Q53- What is load balancing, and how would you implement it?

Load balancing is the process of distributing incoming network traffic or requests across multiple servers to ensure no single server becomes overwhelmed, improving availability, reliability, and performance of applications.

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🔹 Why Load Balancing is Needed

• Prevents server overload during high traffic.
• Ensures high availability by redirecting traffic if a server fails.
• Improves response time by distributing load evenly.
• Supports horizontal scaling (adding more servers easily).

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🔹 Types of Load Balancing

1. Hardware Load Balancers: Physical devices (e.g., F5, Cisco).
2. Software Load Balancers: Nginx, HAProxy, or cloud-based (AWS ELB, Azure Load Balancer).
3. DNS Load Balancing: Uses DNS to distribute traffic across IPs.
4. Round-robin, Least Connections, IP Hash: Algorithms to decide which server gets a request.

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🔹 Implementation Example Using Nginx

1. Install Nginx and configure /etc/nginx/nginx.conf:

http {
    upstream backend_servers {
        server 192.168.1.101:3000;
        server 192.168.1.102:3000;
        server 192.168.1.103:3000;
    }

    server {
        listen 80;

        location / {
            proxy_pass http://backend_servers;
            proxy_set_header Host $host;
            proxy_set_header X-Real-IP $remote_addr;
        }
    }
}

Explanation:

• upstream backend_servers defines multiple Node.js servers.
• Nginx forwards incoming requests to these servers in a round-robin manner.
• Automatically balances load and improves reliability.

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🔹 Cloud-Based Load Balancing

• AWS Elastic Load Balancer (ELB):
  • Automatically distributes traffic across EC2 instances.
  • Supports auto-scaling and health checks.
• Azure Load Balancer / Google Cloud Load Balancer: Similar functionality.

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🔹 Key Points

• Always combine load balancing with health checks to avoid sending traffic to unhealthy servers.
• Choose the right algorithm:
  • Round-robin: Equal distribution, simple.
  • Least connections: Better for servers with variable load.
  • IP hash: Sticky sessions for user-specific data.
• Can be implemented at hardware, software, or cloud level.