TableFlow – Integrated Management System for Restaurant Chains

Integrated Management System for Restaurant Chains

7 members × 6 months

Team Structure

Requirements Definition / Design / Development / Testing / Deployment / Maintenance & Operations

• Backend: Go (Gin) / PostgreSQL / Redis / RabbitMQ

• Frontend: React / TypeScript / Flutter

• Real-time Communication: WebSocket / Socket.IO

• Payment Integration: PayPay / Credit Card / Bank Transfer

• Cloud: AWS (ECS / RDS / ElastiCache)

• Containerization: Docker

• Infrastructure as Code: Terraform

• GitHub Actions / Datadog / PagerDuty

• Instant order transmission from tablets to Kitchen Display System (KDS)

• Order processing latency under 800ms

• No delay even with simultaneous orders from multiple tables

• Supports cashless payments (e.g., PayPay)

• Fully compliant with Japan’s reduced tax rate & invoice system

• Automated and accurate tax calculations

• Eliminated paper tickets, significantly reducing order errors

• KDS visualizes cooking priorities

• Improved table turnover rate

• Live tracking of sales and order status

• Centralized management for both stores and headquarters

• Enables data-driven decision-making

• Reservation confirmation via LINE

• Helps prevent no-shows

• Unit Tests: 500+ cases (98% coverage)

• API Tests: Automated validation for 280 endpoints

• E2E Tests: Covers full flow from order to payment

• Load Testing: Verified for 200 tables simultaneously

• Production deployment only after passing all tests

• Automatic rollback on failure

• Rapid response to hotfixes

• Performance monitoring with Datadog

• 24/7 incident response via PagerDuty

ECS Fargate / RDS / ElastiCache

GitHub Actions

Datadog / PagerDuty

Staging environment mirrors production for full validation

• Achieved 99.97% uptime

• Order processing speed under 800ms

• Maintained zero tax calculation errors

Reduced order errors by 71%

• Increased table turnover rate by 23%

• Faster billing process (completed in seconds)

• Enabled real-time sales tracking

• Increased annual revenue by approx. ¥180 million (~$1.2M) across 8 stores

• Reduced annual operational costs by approx. ¥12 million (~$80K)

• Stable performance even during peak hours

• High accuracy in tax calculations

• Strong appreciation for zero-downtime deployment