Principles and Implementation of Reverse Proxy and Load Balancing

Problem Description
Reverse proxy and load balancing are core components in modern backend architectures. A reverse proxy acts as a gateway for servers, receiving client requests and forwarding them to backend services; load balancing is responsible for distributing traffic reasonably across multiple server instances. Understanding their working principles is crucial for designing highly available systems.

Core Principles

1. Reverse Proxy: Sits between the client and backend servers, hiding real server information and providing a unified entry point.
2. Load Balancing: Distributes requests to multiple servers using specific algorithms to improve system throughput and reliability.

Implementation Details

Step 1: Basic Reverse Proxy Implementation

# Simple reverse proxy example
import http.server
import socketserver
import requests

class ReverseProxyHandler(http.server.BaseHTTPRequestHandler):
    backend_servers = ['http://localhost:8001', 'http://localhost:8002']
    
    def do_GET(self):
        # Select backend server (simple round-robin)
        backend = self.backend_servers.pop(0)
        self.backend_servers.append(backend)
        
        # Forward request
        resp = requests.get(f"{backend}{self.path}")
        
        # Return response to client
        self.send_response(resp.status_code)
        for key, value in resp.headers.items():
            self.send_header(key, value)
        self.end_headers()
        self.wfile.write(resp.content)

Step 2: Evolution of Load Balancing Algorithms

1. Round Robin:

class RoundRobinBalancer:
    def __init__(self, servers):
        self.servers = servers
        self.index = 0
    
    def get_server(self):
        server = self.servers[self.index]
        self.index = (self.index + 1) % len(self.servers)
        return server

2. Weighted Round Robin:

class WeightedRoundRobinBalancer:
    def __init__(self, server_weights):
        self.servers = []
        for server, weight in server_weights.items():
            self.servers.extend([server] * weight)
        self.index = 0
    
    def get_server(self):
        server = self.servers[self.index]
        self.index = (self.index + 1) % len(self.servers)
        return server

3. Least Connections:

class LeastConnectionsBalancer:
    def __init__(self, servers):
        self.server_connections = {server: 0 for server in servers}
    
    def get_server(self):
        return min(self.server_connections.items(), key=lambda x: x[1])[0]
    
    def release_connection(self, server):
        if server in self.server_connections:
            self.server_connections[server] -= 1

Step 3: Health Check Mechanism

import threading
import time

class HealthChecker:
    def __init__(self, servers, check_interval=30):
        self.servers = servers
        self.healthy_servers = set(servers)
        self.check_interval = check_interval
    
    def check_server(self, server):
        try:
            resp = requests.get(f"{server}/health", timeout=5)
            return resp.status_code == 200
        except:
            return False
    
    def start_checking(self):
        def check_loop():
            while True:
                for server in self.servers:
                    is_healthy = self.check_server(server)
                    if is_healthy and server not in self.healthy_servers:
                        self.healthy_servers.add(server)
                    elif not is_healthy and server in self.healthy_servers:
                        self.healthy_servers.remove(server)
                time.sleep(self.check_interval)
        
        thread = threading.Thread(target=check_loop)
        thread.daemon = True
        thread.start()

Step 4: Session Affinity (Sticky Sessions)

class SessionAwareBalancer:
    def __init__(self, servers):
        self.servers = servers
        self.session_map = {}  # session_id -> server
    
    def get_server(self, session_id=None):
        if session_id and session_id in self.session_map:
            return self.session_map[session_id]
        
        server = self.servers[len(self.session_map) % len(self.servers)]
        if session_id:
            self.session_map[session_id] = server
        return server

Step 5: Complete Implementation Example

class AdvancedLoadBalancer:
    def __init__(self, servers):
        self.servers = servers
        self.balancer = LeastConnectionsBalancer(servers)
        self.health_checker = HealthChecker(servers)
        self.session_balancer = SessionAwareBalancer(servers)
        self.health_checker.start_checking()
    
    def handle_request(self, request):
        # Check session stickiness
        session_id = request.cookies.get('session_id')
        if session_id:
            server = self.session_balancer.get_server(session_id)
        else:
            server = self.balancer.get_server()
        
        # Forward request
        self.balancer.server_connections[server] += 1
        try:
            return self.forward_request(server, request)
        finally:
            self.balancer.release_connection(server)

Key Technical Points

1. Connection Pool Management: Reuse backend connections to reduce overhead.
2. Timeout Control: Set connection and read timeouts to avoid blocking.
3. Failover: Automatically detect failed requests and retry with other servers.
4. Dynamic Configuration: Support adding/removing backend servers at runtime.

Practical Application Scenarios

• Nginx: Event-driven reverse proxy implementation.
• HAProxy: Professional TCP/HTTP load balancer.
• Cloud Services: Managed services like AWS ALB, GCP Load Balancer, etc.

This architecture significantly improves system availability and performance by distributing request pressure and enhancing fault tolerance.