Section Project: Cloud-Native E-Commerce Platform

Problem Statement

Modern e-commerce platforms must handle millions of transactions, provide real-time inventory updates, process payments reliably, and scale horizontally during peak demand. Traditional monolithic architectures struggle with these requirements.

Challenges:

  • High Availability: 99.99% uptime requirement
  • Scalability: Handle 10,000+ requests per second
  • Consistency: Distributed transactions across services
  • Observability: Track requests across multiple services
  • Resilience: Graceful degradation when services fail
  • Performance: Sub-100ms response times for critical paths

This project implements a production-ready microservices platform using all the patterns covered in this section.

Requirements

Functional Requirements

  1. Product Management

    • Browse product catalog with pagination
    • Search products by name, category, price range
    • View product details with real-time inventory
    • Cache frequently accessed products

  2. Order Processing

    • Create orders with multiple items
    • Validate inventory availability
    • Process payments with retry logic
    • Implement distributed transactions
    • Send order confirmation notifications

  3. Payment Processing

    • Integrate with payment gateway
    • Handle idempotent payment requests
    • Implement circuit breaker for external calls
    • Support payment retry with exponential backoff

  4. Notifications

    • Async event-driven notifications
    • Email/SMS notifications
    • Delivery guarantees with Kafka

Non-Functional Requirements

  1. Performance

    • API response time: < 100ms
    • Product search: < 50ms
    • Order processing: < 500ms end-to-end

  2. Scalability

    • Horizontal scaling for all services
    • Auto-scaling based on CPU/memory
    • Handle 10,000+ concurrent connections

  3. Reliability

    • 99.99% uptime SLA
    • Zero message loss
    • Automatic failover and recovery

  4. Observability

    • Distributed tracing across all services
    • Metrics collection
    • Centralized logging
    • Real-time dashboards

Constraints

  • Use Go 1.21+
  • gRPC for inter-service communication
  • REST API for external clients
  • Kafka for event streaming
  • Redis for caching
  • PostgreSQL for persistence
  • Kubernetes for orchestration

Design Considerations

System Architecture Overview

The platform consists of five core microservices orchestrated through an API Gateway:

API Gateway: Single entry point providing REST APIs, authentication, rate limiting, and request routing to backend services.

Product Service: Manages product catalog, inventory, and search functionality with Redis caching for frequently accessed products.

Order Service: Orchestrates order creation using the Saga pattern to coordinate distributed transactions across Product and Payment services.

Payment Service: Processes payments through external gateway with circuit breaker pattern for resilience and idempotency for reliability.

Notification Service: Consumes Kafka events and sends order confirmations via email/SMS.

Key Design Patterns

  1. Microservices Architecture: Services decomposed by business capability for independent scaling and deployment
  2. Saga Pattern: Orchestration-based distributed transactions with compensating actions for rollback
  3. Circuit Breaker: Prevents cascading failures when external services are unavailable
  4. API Gateway: Aggregates backend services and handles cross-cutting concerns
  5. Event-Driven Architecture: Asynchronous communication via Kafka for loose coupling
  6. CQRS Lite: Read-heavy operations use caching while writes go to primary database

Technology Stack Rationale

  • gRPC: High-performance inter-service communication with strong typing
  • Kafka: Reliable event streaming with at-least-once delivery guarantees
  • Redis: In-memory caching for sub-millisecond read latency
  • PostgreSQL: ACID transactions for critical business data
  • Prometheus + Jaeger + Grafana: Complete observability stack for metrics, tracing, and visualization

Acceptance Criteria

Your implementation is complete when it demonstrates:

Core Functionality:

  • All five services deploy successfully and pass health checks
  • REST API accepts product searches and returns results < 50ms
  • Complete order flow executes end-to-end
  • Saga rollback works when payment fails
  • Circuit breaker opens after consecutive payment gateway failures
  • Rate limiter blocks requests exceeding configured limits

Observability:

  • Distributed traces visible in Jaeger showing complete request flow across services
  • Prometheus metrics exposed on all services with custom business metrics
  • Grafana dashboards display service health, request rates, latencies, and error rates
  • Logs structured and include trace IDs for correlation

Reliability & Performance:

  • Services auto-scale based on CPU/memory using Horizontal Pod Autoscaler
  • System handles 10,000 requests/second in load tests
  • P95 latency < 100ms for order creation
  • Zero message loss in Kafka event delivery
  • Idempotent payment processing

Testing:

  • Unit tests with >70% code coverage
  • Integration tests verify service-to-service communication
  • End-to-end test creates order and verifies notification delivery
  • Load tests with k6 demonstrate performance requirements

Deployment:

  • Docker Compose starts all infrastructure and services locally
  • Kubernetes manifests deploy to local cluster
  • All ConfigMaps and Secrets properly configured
  • Services discoverable via Kubernetes DNS

Usage Examples

1. Start Local Development Environment

 1# Start all infrastructure services
 2docker-compose up -d postgres redis kafka jaeger prometheus grafana
 3
 4# Run database migrations
 5make migrate-up
 6
 7# Seed test data
 8make seed
 9
10# Start all services
11make run-all

2. Create a Product

 1# REST API
 2curl -X POST http://localhost:8080/api/v1/products \
 3  -H "Content-Type: application/json" \
 4  -H "Authorization: Bearer ${TOKEN}" \
 5  -d '{
 6    "name": "Wireless Mouse",
 7    "description": "Ergonomic wireless mouse with 3200 DPI",
 8    "price": 29.99,
 9    "sku": "MOUSE-001",
10    "inventory": 100,
11    "category": "Electronics"
12  }'
13
14# Response
15{
16  "id": "prod_1a2b3c4d",
17  "name": "Wireless Mouse",
18  "price": 29.99,
19  "sku": "MOUSE-001",
20  "inventory": 100,
21  "created_at": "2025-10-21T10:30:00Z"
22}

3. Search Products

 1# Search with filters
 2curl "http://localhost:8080/api/v1/products/search?q=mouse&category=Electronics&min_price=20&max_price=50&limit=10"
 3
 4# Response
 5{
 6  "products": [
 7    {
 8      "id": "prod_1a2b3c4d",
 9      "name": "Wireless Mouse",
10      "price": 29.99,
11      "inventory": 100
12    }
13  ],
14  "total": 1,
15  "page": 1,
16  "cache_hit": true
17}

4. Create an Order

 1# Create order with multiple items
 2curl -X POST http://localhost:8080/api/v1/orders \
 3  -H "Content-Type: application/json" \
 4  -H "Authorization: Bearer ${TOKEN}" \
 5  -d '{
 6    "user_id": "user_123",
 7    "items": [
 8      {
 9        "product_id": "prod_1a2b3c4d",
10        "quantity": 2
11      },
12      {
13        "product_id": "prod_5e6f7g8h",
14        "quantity": 1
15      }
16    ],
17    "shipping_address": {
18      "street": "123 Main St",
19      "city": "San Francisco",
20      "state": "CA",
21      "zip": "94102"
22    },
23    "payment_method": "credit_card",
24    "idempotency_key": "order_2025_abc123"
25  }'
26
27# Response
28{
29  "order_id": "ord_xyz789",
30  "status": "pending",
31  "total_amount": 89.97,
32  "created_at": "2025-10-21T10:35:00Z",
33  "saga_id": "saga_123"
34}
35
36# Behind the scenes:
37# 1. Validate inventory
38# 2. Reserve inventory
39# 3. Process payment
40# 4. Confirm order
41# 5. Publish order.created event
42# 6. Send notification

5. Check Order Status

 1curl http://localhost:8080/api/v1/orders/ord_xyz789 \
 2  -H "Authorization: Bearer ${TOKEN}"
 3
 4# Response
 5{
 6  "order_id": "ord_xyz789",
 7  "status": "confirmed",
 8  "user_id": "user_123",
 9  "items": [...],
10  "total_amount": 89.97,
11  "payment_status": "completed",
12  "payment_id": "pay_456",
13  "tracking_number": "TRK789012",
14  "created_at": "2025-10-21T10:35:00Z",
15  "confirmed_at": "2025-10-21T10:35:02Z"
16}

6. Monitor System Health

1# Prometheus metrics
2curl http://localhost:9091/metrics | grep -E "(request_duration|request_total|grpc_)"
3
4# Example metrics:
5# http_request_duration_seconds_bucket{method="POST",endpoint="/orders",le="0.1"} 450
6# http_request_total{method="POST",endpoint="/orders",status="200"} 1000
7# grpc_server_handled_total{service="product.v1.ProductService",method="GetProduct",code="OK"} 5000
8# redis_cache_hits_total{service="product"} 3500
9# redis_cache_misses_total{service="product"} 500

7. View Distributed Traces

Access Jaeger UI at http://localhost:16686:

Trace ID: 1a2b3c4d5e6f7g8h
Duration: 145ms

Spans:
├─ gateway: POST /api/v1/orders
│  ├─ order-service: CreateOrder gRPC
│  │  ├─ product-service: CheckInventory gRPC
│  │  ├─ product-service: ReserveInventory gRPC
│  │  ├─ payment-service: ProcessPayment gRPC
│  │  │  └─ payment-gateway: HTTP POST
│  │  ├─ postgres: INSERT order
│  │  └─ kafka: Publish event
│  └─ response serialization

8. Grafana Dashboards

Access Grafana at http://localhost:3000:

Overview Dashboard:

  • Total requests per second
  • Average response time
  • Error rate percentage
  • Active connections
  • CPU and memory usage

Service Dashboard:

  • Per-service request rates
  • gRPC method latencies
  • Cache hit rates
  • Database query times
  • Kafka lag

Business Dashboard:

  • Orders created per hour
  • Revenue per hour
  • Top selling products
  • Average order value
  • Payment success rate

9. Load Testing

 1# Run k6 load test
 2k6 run tests/load/k6/orders.js
 3
 4# Example output:
 5# scenarios: 1 scenario, 1000 max VUs, 5m30s max duration
 6# ✓ status was 200
 7# ✓ order created successfully
 8#
 9# checks.........................: 100.00% ✓ 120000  ✗ 0
10# http_req_duration..............: avg=45ms  min=10ms med=40ms max=250ms p(95)=85ms p(99)=150ms
11# http_reqs......................: 120000  2000/s
12# iteration_duration.............: avg=500ms min=450ms med=495ms max=750ms

10. Kubernetes Deployment

 1# Deploy to Kubernetes
 2kubectl apply -f deployments/kubernetes/namespace.yaml
 3kubectl apply -f deployments/kubernetes/configmaps/
 4kubectl apply -f deployments/kubernetes/secrets/
 5kubectl apply -f deployments/kubernetes/deployments/
 6kubectl apply -f deployments/kubernetes/services/
 7kubectl apply -f deployments/kubernetes/hpa/
 8kubectl apply -f deployments/kubernetes/ingress/
 9
10# Check deployments
11kubectl get pods -n ecommerce
12# NAME                           READY   STATUS    RESTARTS   AGE
13# gateway-7d8f9c5b4-abc12        1/1     Running   0          2m
14# gateway-7d8f9c5b4-def34        1/1     Running   0          2m
15# product-6c7d8e9f0-ghi56        1/1     Running   0          2m
16# product-6c7d8e9f0-jkl78        1/1     Running   0          2m
17# order-5b6c7d8e9-mno90          1/1     Running   0          2m
18# payment-4a5b6c7d8-pqr12        1/1     Running   0          2m
19# notification-3z4y5x6w7-stu34   1/1     Running   0          2m
20
21# Check HPA status
22kubectl get hpa -n ecommerce
23# NAME      REFERENCE            TARGETS         MINPODS   MAXPODS   REPLICAS
24# gateway   Deployment/gateway   45%/70%         2         10        2
25# product   Deployment/product   30%/70%         2         10        2
26# order     Deployment/order     55%/70%         2         10        3

Key Takeaways

Architecture Patterns

  1. Microservices Architecture

    • Service decomposition by business capability
    • Independent deployment and scaling
    • Technology diversity where beneficial

  2. Saga Pattern for Distributed Transactions

    • Orchestration-based saga implementation
    • Compensating transactions for rollback
    • Idempotency for reliability

  3. Circuit Breaker for Resilience

    • Prevent cascading failures
    • Automatic recovery detection
    • Graceful degradation

  4. API Gateway Pattern

    • Single entry point for clients
    • Request aggregation and transformation
    • Cross-cutting concerns

Production Engineering Practices

  1. Observability

    • Distributed tracing with Jaeger
    • Metrics collection with Prometheus
    • Visualization with Grafana
    • Structured logging

  2. Scalability

    • Horizontal pod autoscaling
    • Stateless service design
    • Caching for performance
    • Async processing with Kafka

  3. Reliability

    • Health checks and readiness probes
    • Graceful shutdown
    • Circuit breakers
    • Retry mechanisms

  4. Security

    • JWT authentication
    • Rate limiting
    • Secrets management
    • Network policies

Cloud-Native Principles

  1. Container-First Design

    • Docker for packaging
    • Multi-stage builds for optimization
    • Non-root users for security

  2. Kubernetes Orchestration

    • Declarative deployments
    • Service discovery
    • ConfigMaps and Secrets
    • Ingress for routing

  3. DevOps Integration

    • Infrastructure as Code
    • Automated testing
    • CI/CD ready
    • Monitoring and alerting

Next Steps

After completing this project, you have hands-on experience with:

  • Microservices architecture
  • gRPC and REST APIs
  • Event-driven systems with Kafka
  • Distributed transactions
  • Circuit breakers and resilience
  • Kubernetes deployment
  • Observability stack

  1. Enhance Observability

    • Add OpenTelemetry for vendor-neutral tracing
    • Implement distributed logging with ELK stack
    • Create custom SLIs and SLOs

  2. Improve Resilience

    • Add bulkhead pattern for resource isolation
    • Implement retry with exponential backoff
    • Add chaos engineering tests

  3. Scale Further

    • Implement CQRS pattern
    • Add event sourcing
    • Deploy to cloud

  4. Advanced Topics

    • Service mesh
    • GitOps with ArgoCD
    • Advanced Kubernetes patterns

Move to Capstone Projects

Ready for expert-level challenges? Explore the Capstone Projects section:

These projects build on everything you've learned and push you to expert-level distributed systems engineering.

Download Complete Solution

Download the complete implementation with full source code, tests, and deployment configurations:

Download Complete Solution

Package Contents:

  • All 5 microservices with complete implementations
  • Protobuf definitions and generated gRPC code
  • Kubernetes manifests for production deployment
  • Docker Compose for local development
  • Database migrations and seed data
  • Monitoring dashboards
  • Load tests
  • Comprehensive README with detailed setup instructions and implementation guide
  • ~5,500 lines of production-ready Go code

The README in the download package contains:

  • Detailed architecture diagrams and explanations
  • Complete project structure breakdown
  • Step-by-step implementation guide
  • Development and deployment instructions
  • Testing strategies and examples
  • Troubleshooting guide

Congratulations! You've completed the Production Engineering section by building a production-ready cloud-native e-commerce platform. You now have the skills to architect, build, and deploy enterprise-grade microservices systems.