Food Delivery Application built on Spring Boot Microservices + Azure Cloud

Here's a case study walkthrough for a Food Delivery Application built on Spring Boot Microservices + Azure Cloud, based on the architecture we just created:

🎯 Use Case: Customer Places an Order via Mobile App

👤 Persona:

• Name: Priya Sharma

• Role: End customer

• Intent: Browse restaurants, view menu, place an order, pay online, and track delivery

🛠 Step-by-Step Flow Using Microservices and Azure Services

1. App Launch & Login

• Priya opens the app and logs in using her email/OTP.

• User Service authenticates via Azure AD B2C.

• Session token is securely handled via Azure API Management + Istio.

2. Browse Restaurants

• API call is routed through API Management to the Aggregator Gateway.

• The Restaurant Service fetches data from Azure SQL (restaurants near her location).

• Optional: Redis cache can serve frequently accessed restaurants.

• Response is returned via Gateway → API Management → App.

3. Select Menu

• Priya taps on a restaurant.

• Request hits Menu Service (via API Gateway).

• Menu items and availability pulled from Azure SQL (possibly cached).

• App shows items in real-time.

4. Place Order

• Priya adds items to her cart and checks out.

• Order Service creates an order and stores it in Azure SQL.

• An event is published to Kafka/Event Hub – “Order Placed”.

5. Process Payment

• App redirects to payment.

• Payment Service integrates with a payment gateway.

• Upon success, another Kafka event is fired – “Payment Success”.

• Updates logged into Azure Monitor, and a record stored in SQL.

6. Assign Delivery

• Kafka triggers Delivery Service.

• Delivery is assigned using business logic (zone, distance).

• ETA is calculated (can use AI/ML model).

• Delivery tracking begins and data sent to client app.

7. Notifications

• Notification Service (SMS/Push/Email) sends order and tracking info.

• Uses Azure Communication Services.

• Events also sent to App Insights for auditing.

8. Live Order Tracking

• Customer sees driver location & ETA (polling or websocket-based).

• Delivery location updated via mobile device and published to Kafka.

9. Feedback Collection

• After delivery, Review Service prompts for rating.

• Ratings saved to SQL and insights fed to Analytics Dashboard.

10. Monitoring, Logs, and Alerts

• Every service logs to Azure Monitor and App Insights.

• Alerts configured for anomalies (e.g., payment errors, order failures).

• DevOps pipelines auto-deploy updates with traffic routed using Traffic Manager.

🔐 Security & Infra Notes

• All traffic secured via SSL @ Azure Load Balancer.

• Microservices isolated in AKS within VNet/Subnet, protected by NSG + Azure Firewall.

• Istio service mesh enforces mTLS and policy checks.

• All secrets and connection strings in Azure Key Vault.

📊 Dashboards & KPIs

• Orders per minute

• Delivery time SLAs

• Payment success rates

• Failed transactions

• Service latency via App Insights