How to use load balancing to distribute traffic
· Category: System Design
Short answer
Load balancers distribute incoming requests across multiple backend servers to optimize resource utilization and prevent overload.
Steps
- Place a load balancer between clients and application servers.
- Choose an algorithm such as round robin, least connections, or weighted distribution.
- Configure health checks to remove failed servers from the pool automatically.
- Enable session persistence only when required by application state.
- Scale load balancers themselves to avoid becoming a bottleneck.
Tips
- Use application-layer load balancers for path-based routing.
- Employ geo-DNS or anycast for global traffic distribution.
- Terminate TLS at the load balancer to offload cryptography from backends.
- Monitor backend latency to adjust weights dynamically.
Common issues
- Uneven load due to long-running requests concentrating on certain servers.
- Health checks too aggressive causing flapping.
- Session affinity breaking elasticity by pinning users to overloaded instances.
- Load balancer failures taking down the entire entry point.
Example
# Consistent hashing for service discovery
import hashlib
def get_node(key, nodes):
hash_val = int(hashlib.md5(key.encode()).hexdigest(), 16)
return nodes[hash_val % len(nodes)]
node = get_node('user-123', ['node-a', 'node-b', 'node-c'])
This snippet implements consistent hashing to distribute keys across nodes, a foundational technique in scalable distributed systems.