Load balancing is a crucial component in distributed systems. It can balance the load of servers and improve system performance and reliability. This article will introduce how to use Python to implement an efficient load balancing architecture and provide the corresponding source code.
1. Background Introduction
In modern applications, it is usually necessary to handle a large number of concurrent requests. The goal of load balancing is to distribute these requests to the back-end server cluster to ensure that each server gets a relatively balanced load and provides high-performance and reliable services.
2. Load balancing algorithm
The load balancing algorithm determines how to select the backend server to handle requests. Common load balancing algorithms include round robin, random, weighted round robin and least connection.
Here we will use the least join algorithm as an example. This algorithm selects the server with the smallest number of current connections to handle new requests to achieve load balancing.
3. Python implementation
The following is an example of a simple load balancer implemented in Python:
import random
# 后端服务器列表
backend_servers = ['server1', 'server2', 'server3']
# 每个服务器的当前连接数<