AWSCloud InfrastructureCloud Services

High-Scale E-commerce Infrastructure Architecture

Espina Cloud

January 25, 2026

4 Min Read

41 Views

0 Comments

Europe & North America – High Availability, High Traffic

Hello everyone. We would like to share a real use case we worked on for a company based in the United States. The project involved a large-scale e-commerce platform handling approximately 1.5 million visits per day, with an average order value of around $100 per customer. At this scale, performance, reliability, and data protection are not optional, they are business-critical.

Given these requirements, the company needed an infrastructure capable of high availability, very low latency, and robust data backup mechanisms to prevent any risk of data loss or service disruption. Our role was to design and build an infrastructure that could meet these demands while remaining scalable and resilient under heavy traffic loads.

In this article, we will present a high-level overview of the infrastructure and system architecture we designed and implemented, explaining the key decisions and principles that guided the solution.

1. Key Assumptions (Foundation for the Design)

To correctly design the infrastructure, the following assumptions are made based on your use case:

• ~1.5 million daily visitors
  
• Peak traffic concentration of 5–10% of daily users
  
  → 75,000–150,000 concurrent users
  
• Average ticket value: USD 100
  
• Business criticality: Revenue loss per minute is significant
  
• Geographic focus: Europe and North America
  
• Requirements:
  
  • Very high availability (≥ 99.99%)
    
  • Low latency (< 200 ms perceived)
    
  • Ability to absorb traffic spikes without manual intervention
    
  • No single point of failure
    
  • Seamless regional failover
    
  • Strong security posture
    

2. Core Design Principles

1. Everything must be horizontally scalable
   
2. No critical component may exist in a single region
   
3. The system must assume failures will happen
   
4. Cache everything that is not strictly transactional
   
5. Stateless application services
   
6. Traffic must be absorbed as far from the origin as possible
   
7. Regional isolation with global coordination
   

3. Global Traffic Management Layer

DNS (Global Entry Point)

Responsibilities:

• Route users to the closest healthy region
  
• Automatically remove unhealthy regions
  
• Enable active-active regional traffic
  

4. Content Delivery Network (CDN)

The CDN is the single most important component for bandwidth, performance, and stability.

Functions:

• Cache static assets (images, JS, CSS)
  
• Cache HTML and product pages where possible
  
• Absorb traffic spikes
  
• Terminate TLS close to users
  
• Provide DDoS and bot mitigation
  
• Act as a regional traffic shield
  

Impact:

• 80–95% of requests never reach the backend
  
• Massive reduction in bandwidth costs
  
• Latency drops below 50 ms for cached content
  
• Backend capacity becomes predictable
  

Without a CDN, this scale is not economically or technically viable.

5. Edge Security (Before Backend)

At the CDN / edge layer:

• Web Application Firewall (WAF)
  
• Rate limiting
  
• Bot detection
  
• Layer 7 DDoS protection
  

This ensures only legitimate, clean traffic reaches the core infrastructure.

6. Regional Load Balancing

Each region (EU and NA) has its own Layer 7 load balancers.

Responsibilities:

• Distribute traffic across application instances
  
• Perform continuous health checks
  
• Support zero-downtime deployments
  
• Terminate HTTPS if needed
  

7. Application Layer

Architecture Style

• Microservices or a well-modularized monolith
  
• Stateless services
  
• Containerized workloads
  

Orchestration

• Kubernetes or equivalent
  
• Auto-scaling based on:
  
  • CPU usage
    
  • Request rate
    
  • Latency thresholds
    

Typical services:

• Frontend / BFF
  
• Authentication
  
• Product catalog
  
• Checkout
  
• Payments orchestration
  
• Inventory
  
• User profiles
  

Each service scales independently, preventing cascading failures.

8. Distributed Caching Layer

A distributed in-memory cache (e.g., Redis cluster) is deployed per region.

Cached data:

• Sessions
  
• Product catalog
  
• Pricing
  
• Search results
  
• Authentication tokens
  
• Frequently accessed metadata
  

Benefits:

• Up to 90% reduction in database load
  
• Faster response times
  
• Increased resilience during database pressure
  

Caching is treated as a first-class architectural component, not an optimization.

9. Database Architecture (Most Critical Layer)

Design Pattern: Multi-Region, Read-Optimized

Writes:

• Local to the region
  
• Strong consistency within region
  

Reads:

• Served from local replicas
  
• No cross-region reads in hot paths
  

Replication:

• Asynchronous cross-region replication
  
• Automated failover
  
• Continuous backups
  

Technology Options:

• SQL: Aurora Global Database, Google Spanner
  
• NoSQL: DynamoDB Global Tables, Cassandra
  

Key rules:

• No single database instance
  
• No global write bottleneck
  
• Failover tested regularly
  

10. Checkout and Payments (Revenue-Critical Path)

Payments are never processed internally.

Flow characteristics:

• External payment providers
  
• Short timeouts
  
• Circuit breakers
  
• Controlled retries
  
• Asynchronous confirmation via events/queues
  

Event-driven design:

• Order creation
  
• Inventory reservation
  
• Payment confirmation
  
• Fulfillment triggers
  

This ensures checkout remains available even when downstream systems degrade.

11. Messaging and Asynchronous Processing

Event queues (Kafka, SQS, Pub/Sub) are used to:

• Decouple services
  
• Smooth traffic spikes
  
• Avoid synchronous dependencies
  
• Improve fault tolerance
  

Critical operations never rely on long synchronous chains.

12. Observability and Operations

Monitoring:

• Latency
  
• Error rates
  
• Throughput
  
• Saturation
  

Logging:

• Centralized
  
• Structured
  
• Searchable
  

Tracing:

• End-to-end request visibility
  

Alerting:

• SLO-based
  
• Proactive, not reactive
  

The goal is to detect problems before customers do.13. Bandwidth Considerations

With proper CDN usage:

• Backend sees only 5–20% of total traffic
  
• CDN handles traffic at terabit scale
  
• Backend bandwidth requirements become manageable
  

Without a CDN:

• Extreme bandwidth costs
  
• High failure probability
  
• Poor user experience
  

14. High Availability Strategy

• Multi-AZ per region
  
• Multi-region active-active
  
• Automatic failover
  
• Rolling deployments
  
• No single point of failure
  
• Regular disaster recovery testing
  

Target:

• 99.99% uptime
  
• < 200 ms average response time
  

15. Common Failure Patterns to Avoid

• Single region deployments
  
• Centralized databases
  
• Insufficient caching
  
• Manual scaling
  
• Unprotected edge traffic
  
• Untested failover scenarios
  

With this planning and high-level architecture in place, it is possible to implement the infrastructure using any cloud provider required, depending on the final client’s needs. This may include Amazon Web Services, Microsoft Azure, or Google Cloud Platform. In the next post, I will break down each of these components in greater technical detail to provide a clearer and more in-depth understanding of the solution.