Shankar Yadav’s Post

Today I spent 4 hours debugging a weird backend issue in my AI chatbot project — it taught me a powerful lesson about scaling with Node.js 🔥 While testing my React + Node + MongoDB chatbot app, I noticed the server CPU suddenly spiking and response times jumping from 180 ms to 500 ms. At first, I thought it was my OpenAI API calls. But after some deep logging, I realized the real culprit 👇 Every API request was re-initializing the MongoDB client instead of reusing a single instance. So the app was opening 100+ new connections in seconds — like calling the same friend 100 times just to say “Hi.” 😅 I fixed it by refactoring the code to use a singleton pattern for the DB client and adding a connection pool limit. ✅ After the fix: CPU dropped by ~40% Response time back to ~180 ms Stable performance across concurrent requests Lesson: Small inefficiencies in backend code can multiply massively at scale. Always check if your connections, instances, or API calls are reused efficiently — especially in microservice or AI-based systems. Why I’m Sharing: I’ve been rebuilding my stack from scratch — rural internet, small setup, and zero excuses. I post these learnings not just to share code, but to remind myself that consistency beats resources. If you’re working on React, Node, MongoDB, or AI projects and want to review your architecture or debug issues faster, I’m soon opening 1:1 sessions here 👉 topmate.io/shankar_yadav11 Would love to connect with: 💼 Recruiters hiring for remote full-stack roles 🧑💻 Developers sharing their #BuildInPublic stories 🎯 Learners restarting their tech journey #ReactJS #NodeJS #FullStackDeveloper #BuildInPublic #JavaScript #MongoDB #OpenAI #TechCareer

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