Why load balancers distribute traffic in HLD - Design It to Understand It

Design: Load Balancer Traffic Distribution

Focus on the role and design of load balancers in distributing traffic. Out of scope are detailed server implementations and client-side logic.

Functional Requirements

FR1: Distribute incoming client requests evenly across multiple servers

FR2: Ensure high availability and fault tolerance

FR3: Improve system scalability by adding or removing servers without downtime

FR4: Maintain low latency and fast response times

FR5: Handle sudden spikes in traffic gracefully

Non-Functional Requirements

NFR1: Support at least 10,000 concurrent connections

NFR2: API response time p99 under 200ms

NFR3: Availability target of 99.9% uptime

NFR4: Support both HTTP and TCP traffic

NFR5: Minimal single point of failure

Think Before You Design

Questions to Ask

❓ Question 1

❓ Question 2

❓ Question 3

❓ Question 4

❓ Question 5

Key Components

Load balancer (software or hardware)

Backend servers (application servers)

Health check system to monitor server status

DNS or service discovery for load balancer endpoints

Monitoring and logging tools

Design Patterns

Round-robin load balancing

Least connections load balancing

IP hash for session persistence

Active health checks and failover

Horizontal scaling of backend servers

Reference Architecture

Client
  |
  v
Load Balancer (distributes traffic)
  |
  +----> Server 1
  |
  +----> Server 2
  |
  +----> Server 3

Health Checks monitor servers and inform Load Balancer

Components

Load Balancer

Nginx, HAProxy, AWS ELB, or similar

Receives client requests and distributes them evenly to backend servers

Backend Servers

Application servers (e.g., Node.js, Java, Python)

Process client requests and return responses

Health Check System

Built-in load balancer health checks or external monitoring

Continuously checks server health to avoid sending traffic to unhealthy servers

DNS / Service Discovery

Route53, Consul, or similar

Directs clients to the load balancer endpoint

Monitoring and Logging

Prometheus, Grafana, ELK stack

Track traffic distribution, server health, and performance metrics

Request Flow

1. Client sends a request to the load balancer endpoint.

2. Load balancer receives the request and selects a healthy backend server based on the balancing algorithm.

3. Load balancer forwards the request to the selected backend server.

4. Backend server processes the request and sends the response back to the load balancer.

5. Load balancer forwards the response to the client.

6. Health check system continuously monitors backend servers and updates load balancer about server availability.

Database Schema

Not applicable as this design focuses on traffic distribution rather than data storage.

Scaling Discussion

Bottlenecks

Load balancer becoming a single point of failure under high traffic

Backend servers overwhelmed if traffic is not evenly distributed

Health check delays causing traffic to be sent to unhealthy servers

Latency increase if load balancer is overloaded

Solutions

Use multiple load balancers with DNS round-robin or anycast IP for redundancy

Implement auto-scaling for backend servers based on load metrics

Optimize health check frequency and timeout settings for faster failure detection

Use load balancer clustering or distributed load balancing solutions to share traffic load

Interview Tips

Time: Spend 10 minutes understanding requirements and clarifying constraints, 20 minutes designing the load balancer system and explaining components, 10 minutes discussing scaling and failure scenarios, and 5 minutes summarizing.

Explain why distributing traffic prevents server overload and improves availability

Discuss different load balancing algorithms and when to use them

Highlight the importance of health checks to avoid sending traffic to failed servers

Mention how load balancers enable horizontal scaling and fault tolerance

Address potential bottlenecks and realistic solutions to scale the system