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Load Balancing & Traffic Management

The load balancing utilities provide intelligent traffic distribution, failover handling, and performance optimization for edge environments. These utilities help distribute requests across multiple backend services, handle failures gracefully, and optimize response times.

Features

  • Multiple Algorithms: Round-robin, least connections, weighted, IP hash
  • Health Monitoring: Automatic backend health checks and failover
  • Load Metrics: Real-time load monitoring and adaptive balancing
  • Geographic Routing: Location-based traffic routing
  • Performance Optimization: Response time-based load balancing
  • Session Affinity: Sticky sessions and connection persistence
  • Auto-scaling: Dynamic backend pool management
  • Circuit Breaker: Fault tolerance and graceful degradation

Quick Start

Load Balancing Algorithms

Round Robin

Distributes requests sequentially across all healthy backends.

Weighted Round Robin

Distributes requests based on backend weights.

Least Connections

Routes to the backend with the fewest active connections.

IP Hash

Routes requests from the same IP to the same backend (session affinity).

Least Response Time

Routes to the backend with the fastest recent response times.

Random

Randomly selects a healthy backend.

BackendPool

Manages the collection of backend servers with health status and metadata.

Constructor Options

Backend Configuration

Dynamic Backend Management

Health Monitoring

Automatic health checks and failure detection for backend servers.

Health Check Configuration

Custom Health Checks

Health Status Monitoring

Circuit Breaker Pattern

Prevents cascading failures by temporarily stopping requests to failing backends.

Circuit Breaker Configuration

Circuit Breaker States

Session Affinity

Maintains session persistence by routing related requests to the same backend.

Sticky Sessions

Session Management

Geographic Load Balancing

Routes traffic based on geographic location for improved performance.

Geo-based Routing

Performance Optimization

Connection Pooling

Request Queuing

Load Shedding

Advanced Examples

Multi-region Load Balancing

API Gateway with Load Balancing

Auto-scaling Integration

Blue-Green Deployment

Middleware Integration

Load Balancing Middleware

Performance Considerations

Connection Optimization

Caching Backend Selection

Async Backend Selection

Platform-Specific Notes

Cloudflare Workers

  • Use Durable Objects for session affinity
  • Leverage Cloudflare’s global network for geo-routing
  • Compatible with Cloudflare Load Balancing

Vercel Edge Functions

  • Use Vercel’s edge network for geographic routing
  • Compatible with Vercel KV for backend state
  • Support for Vercel’s deployment regions

Deno Deploy

  • Native HTTP/2 support for connection pooling
  • Compatible with Deno KV for distributed state
  • Support for Web APIs for load balancing

Best Practices

Backend Configuration

Health Check Best Practices

Monitoring and Alerting

Testing

Run load balancing tests with:

API Reference

LoadBalancer Methods

  • selectBackend(request, options) - Select backend for request
  • getMetrics() - Get load balancer metrics
  • getHealthStatus() - Get health status of backends
  • addBackend(backend) - Add backend dynamically
  • removeBackend(backendId) - Remove backend
  • updateBackend(backendId, config) - Update backend configuration

BackendPool Methods

  • addBackend(backend) - Add backend to pool
  • removeBackend(backendId) - Remove backend from pool
  • updateBackend(backendId, config) - Update backend configuration
  • getBackend(backendId) - Get backend by ID
  • getHealthyBackends() - Get all healthy backends
  • getAllBackends() - Get all backends

HealthChecker Methods

  • checkBackend(backend) - Check specific backend health
  • checkAllBackends() - Check all backends health
  • getHealthStatus() - Get health status of all backends
  • on(event, callback) - Listen for health events

Contributing

When contributing to load balancing utilities:
  1. Maintain backward compatibility
  2. Add comprehensive tests for new algorithms
  3. Update documentation for new features
  4. Consider performance impact of changes
  5. Test across all supported platforms

License

MIT