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πŸ‘¨β€πŸ’» Full-Stack & Systems Developer | Distributed Systems Builder

Hi, I'm Naman Arora πŸ‘‹

I enjoy building scalable backend systems, developer tools, and cloud-native applications.

Most of my work revolves around distributed systems, container orchestration, and developer infrastructure.

πŸš€ Current interests

  • 🧩 Designing microservices architectures
  • ☸️ Building systems on Kubernetes
  • 🐧 Working deeply with Linux & containerized environments
  • πŸ€– Building AI-powered developer tools
  • ⚑ Improving system reliability and observability

πŸ› οΈ Technical Stack

πŸ’» Languages

Python TypeScript C++ JavaScript


🌐 Web & Backend

Node.js NestJS React Next.js


πŸ—„οΈ Databases & Queues

PostgreSQL MongoDB Redis


☁️ DevOps & Cloud

Docker Kubernetes Linux GitHub Actions


πŸ“Š Observability

Prometheus Grafana Loki


πŸ“Š GitHub Stats

GitHub Streak


πŸ—οΈ Featured Projects

πŸ‘¨β€βš–οΈ Online Judge Platform

Architecture Diagram

πŸ”— https://github.com/naman22a/online-judge-platform

A scalable LeetCode-style Online Judge built using a distributed microservices architecture.

Tech Stack

React β€’ TypeScript β€’ NestJS β€’ PostgreSQL β€’ Redis β€’ Docker β€’ Kubernetes β€’ BullMQ

Key highlights

  • Designed a 7-service microservices architecture behind an API Gateway.
  • Built a secure code execution engine using Kubernetes Jobs to run untrusted code in isolated containers.
  • Implemented asynchronous submission processing using Redis + BullMQ workers.
  • Added reliability mechanisms including idempotent APIs, retry-safe execution, and dead-letter queues.

☸️ KubeSage β€” AI Kubernetes Debugging CLI

πŸ”— https://github.com/naman22a/kubesage

An AI-powered Kubernetes debugging CLI that analyzes cluster diagnostics and identifies root causes automatically.

Tech Stack

Python β€’ Kubernetes β€’ AWS β€’ LLM APIs β€’ CLI

Key highlights

  • Automatically detects issues like CrashLoopBackOff and OOMKilled.
  • Aggregates pod logs, events, and restart metrics for analysis.
  • Uses LLM-powered diagnostics to reduce investigation time from ~20 minutes to <2 minutes.

πŸ“¬ Connect With Me


⭐ I enjoy building systems that are reliable, scalable, and developer-friendly.

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