Next.js 16TypeScriptGoogle Gemini AIMongoDBRechartsnode-cronTailwind CSSCloudinaryFramer Motion
The Challenge
"Manually monitoring trends is time-consuming. Users require an automated solution that ingest large data streams and translates them into actionable visual insights."
Architectural Solution
Monolithic Next.js 16 (App Router) with a custom Node.js entry point to bypass serverless constraints for long-running cron tasks. Integrated with Google Gemini AI and MongoDB Atlas.
Engineering Deep Dive
An inside look at the structural decisions, trade-offs, and scaling plans devised during implementation.
Context & Constraints
- Trend Monitoring & Analytics.
- Data Visualization & AI Dashboard.
- Automated Background Workflows.
Architecture Trade-offs
Used a custom server.ts to support node-cron, which breaks standard serverless hosting compatibility but ensures robust background task execution.
Database Modeling
Document-oriented structure using Mongoose, featuring time-series collections for tracking trends alongside AI summaries.
Scaling Plan
Decoupling node-cron into a dedicated queue system (BullMQ) to allow the web app to scale independently on serverless edge networks.
Repository Insights
Initialized20 days ago
Last CommitRecently updated
Source Size2.95 MB
VisibilityPrivate