🔧 Building a Feature-Rich Load Balancer in TypeScript: A Detailed Overview

Load balancers are essential components of modern distributed systems, ensuring scalability, fault tolerance, and optimal resource utilization. In this blog, we’ll explore the development and capabilities of a custom Load Balancer Implementation in TypeScript—a project that combines advanced load-balancing algorithms, health checks, self-healing mechanisms, and webhook notifications. This implementation mirrors the functionality of industry-standard tools like NGINX and HAProxy.

GitHub Repository

You can explore the complete project on GitHub: Load Balancer Implementation.

Key Features

1. Easy Configuration:
   
   Configure all aspects of the load balancer through a config.json file. This includes backend server details, health check intervals, and load-balancing algorithms.

2. Load Balancing Algorithms:

   • Random: Requests are sent to a randomly selected backend server.
   • Round-Robin: Requests are distributed sequentially among backend servers.
   • Weighted Round-Robin: Backend servers are prioritized based on assigned weights.

3. Health Checks:
   
   Periodic pings to backend servers ensure only healthy servers receive traffic.

4. Self-Healing:
   
   Automatically attempts to recover downed servers, with a configurable success rate.

5. Retries and Redirects:
   
   Failed requests are retried on alternative healthy servers.

6. Webhook Alerts:
   
   Notify administrators of server failures via custom webhook triggers. Alerts include:

   • Individual server failures.
   • Total backend server failure.

7. Scalability:
   
   The modular design allows for easy addition or removal of backend servers.

Project Structure

The repository contains the following components:

• Backend Server Simulation: Simulates multiple backend servers for load balancing.
• Load Balancer Core: Manages traffic, health checks, retries, and notifications.
• Configuration File: Allows users to define the behavior of the load balancer.

Getting Started

Prerequisites

1. Install Node.js and npm.
2. Clone the repository:

   git clone https://github.com/Ravikisha/Load-Balancer-Implementation.git
   cd Load-Balancer-Implementation
   npm install

Running the Application

1. Start Backend Servers: Run multiple backend servers on different ports using the command:

   npm run dev:be 8081
   npm run dev:be 8082
   npm run dev:be 8083

1. Launch the Load Balancer: Start the load balancer on the specified port:

   npm run dev:lb 8000

1. Send Requests: Use a tool like Postman or Curl to send HTTP requests to the load balancer at http://localhost:8000.

Testing and Monitoring

1. Simulate Backend Server Failures:

   • Kill a backend server process.
   • Observe automatic request redirection to other healthy servers.

2. Webhook Alerts:

   • Configure a webhook URL in config.json for real-time alerts.
   • Use services like Typed Webhook to test notifications.

3. Self-Healing:

   • Check the logs for attempts to restart failed servers.

Configuration Options

The config.json file governs the behavior of the load balancer. Key parameters include:

{
  "lbPORT": 8000,
  "_lbAlgo": "rr",
  "be_servers": [
    { "domain": "http://localhost:8081", "weight": 1 },
    { "domain": "http://localhost:8082", "weight": 1 },
    { "domain": "http://localhost:8083", "weight": 1 }
  ],
  "be_retries": 3,
  "health_check_interval": 30000,
  "send_alert_webhook": "https://webhook.site/your-webhook",
  "enableSelfHealing": true
}

• _lbAlgo: Choose between rand, rr, or wrr.
• be_servers: Define backend servers and their weights.
• send_alert_webhook: Specify a webhook URL for notifications.
• enableSelfHealing: Enable or disable server recovery attempts.

Insights and Learning Outcomes

Developing this load balancer provided insights into:

• Traffic Distribution Techniques: Understanding how different algorithms impact performance and fairness.
• Fault Tolerance: Designing systems that gracefully handle failures and recover automatically.
• Alerting Mechanisms: Using webhooks to keep administrators informed in real-time.
• Configuration Management: Simplifying user experience through JSON-based settings.

Challenges and Future Scope

Challenges:

• Ensuring low latency during health checks and retries.
• Managing detached processes spawned during self-healing.

Future Enhancements:

• Enhanced Health Checks: Add support for more complex health-check mechanisms.
• SSL/TLS Support: Enable secure communication between clients and backend servers.
• Dynamic Scaling: Integrate with cloud APIs to dynamically scale backend server pools.

Conclusion

This project demonstrates how a TypeScript-based load balancer can achieve features similar to enterprise-grade solutions like NGINX or AWS ELB. With robust fault tolerance, advanced load-balancing algorithms, and real-time alerting, this implementation serves as a practical example for developers looking to understand the inner workings of load balancers.

Explore the project on GitHub, try it out, and contribute to its future enhancements!