Load Balancing Patterns
Distribute traffic across infrastructure using the appropriate load balancing approach, from simple round-robin to global multi-region failover.
When to Use This Skill
Use load-balancing-patterns when:
- Distributing traffic across multiple application servers
- Implementing high availability and failover
- Routing traffic based on URLs, headers, or geographic location
- Managing session persistence across stateless backends
- Deploying applications to Kubernetes clusters
- Configuring global traffic management across regions
- Implementing zero-downtime deployments (blue-green, canary)
- Selecting between cloud-managed and self-managed load balancers
Core Load Balancing Concepts
Layer 4 vs Layer 7
Layer 4 (L4) - Transport Layer:
- Routes based on IP address and port (TCP/UDP packets)
- No application data inspection, lower latency, higher throughput
- Protocol agnostic, preserves client IP addresses
- Use for: Database connections, video streaming, gaming, financial transactions, non-HTTP protocols
Layer 7 (L7) - Application Layer:
- Routes based on HTTP URLs, headers, cookies, request body
- Full application data visibility, SSL/TLS termination, caching, WAF integration
- Content-based routing capabilities
- Use for: Web applications, REST APIs, microservices, GraphQL endpoints, complex routing logic
For detailed comparison including performance benchmarks and hybrid approaches, see references/l4-vs-l7-comparison.md.
Load Balancing Algorithms
| Algorithm | Distribution Method | Use Case |
|---|---|---|
| Round Robin | Sequential | Stateless, similar servers |
| Weighted Round Robin | Capacity-based | Different server specs |
| Least Connections | Fewest active connections | Long-lived connections |
| Least Response Time | Fastest server | Performance-sensitive |
| IP Hash | Client IP-based | Session persistence |
| Resource-Based | CPU/memory metrics | Varying workloads |
Health Check Types
Shallow (Liveness): Is the process alive?
- Endpoint:
/health/liveor/live - Returns: 200 if process running
- Use for: Process monitoring, container health
Deep (Readiness): Can the service handle requests?
- Endpoint:
/health/readyor/ready - Validates: Database, cache, external API connectivity
- Use for: Load balancer routing decisions
Health Check Hysteresis: Different thresholds for marking up vs down to prevent flapping
- Example: 3 failures to mark down, 2 successes to mark up
For complete health check implementation patterns, see references/health-check-strategies.md.
Cloud Load Balancers
AWS Load Balancing
Application Load Balancer (ALB) - Layer 7:
- Use for: HTTP/HTTPS applications, microservices, WebSocket
- Features: Path/host/header routing, AWS WAF integration, Lambda targets
- Choose when: Content-based routing needed
Network Load Balancer (NLB) - Layer 4:
- Use for: Ultra-low latency (<1ms), TCP/UDP, static IPs, millions RPS
- Features: Preserves source IP, TLS termination
- Choose when: Non-HTTP protocols, performance critical
Global Accelerator - Layer 4 Global:
- Use for: Multi-region applications, global users, DDoS protection
- Features: Anycast IPs, automatic regional failover
GCP Load Balancing
Application LB (L7): Global HTTPS LB, Cloud CDN integration, Cloud Armor (WAF/DDoS) Network LB (L4): Regional TCP/UDP, pass-through balancing, session affinity Cloud Load Balancing: Single anycast IP, global distribution, backend buckets
Azure Load Balancing
Application Gateway (L7): WAF integration, URL-based routing, SSL termination, autoscaling Load Balancer (L4): Basic and Standard SKUs, health probes, HA ports Traffic Manager (Global): DNS-based routing (priority, weighted, performance, geographic)
For complete cloud provider configurations and Terraform examples, see references/cloud-load-balancers.md.
Self-Managed Load Balancers
NGINX
Best for: General-purpose HTTP/HTTPS load balancing, web application stacks
Capabilities:
- HTTP reverse proxy with multiple algorithms
- TCP/UDP stream load balancing
- SSL/TLS termination
- Passive health checks (open source), active health checks (NGINX Plus)
- Cookie-based sticky sessions (NGINX Plus)
Basic configuration:
upstream backend {
least_conn;
server backend1.example.com:8080 weight=3;
server backend2.example.com:8080 weight=2;
keepalive 32;
}
server {
listen 80;
location / {
proxy_pass http://backend;
proxy_set_header Host $host;
proxy_set_header X-Real-IP $remote_addr;
}
}
For complete NGINX patterns and advanced configurations, see references/nginx-patterns.md.
HAProxy
Best for: Maximum performance, database load balancing, resource efficiency
Capabilities:
- Highest raw throughput, lowest memory footprint
- 10+ load balancing algorithms
- Sophisticated health checks (HTTP, TCP, Redis, MySQL, etc.)
- Cookie or IP-based persistence
Basic configuration:
frontend http_front
bind *:80
default_backend web_servers
backend web_servers
balance roundrobin
option httpchk GET /health
server web1 192.168.1.101:8080 check
server web2 192.168.1.102:8080 check
For complete HAProxy patterns, see references/haproxy-patterns.md.
Envoy
Best for: Microservices, Kubernetes, service mesh integration
Capabilities:
- Cloud-native design with dynamic configuration (xDS APIs)
- Circuit breakers, retries, timeouts
- Advanced health checks (TCP, HTTP, gRPC)
- Excellent observability
For complete Envoy patterns, see references/envoy-patterns.md.
Traefik
Best for: Docker/Kubernetes environments, dynamic configuration, ease of use
Capabilities:
- Automatic service discovery
- Native Kubernetes integration
- Built-in Let's Encrypt support
- Middleware system (auth, rate limiting)
For complete Traefik patterns, see references/traefik-patterns.md.
Kubernetes Ingress Controllers
Selection Guide
| Controller | Best For | Strengths |
|---|---|---|
| NGINX Ingress (F5) | General purpose | Stability, wide adoption, mature features |
| Traefik | Dynamic environments | Easy configuration, service discovery |
| HAProxy Ingress | High performance | Advanced L7 routing, reliability |
| Envoy (Contour/Gateway) | Service mesh | Rich L7 features, extensibility |
| Kong | API-heavy apps | JWT auth, rate limiting, plugins |
| Cloud Provider | Single-cloud | Native cloud integration |
Basic Ingress Example
apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
name: app-ingress
annotations:
nginx.ingress.kubernetes.io/ssl-redirect: "true"
nginx.ingress.kubernetes.io/affinity: "cookie"
spec:
ingressClassName: nginx
tls:
- hosts:
- app.example.com
secretName: app-tls
rules:
- host: app.example.com
http:
paths:
- path: /api
pathType: Prefix
backend:
service:
name: api-service
port:
number: 80
- path: /
pathType: Prefix
backend:
service:
name: web-service
port:
number: 80
For complete Kubernetes ingress examples and Gateway API patterns, see references/kubernetes-ingress.md.
Session Persistence
Sticky Sessions (Use Sparingly)
Cookie-Based: Load balancer sets cookie to track server affinity
- Accurate routing, works with NAT/proxies
- HTTP only, adds cookie overhead
IP Hash: Hash client IP to select backend server
- No cookie required, works for non-HTTP
- Poor distribution with NAT/proxies
Drawbacks: Uneven load distribution, session lost on server failure, complicates scaling
Shared Session Store (Recommended)
Architecture: Stateless application servers + centraliz