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gauravsingh1281 / Rentalog.in--Frontend

Rentalog || Free Rent Management Web App For Landlords. With Rentalog, landlords can keep track of important information about their renters, including their names, addresses, and rental payment history.
https://visionary-fenglisu-db1b1d.netlify.app/
MIT License
95 stars 251 forks source link

[FEATURE] To add load balancing feature #437

Closed Sivasaiklu closed 1 month ago

Sivasaiklu commented 1 month ago

🚀 Feature Request

Description
Load balancing is a technique used to distribute incoming network traffic across multiple servers to ensure no single server becomes overwhelmed. It improves the availability, scalability, and reliability of applications. By evenly distributing the load, servers can handle more requests efficiently, reducing response times and preventing downtime. Load balancing also supports failover by redirecting traffic from unhealthy servers to healthy ones, ensuring continuous service. Advanced load balancing features include session persistence, weighted distribution, and auto-scaling to adapt to varying traffic demands, making it a key component for optimizing system performance.

Problem Statement
As applications scale and user traffic increases, a single server may struggle to handle the growing load, leading to slow response times, service disruptions, or complete system failure. Without an efficient mechanism to distribute this traffic, server performance becomes a bottleneck, negatively impacting user experience and business operations. Additionally, if a server goes down, there is no fallback, causing downtime and loss of service. The challenge is to implement a load balancing solution that can dynamically distribute traffic, ensure high availability, support scaling, and provide seamless failover to maintain system reliability under varying traffic conditions.

Proposed Solution
Traffic Distribution Round Robin: The load balancer would distribute traffic across servers in a cyclical manner. For example, if there are three servers (A, B, and C), the first request goes to Server A, the second to Server B, the third to Server C, and then the cycle repeats. Example Behavior: Request 1 → Server A Request 2 → Server B Request 3 → Server C Request 4 → Server A (cycle restarts) Weighted Round Robin: Servers with higher performance can handle more requests. Server weights are adjusted based on capacity (e.g., Server A can handle twice the load of Server B). Example: If Server A has a weight of 2, and Server B and Server C have a weight of 1 each, the distribution would look like: Request 1 → Server A Request 2 → Server A Request 3 → Server B Request 4 → Server C Least Connections: Traffic is routed to the server with the fewest active connections. This ensures balanced load during times of high traffic. Example: If Server A has 5 connections, Server B has 3, and Server C has 1, the next request goes to Server C.

  1. Health Checks The load balancer periodically sends test requests (e.g., HTTP ping) to each server to ensure they are responsive. Example: If Server B stops responding to health checks, the load balancer automatically removes Server B from the pool and distributes traffic to the healthy servers. UI/Behavior Example: An admin dashboard shows the status of each server in the pool (Healthy, Unresponsive, etc.), and logs any server downtime or failures.
  2. Failover and Self-Healing In case of a server failure, the load balancer immediately reroutes traffic to other healthy servers. Once the failed server recovers and passes health checks, it is automatically re-added to the pool. Example: Request 1 → Server A Request 2 → Server B (fails during processing) Load Balancer detects the failure and retries the request on Server C.
  3. Session Persistence (Sticky Sessions) For applications that require session consistency (e.g., a logged-in user maintaining their cart), the load balancer can route requests from the same user to the same server. Example: User 1 logs in, their requests are sent to Server A. Subsequent requests from this user will continue to be routed to Server A until their session ends, ensuring consistent session data.
  4. Auto-Scaling and Cloud Integration The load balancer integrates with cloud services to automatically spin up new servers when traffic increases and shut down idle servers during low traffic periods. This ensures cost-efficiency and scalability. Example: During peak hours, if the existing servers are handling too many requests, the load balancer triggers auto-scaling to add more servers (Server D, Server E). When traffic drops, these servers can be removed to save costs.
  5. Geographic Load Balancing Users are routed to the server closest to their geographic location to reduce latency. Example: A user from Europe will be directed to a server in the EU region, while a user from the US will be directed to a server in North America. User Interface Example (for Admins): A dashboard that shows: The number of servers in the pool and their statuses (Healthy, Unresponsive, Active Connections). Real-time monitoring of incoming traffic and server utilization. Ability to manually add/remove servers from the pool, set weights, and configure health check intervals. Auto-scaling configuration options (e.g., trigger new instances if CPU utilization exceeds 80%). This feature will ensure that users experience minimal downtime, faster response times, and seamless failover, even during high traffic or server failures.

Checklist

github-actions[bot] commented 1 month ago

Congratulations, @Sivasaiklu! 🎉 Thank you for creating your issue for Rentalog. Your contribution is greatly appreciated and we look forward to working with you to resolve the issue. Keep up the great work! Should you have any queries or require guidance, do not hesitate to ask.