Load balancing is the process of distributing requests across multiple servers to improve performance, reliability, and scalability. Rather than a single server handling all requests, load balancers distribute traffic across multiple servers. This increases capacity, ensures no single server becomes a bottleneck, and enables graceful handling of server failures through failover.
Load Balancing Benefits
Load balancing provides multiple advantages:
Increased capacity - Multiple servers combined handle more traffic than a single server.
Reduced latency - Distributing requests across servers reduces wait times.
Improved reliability - If one server fails, requests route to remaining servers, maintaining availability.
Maintenance flexibility - Servers can be taken offline for updates or maintenance without service interruption.
Scalability - Adding servers increases capacity without changing client configuration.
Load Balancing Algorithms
Different algorithms distribute traffic differently:
Round-robin - Distributing requests sequentially across servers. Simple but may not account for server load.
Least connections - Routing requests to the server with fewest active connections. Accounts for server load.
Weighted round-robin - Distributing more requests to more powerful servers.
IP hash - Routing requests from the same client to the same server, useful for session affinity.
Least response time - Routing to the server with fastest response time.
Random - Random distribution. Simple but may not optimise load.
Custom algorithms - Writing custom logic for specific distribution patterns.
Choosing algorithms depends on application characteristics and requirements.
Load Balancer Types
Different load balancers operate at different network layers:
Layer 4 (Transport) - Balancing based on IP address, port, and TCP/UDP protocol. Simple, fast, suitable for simple distribution.
Layer 7 (Application) - Balancing based on HTTP headers, URLs, hostname, and application-specific logic. More sophisticated but higher overhead.
Global load balancing - Distributing across geographically distant data centres.
API gateway load balancing - Sophisticated load balancing and routing for API traffic.
Implementation Approaches
Load balancers can be implemented various ways:
Hardware load balancers - Dedicated hardware appliances. Expensive but high performance.
Software load balancers - Software running on servers (HAProxy, Nginx). Cost-effective and flexible.
Cloud load balancers - Managed services (AWS Elastic Load Balancing, Azure Load Balancer). Transparent scaling and management.
DNS load balancing - Using DNS to distribute traffic across servers. Simple but less sophisticated.
Most modern applications use cloud-managed load balancers for simplicity and automatic scaling.
Session Affinity
Some applications require routing requests from the same user to the same server:
Sticky sessions - Using cookies or IP addresses to ensure requests from a user go to the same server.
Session persistence - Ensuring in-memory session data persists across requests.
Distributed sessions - Storing sessions in databases or caches enabling any server to serve a user.
Stateless design - Designing applications without session affinity eliminates this complexity.
Health Checks
Load balancers monitor server health:
Active health checks - Periodically sending requests to verify servers are healthy.
Passive health checks - Monitoring responses to actual requests to detect failures.
Failure handling - Removing unhealthy servers from the pool automatically.
Recovery - Adding servers back when they become healthy.
Proper health checks ensure failed servers are removed quickly, maintaining availability.
Sticky Sessions vs. Stateless Design
Sticky sessions simplify some scenarios but create complexity:
Sticky session challenges - If server fails, user loses session. Hard to rebalance load. Prevents auto-scaling.
Stateless design benefits - Any server can handle any request, enabling transparent scaling and failover.
Modern approach - Store session state in databases or caches, enabling true stateless design.
Content-Based Routing
Sophisticated load balancing routes based on content:
Host-based routing - Different servers for different hostnames.
Path-based routing - Different servers for different URL paths.
Header-based routing - Different servers based on request headers.
Query-string routing - Different servers based on query parameters.
This enables complex routing whilst maintaining transparency to clients.
Geographic Load Balancing
For global applications:
Regional load balancing - Distributing across servers in a region.
Global load balancing - Directing users to nearest data centre.
Failover - Directing traffic to alternate regions if primary region fails.
Latency-based routing - Routing to lowest-latency data centre.
Geographic load balancing enables global service with local performance.
Load Balancing at PixelForce
PixelForce uses AWS Elastic Load Balancing for applications requiring distribution across multiple servers. Whether distributing web traffic or API requests, load balancing is fundamental to building scalable, reliable systems.
SSL/TLS Termination
Load balancers often handle encryption:
Termination - Load balancers accept encrypted client connections, decrypt, and forward plaintext to backend servers.
Benefits - Centralises encryption handling, offloads CPU from application servers.
Trade-offs - Increases load balancer responsibility.
Monitoring Load Balancers
Proper monitoring ensures load balancing works:
Traffic distribution - Verifying traffic distributes properly across servers.
Server health - Monitoring that health checks work and failed servers are removed.
Performance metrics - Response times, error rates, and throughput.
Load patterns - Understanding traffic patterns to optimise distribution.
Conclusion
Load balancing distributes requests across multiple servers improving performance, reliability, and scalability. By distributing traffic, ensuring failover, and monitoring health, load balancers enable building systems that scale transparently and remain available despite individual server failures.