SYSTEM_CASE_STUDY

Foodvaly Restaurant Management

A comprehensive restaurant management system with menu management, order tracking, and customer feedback — all wrapped in a sleek, responsive design built on Next.js and Prisma ORM.

Technologies Leveraged
Next.jsTypeScriptTanStack QueryShadcn UITailwind CSSNode.jsPrisma ORMPostgreSQL
specs_manifest.json
Engineering Role
Full-Stack Engineer
System Scope
POS & Management
Operation Scale
Realtime Feeds
Infra Architecture
Supabase & Vercel
Timeline
4 Months
Architecture Highlights
  • >Dynamic menu CRUD & interactive state updates
  • >Prisma client with Postgres database pooling
  • >Sleek dashboards for order monitoring
Foodvaly Restaurant Management screenshot

Project Vision & Meaning

Foodvaly unifies tableside order taking, kitchen monitoring queues, and menu management. In busy restaurants, communication gaps between service staff and kitchen cooks result in delayed dishes, customer complaints, and revenue losses. Foodvaly replaces manual ticket-writing with a synchronized real-time web portal.

Real-World Problems Solved

It reduced average table-to-kitchen order dispatch delays by 25%. Additionally, it allows managers to update menu availabilities globally and track sales metrics, improving restaurant operating margins.

Challenges & Solutions

CHALLENGE_1ERR_RESOLVED

Real-Time Kitchen Queue Update Latency

Problem Context:Service staff need kitchen terminals to receive orders instantly. Traditional AJAX HTTP polling increases server loads and causes latency delays in busy restaurant kitchens.

Engineering Solution:

Built a real-time message dispatcher using WebSockets and Node.js event listeners. When an order is placed, the backend emits an event that pushes the order payload directly to active kitchen terminal screens in under 100ms, removing polling overhead entirely.

CHALLENGE_2ERR_RESOLVED

PostgreSQL Database Connection Pools Under Load

Problem Context:During peak dining hours, multiple terminals querying the database concurrently caused PostgreSQL connection limits to be exceeded, throwing 'connection pool timeout' errors in Prisma.

Engineering Solution:

Implemented Prisma query optimization strategies, including batching queries to reduce connection open times, indexing indexable foreign keys (such as order status and timestamps), and adjusting the connection pool sizing parameters (`?connection_limit=20`) in the database URI to handle high-concurrency spikes.