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Ravi Kishan
Ravi Kishan

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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.

Poster


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
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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
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  1. Launch the Load Balancer: Start the load balancer on the specified port:
   npm run dev:lb 8000
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  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
}
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  • _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!

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