Table of Contents
CDN Issues, Incidents, and Mitigation Strategies #
Cache Consistency Issues #
| Issue | STAR Incident Example | Contributing Patterns | Canonical Solution Pattern | Real-world Incidents |
|---|---|---|---|---|
| Cache invalidation failures | S: E-commerce platform updates product pricing T: Ensure all users see current prices A: Stale prices remained cached at edge locations despite origin updates R: Customers complained about price mismatches at checkout | - Missing cache invalidation hooks - Improper cache key design - Unclear content dependencies - Manual purge processes - Content versioning gaps | Cache Versioning Pattern with automated invalidation on content updates | - 2019 Shopify pricing inconsistencies - Amazon product availability mismatches - Cloudflare cache purge delays during site updates |
| Inconsistent TTL policies | S: News website delivering breaking news T: Ensure timely content updates across global audience A: Inconsistent TTL settings caused different users to see different content versions R: Misinformation spread as corrections weren’t seen by all users | - Ad-hoc TTL assignments - Missing content classification - Environment-specific settings - Developer discretion for TTLs - Unaudited cache headers | Content-aware TTL Pattern with content type classification system | - CNN stale news delivery during major events - BBC inconsistent coverage during elections - Akamai customer complaints about TTL inconsistencies |
| Cache stampede | S: Popular streaming platform during major release T: Handle spike in viewing of new content A: Simultaneous cache expiry caused flood of origin requests R: Origin servers overloaded, service degraded for all users | - Fixed TTL expirations - Cache-aside implementation - Missing request coalescing - Single-tier caching - High cache churn | Staggered Expiration Pattern with request coalescing and background refresh | - Netflix cache stampede during popular show release - Shopify Black Friday traffic spikes - Reddit “hug of death” incidents |
| Cold cache performance | S: Gaming platform after maintenance window T: Resume normal service after planned maintenance A: Empty caches after restart caused all requests to hit origin R: Post-maintenance performance degradation and poor user experience | - Cache clearing during updates - Missing cache warming - Binary cache state (full/empty) - Origin dependency during restarts - Restart-prone edge nodes | Cache Warming Pattern with progressive deployment and intelligent preloading | - Blizzard post-maintenance login queues - Fastly global restart performance impact - Epic Games store slowdowns after updates |
Performance Issues #
| Issue | STAR Incident Example | Contributing Patterns | Canonical Solution Pattern | Real-world Incidents |
|---|---|---|---|---|
| Origin shield failures | S: Video streaming service during sports event T: Protect origin servers from traffic spikes A: Misconfigured shield allowed traffic to bypass to origin R: Origin servers crashed, causing streaming outage | - Improper shield configuration - Direct origin access paths - Missing request aggregation - Shield capacity limitations - Origin-direct fallbacks | Layered Caching Pattern with regional shield hierarchies | - 2020 Cloudflare origin shield bypass incident - Akamai shield routing issues - AWS CloudFront origin overloads |
| Edge node congestion | S: Social media platform serving viral content T: Maintain performance under sudden popularity spikes A: Specific edge locations became overloaded with requests R: Regional performance degradation and timeout errors | - Fixed capacity allocation - Regional traffic imbalances - Ineffective load balancing - Missing traffic steering - Rigid edge deployment | Dynamic Edge Selection Pattern with real-time traffic distribution | - Fastly edge node congestion incidents - Cloudflare regional hotspots during viral events - Akamai capacity planning challenges |
| SSL/TLS overhead | S: Financial services website with strict security T: Maintain high security while preserving performance A: Full TLS handshakes for all requests created processing bottlenecks R: Page load times increased, impacting user experience | - Session cache misses - Missing session resumption - Frequent key rotation - Strict cipher requirements - Edge compute limitations | TLS Session Reuse Pattern with optimized cipher configurations | - Cloudflare TLS 1.3 deployment challenges - Let’s Encrypt certificate deployment impact - Financial sector performance/security balancing issues |
| Content optimization failures | S: Mobile app content delivery T: Optimize delivery for various network conditions A: Image optimization failed to adapt to network quality R: Mobile users on poor connections experienced timeouts | - Static content optimization - Missing client context - One-size-fits-all settings - Aggressive compression - Origin-only transformations | Adaptive Optimization Pattern with client-aware content transformation | - Google AMP performance variability - Facebook mobile content delivery challenges - Image-heavy site optimization failures |
Security Issues #
| Issue | STAR Incident Example | Contributing Patterns | Canonical Solution Pattern | Real-world Incidents |
|---|---|---|---|---|
| Cache poisoning | S: Financial services website T: Serve secure, trusted content to users A: Malicious actors injected bad content into cache through header manipulation R: Fraudulent content served from trusted domain | - Missing input validation - Cache key manipulation - HTTP header injection - Unvalidated parameters in cache key - Request-controlled caching | Validated Cache Key Pattern with strict input sanitization | - 2018-2019 cache poisoning vulnerabilities (CVE-2018-1000136) - Web Cache Deception attacks on major sites - eBay cache poisoning incidents |
| TLS configuration weaknesses | S: Healthcare patient portal T: Secure patient data in transit A: Outdated TLS configuration allowed downgrade attacks R: Potential regulatory violations and data exposure risks | - Legacy protocol support - Weak cipher suites - Missing security headers - Outdated TLS versions - Inconsistent edge configurations | TLS Hardening Pattern with automated security posture verification | - POODLE and BEAST vulnerabilities affecting CDNs - Heartbleed exposure in CDN edge nodes - HIPAA compliance failures due to TLS misconfigurations |
| DDoS protection bypass | S: Online banking platform T: Maintain availability during attack A: Attackers identified CDN bypasses to reach origin directly R: Successful denial of service despite CDN protection | - Origin IP exposure - DNS configuration leaks - Inconsistent access controls - Direct origin connectivity - Incomplete request filtering | Origin Cloaking Pattern with strict access control enforcement | - GitHub 1.35 Tbps attack (2018) - Dyn DNS attack affecting CDN routing - Imperva/Cloudflare protection bypass incidents |
| Web application firewall evasion | S: E-commerce payment processing T: Protect web forms from injection attacks A: Attackers bypassed WAF rules using encoding variations R: SQL injection succeeded despite WAF protection | - Signature-based detection - Limited encoding understanding - Rule-based approach - Missing contextual analysis - Outdated protection patterns | Layered Defense Pattern with multiple inspection points and anomaly detection | - Bypass of ModSecurity rules on CDNs - Cloudflare WAF bypass techniques demonstrated at security conferences - Akamai WAF evasion using edge-case encodings |
Operational Issues #
| Issue | STAR Incident Example | Contributing Patterns | Canonical Solution Pattern | Real-world Incidents |
|---|---|---|---|---|
| Configuration propagation delays | S: Global banking website security update T: Deploy critical security patch to all edge locations A: Configuration changes took hours to reach all edge nodes R: Extended vulnerability window during gradual rollout | - Global edge distribution - Asynchronous config updates - Missing propagation tracking - Edge node autonomy - Sequential update processes | Atomic Configuration Pattern with staged propagation and verification | - Fastly configuration propagation incident (2021) - Cloudflare edge configuration inconsistencies - Akamai property deployment delays |
| Edge node failures | S: Video streaming platform during major premiere T: Deliver content to millions of concurrent viewers A: Several edge locations experienced hardware failures R: Regional service degradation and buffering issues | - Insufficient redundancy - Regional capacity planning - Failure domain isolation - Retry storms during failures - Connection pooling limits | N+K Edge Redundancy Pattern with automated failover and client rerouting | - Level 3 (CenturyLink) edge router failures - Fastly point-of-presence outages - Netflix regional availability challenges |
| Origin health detection failures | S: Corporate website serving critical information T: Automatically detect and route around origin issues A: Health checks passed despite origin application errors R: CDN continued routing to failed origin | - Simplistic health checks - TCP/ping-only verification - Missing application-level checks - Binary health status - Infrequent check intervals | Synthetic Transaction Pattern with application-aware health verification | - GitHub availability incident (2018) - Synthetic monitoring failures reported by Catchpoint - Content errors despite “healthy” origin reports |
| Cost management challenges | S: Media company serving large video files T: Optimize CDN costs while maintaining performance A: Improper cache settings caused excessive origin fetches and transfer costs R: 300% overspend on monthly CDN budget | - Aggressive TTL settings - Cacheability hesitancy - Missing cost monitoring - One-size-fits-all policies - Origin-intensive architectures | Cost-Aware Caching Pattern with economic-based optimization and monitoring | - Video streaming companies reporting major CDN cost overruns - Mobile app background requests creating unexpected traffic - Large file delivery cost optimization challenges |
Global Distribution Issues #
| Issue | STAR Incident Example | Contributing Patterns | Canonical Solution Pattern | Real-world Incidents |
|---|---|---|---|---|
| Inconsistent global performance | S: Global SaaS application T: Deliver consistent user experience worldwide A: Dramatic performance differences between regions R: Customer complaints about regional discrimination | - Single-region origin - Inconsistent edge capabilities - Uneven global distribution - Network peering limitations - Regional capacity disparities | Follow-the-Sun Deployment Pattern with regional origin redundancy | - Microsoft Teams regional performance disparities - Google Workspace latency variations by geography - SaaS regional experience inconsistencies |
| Geo-routing inaccuracies | S: Content streaming service with licensing restrictions T: Enforce regional content licensing rules A: IP-based geolocation routed users to wrong regional content R: Licensing violations and customer complaints about missing content | - IP-only geolocation - Outdated IP databases - VPN/proxy detection gaps - Missing multi-signal verification - Binary geo decisions | Multi-factor Geolocation Pattern with layered verification techniques | - Netflix geolocation errors affecting content availability - BBC iPlayer international access issues - Sports streaming regional blackout failures |
| DNS-based routing failures | S: Global retail platform T: Route users to optimal CDN edge nodes A: DNS resolver issues caused suboptimal routing decisions R: Users directed to distant edge locations, increasing latency | - ISP DNS resolver limitations - DNS caching behaviors - EDNS client subnet issues - Anycast limitations - Missing client intelligence | Client-aware Routing Pattern with application-level routing decisions | - ISP DNS resolver issues affecting CDN performance - DNS-based load balancing failures during provider outages - Public resolver performance impacts on CDN effectiveness |
| Multi-CDN orchestration failures | S: Video conferencing service using multiple CDNs T: Optimize performance and reliability through CDN diversity A: CDN switching logic caused oscillations between providers R: Degraded user experience due to connection resets and cache misses | - Simplistic CDN selection - Missing state in switching logic - Aggressive failover thresholds - Inconsistent CDN capabilities - Cost-only optimization | Stable CDN Selection Pattern with hysteresis and performance-aware routing | - Major sporting events streaming failures - Video platform multi-CDN implementation challenges - Inconsistent multi-CDN performance during peak events |
Content Management Issues #
| Issue | STAR Incident Example | Contributing Patterns | Canonical Solution Pattern | Real-world Incidents |
|---|---|---|---|---|
| Dynamic content caching challenges | S: News website with personalized content T: Cache as much content as possible while preserving personalization A: Over-conservative caching approach limited CDN benefits R: Origin servers overloaded during traffic spikes | - Binary caching approach - All-or-nothing personalization - Missing edge computation - Cookie-dependent content - Fear of stale content | Edge Assembly Pattern with fragment caching and edge composition | - News site performance challenges during elections - Social media feed delivery bottlenecks - E-commerce personalization performance tradeoffs |
| Large file optimization issues | S: Software distribution platform T: Efficiently deliver multi-GB installation files A: Monolithic file delivery caused frequent download restarts R: Poor completion rates and user frustration | - Single-chunk file delivery - TCP session limitations - Network instability handling - Progressive delivery gaps - Range request inefficiencies | Chunked Transfer Pattern with resumable downloads and parallel transfers | - Microsoft Windows update delivery challenges - Game distribution platform download reliability problems - Video asset delivery optimization failures |
| Origin synchronization problems | S: Content publishing platform with multiple origins T: Ensure consistent content across all CDN source origins A: Content updates applied inconsistently across origins R: Users saw different content depending on which origin served their edge location | - Multi-master content architecture - Asynchronous origin replication - Missing consistency enforcement - Independent origin scaling - Eventual consistency models | Origin Consistency Pattern with content versioning and atomic updates | - Multi-region CMS deployments causing inconsistency - Cloud storage replication delays affecting CDN content - Database-backed origins showing inconsistent content |
| Asset optimization failures | S: Mobile-focused web application T: Optimize images and assets for various devices A: On-the-fly image optimization created processing bottlenecks R: High latency for image-heavy pages, particularly on mobile | - Runtime transformation - Missing pre-optimization - Device detection limitations - Quality vs. size tradeoffs - Processor-intensive operations | Precomputed Variant Pattern with device-specific asset preparation | - Image-heavy site optimization challenges - Mobile-first deployments with desktop performance impacts - E-commerce product image delivery optimization failures |
API and Dynamic Content Issues #
| Issue | STAR Incident Example | Contributing Patterns | Canonical Solution Pattern | Real-world Incidents |
|---|---|---|---|---|
| API caching inconsistencies | S: Public API service with rate limits T: Leverage CDN to reduce origin load for repeatable requests A: Improper cache key design caused data leakage between clients R: Users received other clients’ data, creating security incident | - Authentication-ignorant caching - Insufficient cache key design - Missing Vary headers - Request-specific response caching - Authorization bypass | Tokenized Cache Key Pattern with authentication-aware caching | - API gateway cache leakage incidents - OAuth token exposure through improper caching - Mobile app receiving mixed-client data |
| Websocket and long-polling limitations | S: Real-time collaborative application T: Maintain persistent connections for thousands of users A: CDN terminated connections prematurely R: Frequent disconnections and data synchronization failures | - Connection timeout limits - Load balancer behaviors - Missing protocol support - Idle connection management - Stateless edge design | Persistent Connection Pattern with connection-aware routing and management | - Slack websocket disconnection issues - Collaborative document editing failure reports - Game server connection stability challenges |
| GraphQL CDN integration challenges | S: Mobile app using GraphQL for data fetching T: Optimize CDN usage for GraphQL queries A: POST-based queries bypassed CDN caching entirely R: Origin servers overwhelmed by repetitive GraphQL queries | - POST request caching limitations - Query complexity variations - Missing query normalization - Operation-specific caching - Highly customized requests | Automatic Persisted Queries Pattern with query hashing and GET transformation | - Apollo GraphQL caching implementation challenges - Mobile app performance degradation with GraphQL - API gateway customization for GraphQL CDN optimization |
| Microservice composition challenges | S: E-commerce website built on microservices T: Deliver fast page loads composed from multiple services A: Edge timeouts waiting for slow microservices R: Poor user experience with partial page loads | - Request waterfalls - All-or-nothing page assembly - Origin-based composition - Tight coupling to backend services - Synchronous composition | Edge Composition Pattern with progressive rendering and service isolation | - Retail site performance challenges during sales events - Travel booking site timeout issues - Service interdependency causing cascading failures |
Edge Computing Issues #
| Issue | STAR Incident Example | Contributing Patterns | Canonical Solution Pattern | Real-world Incidents |
|---|---|---|---|---|
| Edge function performance variability | S: E-commerce site using edge functions for personalization T: Deliver consistent sub-100ms personalized responses A: Edge function performance varied dramatically by region and load R: Inconsistent user experience and timeout errors | - Resource-intensive edge code - Cold start penalties - Regional capacity variations - Missing performance monitoring - Unbounded computation | Resource-Aware Edge Pattern with performance budgets and circuit breakers | - Cloudflare Workers performance variability reports - Lambda@Edge cold start complaints - Fastly Compute@Edge resource exhaustion incidents |
| Edge state management challenges | S: Shopping cart implemented at the edge T: Maintain consistent cart state across user sessions A: Distributed state inconsistencies caused cart items to disappear R: Lost sales and customer service complaints | - Edge node state isolation - Missing state synchronization - Request distribution changes - Sticky session failures - In-memory state limitations | Distributed State Pattern with central source of truth and local caching | - Shopping cart implementation challenges on CDNs - Session state consistency issues reported with edge functions - Multi-region deployment state synchronization problems |
| Edge deployment failures | S: Financial services application T: Deploy new security rules to edge functions A: Partial deployment created inconsistent rule enforcement R: Security policy violations in some regions | - Missing deployment atomicity - Independent edge deployments - Versioning challenges - Rollback limitations - Change verification gaps | Blue/Green Edge Deployment Pattern with atomic activation and verification | - Partial WAF rule deployment incidents - Edge function version inconsistencies - Authentication rule deployment failures |
| Edge-to-origin communication failures | S: Global retail application T: Connect edge functions to internal services A: Edge-to-origin connectivity issues created regional failures R: Transactions failed for users in specific regions | - Direct backend dependencies - Missing circuit breakers - Timeout misalignment - Network path limitations - Authentication challenges | Edge Resiliency Pattern with circuit breakers and graceful degradation | - Edge function to backend connectivity issues - Origin connection pool exhaustion during traffic spikes - Authentication token propagation failures |
Monitoring and Observability Issues #
| Issue | STAR Incident Example | Contributing Patterns | Canonical Solution Pattern | Real-world Incidents |
|---|---|---|---|---|
| Limited edge visibility | S: Media streaming platform experiencing buffering T: Identify root cause of playback issues A: Limited metrics from edge nodes obscured the problem source R: Extended troubleshooting time, prolonged user impact | - Aggregated-only metrics - Missing edge logging - Limited dimensionality - Delayed metric availability - Insufficient granularity | Edge Telemetry Pattern with granular, real-time observability | - Video streaming quality troubleshooting challenges - CDN performance root cause analysis difficulties - Regional performance variation isolation problems |
| Real user experience blind spots | S: Single page application served via CDN T: Understand actual user performance experience A: Server-side metrics showed good performance while users experienced problems R: Missed client-side performance issues affecting conversion | - Server-centric monitoring - Missing real user metrics - Last-mile blind spots - Synthetic-only testing - Limited client telemetry | RUM Integration Pattern with client-side performance correlation | - JavaScript framework rendering performance issues - Mobile client experience divergence from synthetic tests - Third-party script impact invisibility |
| Cache efficiency blind spots | S: Content site with unpredictable traffic patterns T: Optimize cache hit rates to reduce origin load A: Missing visibility into cache key distribution led to poor hit rates R: Excess origin traffic and higher costs despite CDN usage | - Binary hit/miss metrics - Missing cache key analytics - Aggregate-only reporting - No content-specific insights - Origin-only monitoring | Cache Analytics Pattern with detailed key distribution and efficiency metrics | - High CDN costs despite ostensibly high hit rates - Unexpected origin load during promotions - Cacheable content mistakenly bypassing cache |
| Error attribution challenges | S: E-commerce checkout flow T: Quickly identify source of user-facing errors A: Unclear whether errors originated at CDN, origin, or client R: Extended mean-time-to-resolution for critical issues | - Ambiguous error reporting - Missing request tracing - Layer-specific monitoring - Insufficient error context - Siloed observability | Distributed Tracing Pattern with cross-layer correlation and attribution | - 500 error source attribution difficulties - Multi-CDN error troubleshooting complexity - Client-reported issues with unclear source |
Compliance and Regulatory Issues #
| Issue | STAR Incident Example | Contributing Patterns | Canonical Solution Pattern | Real-world Incidents |
|---|---|---|---|---|
| Data sovereignty violations | S: Healthcare platform serving international patients T: Comply with regional data protection laws A: Patient data cached in non-compliant regions R: Regulatory violation and potential fines | - Global CDN distribution - Missing geo-fencing - Default caching behaviors - Unclear data classification - Insufficient controls | Geo-Aware Delivery Pattern with regulatory boundary enforcement | - GDPR compliance challenges with global CDNs - Healthcare data localization requirement violations - Financial data cross-border caching issues |
| PCI compliance gaps | S: Payment processing on e-commerce site T: Maintain PCI DSS compliance for payment flows A: PII/payment data inadvertently cached at edge R: Compliance audit failure and remediation requirements | - Improper cache-control headers - Missing sensitive data detection - Form data in URLs - Default-cacheable settings - Insufficient security reviews | PCI Segmentation Pattern with strict no-store policies for sensitive flows | - Credit card information exposure in cached pages - PCI audit failures related to CDN configurations - Payment form caching violations |
| Log and analytics data protection | S: Marketing website with user tracking T: Collect analytics while respecting privacy regulations A: Edge logs contained PII despite anonymization attempts R: Data privacy violation when logs were processed | - Excessive logging - Client IP retention - URL parameter logging - Missing PII scrubbing - Identifier correlation | Privacy-by-Design Logging Pattern with automated PII detection and protection | - GDPR violations from CDN logging practices - Cookie and tracking consent bypasses - IP address retention policy violations |
| Accessibility compliance challenges | S: Government website serving diverse users T: Maintain WCAG compliance for all users A: CDN-based optimizations broke screen reader compatibility R: Accessibility complaints and compliance violations | - Image optimization side effects - Dynamic content modifications - Script injection interference - Markup transformation - Testing gaps | Accessible Transformation Pattern with accessibility-aware optimizations | - Government site section 508 compliance failures - Screen reader compatibility issues after CDN adoption - Mobile optimization breaking accessibility features |
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