harishraja1006/reverse-proxy-gateway-dashboard — explained in plain English
Analysis updated 2026-05-18
Study a working example of a round robin load balancer built in Python and Flask.
Run a local dashboard that shows request rates, response times, and backend health in real time.
Use the project structure as a starting point for building a custom reverse proxy with monitoring.
| harishraja1006/reverse-proxy-gateway-dashboard | 09catho/axon | abdulrdeveloper/react--tic-tac-toe | |
|---|---|---|---|
| Stars | 13 | 13 | 13 |
| Language | JavaScript | JavaScript | JavaScript |
| Setup difficulty | moderate | moderate | easy |
| Complexity | 3/5 | 4/5 | 1/5 |
| Audience | developer | researcher | developer |
Figures from each repo's GitHub metadata at analysis time.
Requires creating a Python virtual environment and manually starting three separate backend server scripts plus the load balancer.
This project is a reverse proxy gateway built with Flask, paired with a live monitoring dashboard made using Chart.js. In plain terms, a reverse proxy sits in front of several backend servers and spreads out incoming requests between them, so no single server gets overwhelmed. Here, that spreading is done using a round robin method, meaning requests are handed out to each backend server in turn, one after another. Alongside the proxy itself, the project ships a dashboard you can open in a browser to watch what is happening in real time. It shows things like how many requests each server is handling, whether each backend server is healthy, how fast servers are responding, and how traffic is being split across the cluster. There is also a live event log so you can see actions as they occur rather than digging through separate log files. The project is organized into three main parts: backend server scripts that simulate the servers receiving traffic, a load balancer module that does the actual request routing and health checks, and a dashboard module that serves the web interface and pulls in the live statistics. It is written in Python using Flask for the web and routing logic, with HTML, CSS, and JavaScript plus Chart.js handling the dashboard's charts and visuals. To run it, you create a Python virtual environment, install the listed dependencies, start the three backend server scripts, then start the load balancer itself, after which the dashboard becomes available in a browser. The author notes several planned additions that are not yet built, including switching between different scheduling algorithms, automatic failover if a server goes down, Docker and Kubernetes deployment support, login authentication, HTTPS, rate limiting, and integration with Prometheus and Grafana for more advanced monitoring.
A Flask-based reverse proxy that spreads requests across several backend servers, with a real-time Chart.js dashboard showing traffic and server health.
Mainly JavaScript. The stack also includes Python, Flask, Chart.js.
Use freely for any purpose, including commercial use, as long as you keep the copyright notice.
Setup difficulty is rated moderate, with roughly 30min to a first successful run.
Mainly developer.
This repo across BitVibe Labs
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