High-Volume Web Application Architecture

View High-Volume Web Application Architecture Fullscreen

This interactive visualization demonstrates a scalable web application architecture designed to handle high traffic volumes. The architecture shows how user requests flow through security layers, load balancing, application servers, and database infrastructure with synchronization capabilities.

Overview

This microsim illustrates a production-grade web application infrastructure that demonstrates key concepts in distributed systems, load balancing, and database architecture. The visualization shows how modern web applications achieve scalability by distributing load across multiple servers while maintaining data consistency through database synchronization.

The architecture represents a common pattern used by high-traffic websites and applications, where horizontal scaling (adding more servers) is preferred over vertical scaling (making individual servers more powerful).

Features

Node Types

• User (Amber, User Icon): End users accessing the application

• Properties: username, device, location, session_type

• Security (Red, Security Icon): Firewall providing perimeter security

• Properties: name, vendor, rules, throughput, status

• Network (Cyan, Router Icon): Load balancer distributing traffic

• Properties: name, type, algorithm, health_checks, SSL_termination

• Server (Gray, Server Icon): Web application servers (3 instances)

• Properties: hostname, IP, OS, memory, CPU, app

• Database (Orange, Database Icon): PostgreSQL database instances (3 instances)

• Properties: name, type, version, size, replication, connections

• Database (Purple, Database-Gear Icon): Synchronization server

• Properties: name, type, version, role, sync_interval, backup_schedule

Interactive Features

• Hover Tooltips: Hover over any node to see its type and properties in a tooltip
• Click for Details: Click on a node to display full details in the right sidebar
• Search: Use the search box to find nodes by name or property values
• Filter by Type: Toggle checkboxes to show or hide specific node types
• Select All/Unselect All: Bulk controls to quickly filter all node types
• Force-Directed Layout: Automatic node positioning using physics simulation
• Relationship Visualization: Colored edges show different types of connections (HTTPS, FORWARDS, ROUTES, QUERIES, SYNCS_TO)

Educational Insights

1. Horizontal Scaling Pattern: This architecture demonstrates horizontal scaling—adding more servers to handle increased load rather than upgrading individual machines. This approach provides better fault tolerance and allows for incremental capacity increases.

2. Load Balancing Strategies: The load balancer uses a round-robin algorithm to distribute incoming requests across three web servers. This ensures even distribution of load and prevents any single server from becoming a bottleneck.

3. Database Architecture Trade-offs: Each web server connects to its own database instance for low-latency access, but this creates data consistency challenges. The synchronization server maintains near real-time consistency across all database instances, introducing complexity but enabling better performance.

Data Flow

The request flow through the architecture follows this path:

1. User → Firewall: Users connect via HTTPS through the perimeter firewall
2. Firewall → Load Balancer: The firewall forwards authenticated traffic to the load balancer
3. Load Balancer → Web Servers: The load balancer distributes requests across three web servers using round-robin algorithm
4. Web Servers → Databases: Each web server queries its dedicated database instance
5. Databases → Sync Server: All databases synchronize with the master sync server to maintain data consistency

Architecture Considerations

Advantages

• Scalability: Can handle increased load by adding more web servers and databases
• Performance: Each web server has dedicated database access with low latency
• Fault Tolerance: Failure of one web server doesn't impact the others
• Security: Firewall provides perimeter protection and access control

Limitations

• Single Points of Failure: The firewall and load balancer are potential single points of failure
• Complexity: Database synchronization adds operational complexity
• Consistency Lag: There may be slight delays in data synchronization across databases
• Cost: Running multiple servers and databases increases infrastructure costs

Real-World Applications

This architecture pattern is commonly used in:

• E-commerce platforms handling thousands of concurrent users
• Social media applications with global user bases
• SaaS applications requiring high availability
• Content delivery systems with geographic distribution

Data Structure

The visualization uses a JSON data structure with nodes and edges:

{
  "nodes": [
    {
      "id": 1,
      "label": "Mobile User",
      "type": "User",
      "properties": {
        "username": "alice_mobile",
        "device": "iPhone 14",
        "location": "Remote",
        "session_type": "Mobile App"
      },
      "shape": "image",
      "image": "../../it-icons/user.svg",
      "color": "#f59e0b",
      "size": 25
    }
  ],
  "edges": [
    {
      "from": 1,
      "to": 3,
      "label": "HTTPS",
      "arrows": "to",
      "width": 2
    }
  ]
}

Implementation Notes

• Library: vis-network JavaScript library
• Layout: Force-directed using Barnes-Hut algorithm
• Icons: IT infrastructure icons from /docs/it-icons/ (MIT License)
• Data File: web-app-architecture-data.json

Next Steps

To extend or customize this microsim:

1. Add Redundancy: Include redundant firewalls and load balancers for high availability
2. Geographic Distribution: Show multiple data centers with cross-region replication
3. Caching Layer: Add Redis/Memcached nodes between web servers and databases
4. Monitoring: Include monitoring and logging infrastructure nodes
5. CDN Integration: Show content delivery network for static assets
6. Microservices: Break down the web server tier into specialized microservices