 1
# Check cache first
cache_entry, cache_status = self.cache.get(request.url, request.headers)
if cache_status == CacheStatus.HIT:
self.cache_hit_count += 1
response_time = (time.time() - start_time) * 1000
return CDNResponse(
status_code=200,
headers={
'content-type': cache_entry.content_type,
'etag': cache_entry.etag,
'cache-control': cache_entry.cache_control,
'x-cache': 'HIT',
'x-edge-location': self.edge_location.id
},
content=cache_entry.content,
cache_status=cache_status,
edge_location=self.edge_location.id,
response_time_ms=response_time
)
# Cache miss - fetch from origin
try:
origin_response = await self._fetch_from_origin(request)
# Cache the response if cacheable
if self._is_cacheable(origin_response):
cache_entry = self._create_cache_entry(origin_response)
self.cache.put(request.url, request.headers, cache_entry)
response_time = (time.time() - start_time) * 1000
return CDNResponse(
status_code=origin_response['status'],
headers={
**origin_response['headers'],
'x-cache': 'MISS',
'x-edge-location': self.edge_location.id
},
content=origin_response['content'],
cache_status=CacheStatus.MISS,
edge_location=self.edge_location.id,
response_time_ms=response_time
)
except Exception as e:
response_time = (time.time() - start_time) * 1000
return CDNResponse(
status_code=502,
headers={'x-edge-location': self.edge_location.id},
content=b'Bad Gateway',
cache_status=CacheStatus.MISS,
edge_location=self.edge_location.id,
response_time_ms=response_time
)
async def _fetch_from_origin(self, request: CDNRequest) -> Dict:
"""Fetch content from origin server"""
# Try origin servers in order
for origin_server in self.origin_servers:
try:
async with aiohttp.ClientSession() as session:
async with session.request(
method=request.method,
url=f"{origin_server}{request.url}",
headers=request.headers,
timeout=aiohttp.ClientTimeout(total=30)
) as response:
content = await response.read()
return {
'status': response.status,
'headers': dict(response.headers),
'content': content
}
except Exception as e:
print(f"Failed to fetch from {origin_server}: {e}")
continue
raise Exception("All origin servers failed")
def _is_cacheable(self, response: Dict) -> bool:
"""Determine if response is cacheable"""
# Don't cache error responses
if response['status'] >= 400:
return False
# Check cache-control headers
cache_control = response['headers'].get('cache-control', '')
if 'no-cache' in cache_control or 'no-store' in cache_control:
return False
# Check for explicit caching headers
if 'expires' in response['headers'] or 'max-age' in cache_control:
return True
# Default caching for static content
content_type = response['headers'].get('content-type', '')
static_types = ['image/', 'text/css', 'application/javascript', 'font/']
return any(content_type.startswith(t) for t in static_types)
def _create_cache_entry(self, response: Dict) -> CacheEntry:
"""Create cache entry from origin response"""
content = response['content']
headers = response['headers']
current_time = time.time()
# Calculate expiration time
expires_at = current_time + 3600 # Default 1 hour
cache_control = headers.get('cache-control', '')
if 'max-age' in cache_control:
max_age = int(cache_control.split('max-age=')[1].split(',')[0])
expires_at = current_time + max_age
elif 'expires' in headers:
# Parse expires header (simplified)
expires_at = current_time + 3600
# Generate ETag if not present
etag = headers.get('etag', hashlib.md5(content).hexdigest())
return CacheEntry(
content=content,
content_type=headers.get('content-type', 'application/octet-stream'),
etag=etag,
last_modified=current_time,
expires_at=expires_at,
cache_control=cache_control,
size_bytes=len(content)
)
def get_performance_stats(self) -> Dict:
"""Get edge server performance statistics"""
cache_hit_rate = (self.cache_hit_count / self.request_count * 100) if self.request_count > 0 else 0
return {
'edge_location': self.edge_location.id,
'region': self.edge_location.region,
'total_requests': self.request_count,
'cache_hit_rate_percent': cache_hit_rate,
'bandwidth_usage_mbps': self.bandwidth_usage_mbps,
'load_percent': self.edge_location.current_load,
'cache_stats': self.cache.get_stats()
}
Edge Computing
Edge Function Implementation
Serverless Edge Functions (Python)
python
import json
import time
import asyncio
from typing import Dict, Any, Callable, List
from dataclasses import dataclass
from enum import Enum
class EdgeFunctionType(Enum):
REQUEST_MODIFIER = "request_modifier"
RESPONSE_MODIFIER = "response_modifier"
AUTHENTICATION = "authentication"
RATE_LIMITING = "rate_limiting"
A_B_TESTING = "a_b_testing"
PERSONALIZATION = "personalization"
@dataclass
class EdgeFunctionConfig:
name: str
function_type: EdgeFunctionType
enabled: bool
priority: int
timeout_ms: int
memory_limit_mb: int
environment_variables: Dict[str, str]
@dataclass
class EdgeRequest:
method: str
url: str
headers: Dict[str, str]
body: bytes
client_ip: str
user_agent: str
geo_location: Dict[str, str]
timestamp: float
@dataclass
class EdgeResponse:
status_code: int
headers: Dict[str, str]
body: bytes
modified: bool = False
class EdgeFunctionRuntime:
def __init__(self):
self.functions: Dict[str, Callable] = {}
self.configs: Dict[str, EdgeFunctionConfig] = {}
self.execution_stats: Dict[str, Dict] = {}
def register_function(self, config: EdgeFunctionConfig, function: Callable):
"""Register an edge function"""
self.functions[config.name] = function
self.configs[config.name] = config
self.execution_stats[config.name] = {
'total_executions': 0,
'total_duration_ms': 0,
'errors': 0,
'timeouts': 0
}
async def execute_request_functions(self, request: EdgeRequest) -> EdgeRequest:
"""Execute request modifier functions"""
modified_request = request
# Get request modifier functions sorted by priority
request_functions = [
(name, func) for name, func in self.functions.items()
if (self.configs[name].function_type == EdgeFunctionType.REQUEST_MODIFIER and
self.configs[name].enabled)
]
request_functions.sort(key=lambda x: self.configs[x[0]].priority)
for func_name, func in request_functions:
try:
start_time = time.time()
# Execute function with timeout
modified_request = await asyncio.wait_for(
func(modified_request),
timeout=self.configs[func_name].timeout_ms / 1000
)
# Update stats
duration_ms = (time.time() - start_time) * 1000
self._update_stats(func_name, duration_ms, success=True)
except asyncio.TimeoutError:
self._update_stats(func_name, 0, timeout=True)
print(f"Edge function {func_name} timed out")
except Exception as e:
self._update_stats(func_name, 0, error=True)
print(f"Edge function {func_name} failed: {e}")
return modified_request
async def execute_response_functions(self, request: EdgeRequest,
response: EdgeResponse) -> EdgeResponse:
"""Execute response modifier functions"""
modified_response = response
# Get response modifier functions sorted by priority
response_functions = [
(name, func) for name, func in self.functions.items()
if (self.configs[name].function_type == EdgeFunctionType.RESPONSE_MODIFIER and
self.configs[name].enabled)
]
response_functions.sort(key=lambda x: self.configs[x[0]].priority)
for func_name, func in response_functions:
try:
start_time = time.time()
# Execute function with timeout
modified_response = await asyncio.wait_for(
func(request, modified_response),
timeout=self.configs[func_name].timeout_ms / 1000
)
# Update stats
duration_ms = (time.time() - start_time) * 1000
self._update_stats(func_name, duration_ms, success=True)
except asyncio.TimeoutError:
self._update_stats(func_name, 0, timeout=True)
print(f"Edge function {func_name} timed out")
except Exception as e:
self._update_stats(func_name, 0, error=True)
print(f"Edge function {func_name} failed: {e}")
return modified_response
def _update_stats(self, func_name: str, duration_ms: float,
success: bool = False, error: bool = False, timeout: bool = False):
"""Update function execution statistics"""
stats = self.execution_stats[func_name]
stats['total_executions'] += 1
if success:
stats['total_duration_ms'] += duration_ms
elif error:
stats['errors'] += 1
elif timeout:
stats['timeouts'] += 1
def get_function_stats(self) -> Dict[str, Dict]:
"""Get execution statistics for all functions"""
result = {}
for func_name, stats in self.execution_stats.items():
avg_duration = 0
if stats['total_executions'] > stats['errors'] + stats['timeouts']:
successful_executions = stats['total_executions'] - stats['errors'] - stats['timeouts']
avg_duration = stats['total_duration_ms'] / successful_executions
result[func_name] = {
'total_executions': stats['total_executions'],
'average_duration_ms': avg_duration,
'error_rate_percent': (stats['errors'] / stats['total_executions'] * 100) if stats['total_executions'] > 0 else 0,
'timeout_rate_percent': (stats['timeouts'] / stats['total_executions'] * 100) if stats['total_executions'] > 0 else 0,
'enabled': self.configs[func_name].enabled
}
return result
# Example edge functions
async def geo_redirect_function(request: EdgeRequest) -> EdgeRequest:
"""Redirect users based on geographic location"""
country = request.geo_location.get('country', 'US')
# Redirect EU users to EU-specific content
if country in ['DE', 'FR', 'IT', 'ES', 'NL', 'GB']:
if not request.url.startswith('/eu/'):
request.url = f"/eu{request.url}"
return request
async def security_headers_function(request: EdgeRequest, response: EdgeResponse) -> EdgeResponse:
"""Add security headers to response"""
security_headers = {
'X-Content-Type-Options': 'nosniff',
'X-Frame-Options': 'DENY',
'X-XSS-Protection': '1; mode=block',
'Strict-Transport-Security': 'max-age=31536000; includeSubDomains',
'Content-Security-Policy': "default-src 'self'; script-src 'self' 'unsafe-inline'"
}
response.headers.update(security_headers)
response.modified = True
return response
async def a_b_testing_function(request: EdgeRequest) -> EdgeRequest:
"""Implement A/B testing logic"""
import hashlib
# Use client IP for consistent assignment
user_hash = int(hashlib.md5(request.client_ip.encode()).hexdigest(), 16)
variant = 'A' if user_hash % 2 == 0 else 'B'
# Add variant header
request.headers['X-AB-Variant'] = variant
# Modify URL for variant B
if variant == 'B' and '/api/' in request.url:
request.url = request.url.replace('/api/', '/api/v2/')
return request
async def rate_limiting_function(request: EdgeRequest) -> EdgeRequest:
"""Implement rate limiting at the edge"""
# Simple in-memory rate limiting (in production, use distributed cache)
rate_limit_store = {}
client_key = request.client_ip
current_time = int(time.time())
window_size = 60 # 1 minute window
max_requests = 100
# Clean old entries
rate_limit_store = {
k: v for k, v in rate_limit_store.items()
if current_time - v['window_start'] < window_size
}
if client_key not in rate_limit_store:
rate_limit_store[client_key] = {
'count': 1,
'window_start': current_time
}
else:
entry = rate_limit_store[client_key]
if current_time - entry['window_start'] >= window_size:
# Reset window
entry['count'] = 1
entry['window_start'] = current_time
else:
entry['count'] += 1
# Check rate limit
if rate_limit_store[client_key]['count'] > max_requests:
# Return rate limit exceeded response
raise Exception("Rate limit exceeded")
return request
# Setup edge function runtime
runtime = EdgeFunctionRuntime()
# Register functions
runtime.register_function(
EdgeFunctionConfig(
name="geo_redirect",
function_type=EdgeFunctionType.REQUEST_MODIFIER,
enabled=True,
priority=1,
timeout_ms=100,
memory_limit_mb=128,
environment_variables={}
),
geo_redirect_function
)
runtime.register_function(
EdgeFunctionConfig(
name="security_headers",
function_type=EdgeFunctionType.RESPONSE_MODIFIER,
enabled=True,
priority=1,
timeout_ms=50,
memory_limit_mb=64,
environment_variables={}
),
security_headers_function
)
runtime.register_function(
EdgeFunctionConfig(
name="a_b_testing",
function_type=EdgeFunctionType.REQUEST_MODIFIER,
enabled=True,
priority=2,
timeout_ms=100,
memory_limit_mb=128,
environment_variables={}
),
a_b_testing_function
)
Global Distribution Strategies
Intelligent Routing
Geographic and Performance-based Routing
python
import math
import time
from typing import Dict, List, Optional, Tuple
from dataclasses import dataclass
from enum import Enum
class RoutingStrategy(Enum):
GEOGRAPHIC = "geographic"
PERFORMANCE = "performance"
LOAD_BASED = "load_based"
HYBRID = "hybrid"
@dataclass
class GeographicLocation:
latitude: float
longitude: float
country: str
region: str
city: str
@dataclass
class EdgeServerMetrics:
server_id: str
location: GeographicLocation
current_load_percent: float
average_response_time_ms: float
bandwidth_utilization_percent: float
health_score: float # 0.0 to 1.0
last_updated: float
class IntelligentRouter:
def __init__(self, strategy: RoutingStrategy = RoutingStrategy.HYBRID):
self.strategy = strategy
self.edge_servers: Dict[str, EdgeServerMetrics] = {}
self.performance_history: Dict[str, List[float]] = {}
self.routing_weights = {
'distance': 0.3,
'performance': 0.4,
'load': 0.3
}
def register_edge_server(self, metrics: EdgeServerMetrics):
"""Register an edge server"""
self.edge_servers[metrics.server_id] = metrics
if metrics.server_id not in self.performance_history:
self.performance_history[metrics.server_id] = []
def update_server_metrics(self, server_id: str, metrics: EdgeServerMetrics):
"""Update server metrics"""
if server_id in self.edge_servers:
self.edge_servers[server_id] = metrics
# Update performance history
history = self.performance_history[server_id]
history.append(metrics.average_response_time_ms)
# Keep only recent history (last 100 measurements)
if len(history) > 100:
history.pop(0)
def calculate_distance(self, client_location: GeographicLocation,
server_location: GeographicLocation) -> float:
"""Calculate distance between client and server using Haversine formula"""
# Convert latitude and longitude from degrees to radians
lat1, lon1 = math.radians(client_location.latitude), math.radians(client_location.longitude)
lat2, lon2 = math.radians(server_location.latitude), math.radians(server_location.longitude)
# Haversine formula
dlat = lat2 - lat1
dlon = lon2 - lon1
a = math.sin(dlat/2)**2 + math.cos(lat1) * math.cos(lat2) * math.sin(dlon/2)**2
c = 2 * math.asin(math.sqrt(a))
# Radius of earth in kilometers
r = 6371
return c * r
def calculate_server_score(self, client_location: GeographicLocation,
server_metrics: EdgeServerMetrics) -> float:
"""Calculate overall score for a server"""
# Distance score (lower distance = higher score)
distance_km = self.calculate_distance(client_location, server_metrics.location)
max_distance = 20000 # Maximum possible distance (half earth circumference)
distance_score = 1.0 - (distance_km / max_distance)
# Performance score (lower response time = higher score)
max_response_time = 2000 # 2 seconds
performance_score = max(0, 1.0 - (server_metrics.average_response_time_ms / max_response_time))
# Load score (lower load = higher score)
load_score = 1.0 - (server_metrics.current_load_percent / 100)
# Health score (already normalized 0-1)
health_score = server_metrics.health_score
# Weighted combination
if self.strategy == RoutingStrategy.GEOGRAPHIC:
return distance_score * 0.8 + health_score * 0.2
elif self.strategy == RoutingStrategy.PERFORMANCE:
return performance_score * 0.7 + health_score * 0.3
elif self.strategy == RoutingStrategy.LOAD_BASED:
return load_score * 0.7 + health_score * 0.3
else: # HYBRID
return (
distance_score * self.routing_weights['distance'] +
performance_score * self.routing_weights['performance'] +
load_score * self.routing_weights['load']
) * health_score # Health as a multiplier
def select_edge_server(self, client_location: GeographicLocation,
request_type: str = 'default') -> Optional[str]:
"""Select the best edge server for a client"""
if not self.edge_servers:
return None
# Filter healthy servers
healthy_servers = {
server_id: metrics for server_id, metrics in self.edge_servers.items()
if metrics.health_score > 0.5 and metrics.current_load_percent < 95
}
if not healthy_servers:
return None
# Calculate scores for all healthy servers
server_scores = []
for server_id, metrics in healthy_servers.items():
score = self.calculate_server_score(client_location, metrics)
server_scores.append((server_id, score))
# Sort by score (highest first)
server_scores.sort(key=lambda x: x[1], reverse=True)
# Return the best server
return server_scores[0][0]
def get_routing_recommendations(self, client_location: GeographicLocation) -> List[Tuple[str, float]]:
"""Get top 3 server recommendations with scores"""
recommendations = []
for server_id, metrics in self.edge_servers.items():
if metrics.health_score > 0.3: # Include marginally healthy servers
score = self.calculate_server_score(client_location, metrics)
recommendations.append((server_id, score))
# Sort by score and return top 3
recommendations.sort(key=lambda x: x[1], reverse=True)
return recommendations[:3]
def optimize_routing_weights(self, performance_data: Dict[str, List[float]]):
"""Optimize routing weights based on historical performance"""
# Simple optimization based on average performance
# In production, use more sophisticated ML algorithms
total_performance = 0
server_count = 0
for server_id, response_times in performance_data.items():
if response_times:
avg_response_time = sum(response_times) / len(response_times)
total_performance += avg_response_time
server_count += 1
if server_count > 0:
avg_global_performance = total_performance / server_count
# Adjust weights based on global performance
if avg_global_performance > 500: # High latency
self.routing_weights['distance'] = 0.5
self.routing_weights['performance'] = 0.3
self.routing_weights['load'] = 0.2
elif avg_global_performance < 100: # Low latency
self.routing_weights['distance'] = 0.2
self.routing_weights['performance'] = 0.3
self.routing_weights['load'] = 0.5
def get_routing_stats(self) -> Dict:
"""Get routing statistics"""
total_servers = len(self.edge_servers)
healthy_servers = sum(1 for m in self.edge_servers.values() if m.health_score > 0.5)
avg_load = sum(m.current_load_percent for m in self.edge_servers.values()) / total_servers if total_servers > 0 else 0
avg_response_time = sum(m.average_response_time_ms for m in self.edge_servers.values()) / total_servers if total_servers > 0 else 0
return {
'total_servers': total_servers,
'healthy_servers': healthy_servers,
'health_percentage': (healthy_servers / total_servers * 100) if total_servers > 0 else 0,
'average_load_percent': avg_load,
'average_response_time_ms': avg_response_time,
'routing_strategy': self.strategy.value,
'routing_weights': self.routing_weights
}
Real-World Examples
Cloudflare's Edge Network
Global Edge Architecture:
[User Request] → [Anycast DNS] → [Nearest Edge Location]
↓
[Edge Functions] → [Cache Check] → [Origin Shield] → [Origin Server]
↓
[Response Optimization] → [Security Filtering] → [User Response]
Key Features:
- 200+ Edge Locations: Global presence for low latency
- Anycast Network: Automatic routing to nearest edge
- Edge Functions: Serverless compute at the edge
- Smart Routing: Performance-based origin selection
AWS CloudFront Architecture
Multi-tier CDN Structure:
[Regional Edge Caches] ← [Edge Locations] ← [Users]
↓ ↓
[Origin Shield] ← [S3/ALB/Custom Origins]
Optimization Features:
- HTTP/2 and HTTP/3: Modern protocol support
- Compression: Automatic content compression
- Lambda@Edge: Serverless edge computing
- Real-time Logs: Detailed analytics and monitoring
Best Practices
1. CDN Configuration
- Optimize cache headers for different content types
- Use appropriate TTL values based on content update frequency
- Implement cache invalidation strategies for dynamic content
- Monitor cache hit ratios and optimize accordingly
2. Edge Computing
- Keep edge functions lightweight to minimize latency
- Implement proper error handling for edge function failures
- Use edge computing for personalization and A/B testing
- Monitor edge function performance and resource usage
3. Global Distribution
- Choose edge locations based on user geography
- Implement intelligent routing for optimal performance
- Use multiple CDN providers for redundancy
- Monitor global performance and adjust routing accordingly
4. Security
- Implement DDoS protection at the edge
- Use Web Application Firewalls (WAF) for security filtering
- Enable HTTPS everywhere with automatic certificate management
- Implement rate limiting to prevent abuse
Common Pitfalls
1. Over-Caching
- Caching dynamic content inappropriately
- Long TTL values for frequently changing content
- Not implementing cache invalidation properly
- Ignoring cache-control headers from origin
2. Poor Edge Function Design
- Heavy computation at the edge causing latency
- Stateful edge functions causing consistency issues
- Not handling edge function failures gracefully
- Excessive edge function chaining
3. Inadequate Monitoring
- Not monitoring cache performance across regions
- Missing edge function error tracking
- Inadequate origin server monitoring
- Not tracking user experience metrics
4. Cost Optimization
- Not optimizing data transfer costs between regions
- Over-provisioning edge locations without traffic justification
- Ignoring bandwidth costs for cache misses
- Not using cost-effective storage tiers for origin content
Next Chapter: Chapter 13: Reliability Patterns - Circuit breakers, retry patterns, and failover design