Load Balancing: Interview Preparation Guide

1. Load Balancing Algorithms

Load balancing distributes incoming traffic across multiple servers to optimize performance, reliability, and availability. Below are three common load-balancing algorithms:

Round Robin

• Requests are distributed sequentially across servers in a cyclic manner.
• Example: If there are three servers (A, B, C), the first request goes to A, the second to B, the third to C, and then the cycle repeats.
• Pros:
  • Simple and easy to implement.
  • Works well when all servers have equal capacity.
• Cons:
  • Doesn't consider server load, leading to potential performance bottlenecks.

Least Connections

• Directs new requests to the server with the fewest active connections.
• Pros:
  • Balances traffic more efficiently in environments where requests take variable processing time.
  • Prevents overloading a single server.
• Cons:
  • Slightly higher overhead due to real-time connection tracking.

Consistent Hashing

• Requests are routed based on a hash of the client’s IP address, request URL, or other identifying data.
• If a server is added or removed, only a subset of keys needs to be re-mapped.
• Pros:
  • Ideal for distributed caching (e.g., CDN, databases like Redis, or partitioned NoSQL systems).
  • Ensures users consistently reach the same server, reducing cache misses.
• Cons:
  • Can lead to uneven distribution if not implemented correctly.

2. How a Reverse Proxy Helps in Scalability

A reverse proxy is an intermediary server that forwards client requests to backend servers. It plays a crucial role in scalability and performance optimization.

How It Helps:

• Load Balancing: Distributes requests among multiple backend servers.
• Caching: Stores frequently accessed content, reducing backend load.
• SSL Termination: Handles SSL encryption and decryption, offloading work from backend servers.
• Compression: Reduces response size to optimize bandwidth usage.
• Security: Protects backend servers from direct exposure to the internet.

Popular Reverse Proxy Solutions:

• Nginx
• HAProxy
• Apache HTTP Server
• Traefik

3. What Is Sticky Session Load Balancing?

Sticky sessions (or session persistence) ensure that requests from the same client are always routed to the same backend server.

How It Works:

• A cookie-based or IP-based mechanism is used to track users.
• The load balancer maintains a mapping of client requests to a specific server.

When to Use It:

• Applications that require stateful sessions (e.g., shopping carts, user authentication sessions).
• When avoiding session replication across servers.

Challenges:

• Reduces fault tolerance since all user sessions are tied to a single server.
• Can cause uneven load distribution if some users generate significantly more traffic than others.

4. When to Use Global Load Balancing

Global Load Balancing (GLB) distributes traffic across multiple geographical regions or data centers.

When It’s Needed:

1. Disaster Recovery & High Availability: Ensures uptime even if one data center fails.
2. Latency Optimization: Routes requests to the closest or fastest data center.
3. Traffic Distribution: Prevents overloading a single region.
4. Compliance & Data Residency: Ensures user data stays in specific regions due to legal requirements.

Techniques Used:

• DNS-based Load Balancing (e.g., AWS Route 53, Cloudflare, Akamai)
• Anycast Routing: Routes users to the nearest available server.
• Geo-based Load Balancing: Directs users to a specific region based on their location.

5. Handling Failover in a Load-Balanced System

Failover ensures high availability by rerouting traffic if a server or region fails.

Strategies for Failover Handling:

1. Health Checks & Monitoring

   • Load balancers regularly check server health.
   • Unhealthy servers are automatically removed from the pool.
   • Tools: Prometheus, Grafana, ELK Stack.

2. Automatic Failover

   • If a server goes down, traffic is rerouted to healthy servers.
   • Example: Using DNS failover to redirect traffic to another region.

3. Active-Passive vs. Active-Active Failover

   • Active-Passive: A backup server remains idle until needed.
   • Active-Active: All servers handle traffic, redistributing requests dynamically in case of failure.

4. Session Replication & Database Failover

   • Sessions should be replicated across multiple servers to avoid data loss.
   • Databases should have read replicas or failover mechanisms like Amazon RDS Multi-AZ or PostgreSQL streaming replication.

5. Circuit Breakers & Retry Logic

   • Circuit breaker patterns (e.g., Netflix Hystrix) prevent overwhelming failed services.
   • Clients should implement exponential backoff retries to reduce load during failures.

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Conclusion

Load balancing is crucial for optimizing performance, ensuring high availability, and handling failovers efficiently. Understanding different algorithms, reverse proxies, sticky sessions, global load balancing, and failover strategies is essential for designing scalable systems. Mastering these concepts will help you ace system design interviews and build resilient applications.

Happy Learning! 🚀