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

Load balancers are an important element of modern distributed systems, ensuring scalability, fault tolerance, and optimal resource utilization. In this blog, we will explore the development and functionality of custom Load balancer implementation in TypeScript— A project that combines advanced load balancing algorithms, health checks, self-healing mechanisms, and webhook notifications. This implementation reflects the functionality of industry standard tools such as NGINX and HA proxy.

GitHub repository

You can explore the complete project on GitHub: Load balancer implementation.

Main features

1. Simple configuration:

   By configuring various aspects of your load balancer config.json document. This includes backend server details, health check intervals, and load balancing algorithms.

2. Load balancing algorithm:

   • Random: The request is sent to a randomly selected backend server.
   • Round robin: Requests are distributed sequentially among backend servers.
   • Weighted round robin: Backend servers decide the priority based on assigned weights.

3. Health check:

   Pinging your backend servers regularly ensures that only healthy servers receive traffic.

4. Self-healing:

   Automatically try to recover downed servers, the success rate can be set.

5. Retry and redirect:

   Failed requests will be retried on an alternate healthy server.

6. Webhook alert:

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

   • Individual server failure.
   • The backend server completely failed.

7. Scalability:

   Modular design makes it easy to add or delete backend servers.

Project structure

This repository contains the following components:

• Backend server simulation: Simulate multiple backend servers for load balancing.
• Load balancer core: Manage traffic, health checks, retries, and notifications.
• Profile: Allows the user to define the behavior of the load balancer.

getting Started

Prerequisites

1. Install Node.js and New project management.
2. Clone the repository:

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

Run the application

1. Start the backend server:
   Use the following commands to execute multiple backend servers on different ports:

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

1. Start the load balancer:
   Start the load balancer on the specified port:

   npm run dev:lb 8000

1. Send request:
   Use tools like Postman or Curl to route HTTP requests to the load balancer http://localhost:8000.

Test and monitor

1. To simulate a backend server failure:

   • Kill the backend server process.
   • Watch for automatic requests to be redirected to other health servers.

2. Webhook alert:

   • Configure webhook URL config.json for instant alerts.
   • Use similar services Typed Webhooks Test notification.

3. Self-healing:

   • Check the logs for attempts to restart the failed server.

Configuration options

this config.json Profiles control 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 rand, rror wrr.
• be_servers: Define the backend servers and their weights.
• send_alert_webhook: Specify the Webhook URL of the notification.
• enableSelfHealing: Enable or disable server recovery attempts.

Insights and Learning Outcomes

Developing this load balancer provided insights into:

• Traffic distribution technology: Understand how different algorithms affect performance and fairness.
• Fault tolerance: Design systems that handle failures gracefully and recover automatically.
• Alert mechanism: Use webhooks to keep administrators informed of the situation.
• Configuration management: Simplify the user experience with JSON-based settings.

Challenges and future scope

challenge:

• Ensure low latency during health checks and retries.
• Managing detachment processes that occur during self-healing.

Future enhancements:

• Enhanced health checks: Added support for more complex health check mechanisms.
• SSL/TLS support: Enable secure communication between clients and backend servers.
• Dynamic scaling: Integrates with cloud APIs to dynamically scale backend server pools.

in conclusion

This project demonstrates how a TypeScript-based load balancer can achieve similar functionality to enterprise-level solutions, such as NGINX or AWS elastic load balancing. With strong fault tolerance, advanced load balancing algorithms, and instant alerts, this implementation provides a practical example for developers who want to understand the inner workings of a load balancer.

Explore the project GitHubtry it out and contribute to its future enhancements!