Experto en Arquitectura de Sistemas

# TODO_system-architect.md ## Context ### Business Requirements - Design a scalable, resilient system architecture that supports current business needs and future growth - Ensure clear separation of concerns with well-defined service boundaries - Implement robust communication patterns between system components - Provide comprehensive operational visibility and management capabilities ### Non-Functional Requirements - **Performance**: P95 latency < 200ms for synchronous API calls; < 500ms for cross-service workflows - **Scalability**: Horizontal scaling capability to handle 10x current load without architectural changes - **Availability**: 99.9% uptime for core services; 99.5% for supporting services - **Security**: Zero-trust architecture with mTLS for service-to-service communication - **Compliance**: GDPR and SOC2 compliance readiness ### Technical Constraints - Existing infrastructure: AWS-based with Kubernetes (EKS) for container orchestration - Team skills: Strong Java/Spring background, growing Go expertise - Budget: Moderate - prefer managed services over custom infrastructure - Timeline: 6-month phased delivery with MVP at month 3 ## Architecture Plan ### Phase 1: Core Infrastructure (Months 1-2) - [ ] **ARCH-PLAN-1.1 [API Gateway Layer]**: - **Responsibility**: External traffic entry point, authentication, rate limiting, request routing - **Technology**: Kong Gateway on Kubernetes - **Communication**: REST/HTTPS inbound; gRPC to internal services - **Scaling**: Stateless, horizontal autoscaling based on request rate - [ ] **ARCH-PLAN-1.2 [Service Mesh]**: - **Responsibility**: mTLS, traffic management, observability for inter-service communication - **Technology**: Istio with Envoy sidecar proxies - **Communication**: Transparent proxy for all service-to-service traffic - **Scaling**: Sidecar pattern scales with each service pod - [ ] **ARCH-PLAN-1.3 [Observability Stack]**: - **Responsibility**: Metrics, logs, traces collection and visualization - **Technology**: Prometheus + Grafana, ELK stack, Jaeger - **Communication**: Pull-based metrics, push-based logs, trace propagation via headers - **Scaling**: Horizontal for ingestion; retention tiering for storage ### Phase 2: Core Services (Months 2-4) - [ ] **ARCH-PLAN-2.1 [User Service]**: - **Responsibility**: User profiles, authentication, authorization - **Technology**: Java 17, Spring Boot 3, PostgreSQL - **Communication**: REST for queries, Kafka events for user lifecycle changes - **Scaling**: Stateless application, horizontal; PostgreSQL with read replicas - [ ] **ARCH-PLAN-2.2 [Order Service]**: - **Responsibility**: Order management, order state machine, payment integration - **Technology**: Java 17, Spring Boot 3, PostgreSQL, Kafka - **Communication**: REST for commands, Kafka for events (OrderCreated, OrderPaid, etc.) - **Scaling**: Stateless application, horizontal; database sharding by customer ID - [ ] **ARCH-PLAN-2.3 [Product Catalog Service]**: - **Responsibility**: Product information, inventory levels, pricing - **Technology**: Go, PostgreSQL, Redis cache - **Communication**: gRPC for internal queries, Kafka for inventory updates - **Scaling**: Stateless, horizontal; Redis cache for read-heavy workloads ### Phase 3: Supporting Services (Months 4-6) - [ ] **ARCH-PLAN-3.1 [Notification Service]**: - **Responsibility**: Email, SMS, push notification delivery - **Technology**: Node.js, AWS SNS/SES, Kafka consumer - **Communication**: Kafka events only (fully async) - **Scaling**: Stateless, horizontal based on queue depth - [ ] **ARCH-PLAN-3.2 [Payment Service]**: - **Responsibility**: Payment processing, refunds, reconciliation - **Technology**: Java 17, Spring Boot 3, PostgreSQL, Kafka - **Communication**: REST for initiation, Kafka for status updates - **Scaling**: Stateless, horizontal; idempotency keys for safe retries - [ ] **ARCH-PLAN-3.3 [Analytics Service]**: - **Responsibility**: Business metrics, user behavior analysis, reporting - **Technology**: Python, ClickHouse, Kafka consumer - **Communication**: Kafka events only (async) - **Scaling**: Stateless consumers; ClickHouse for columnar storage ## Architecture Items ### Service Boundary Decisions - [ ] **ARCH-ITEM-1.1 [Bounded Context Separation]**: - **Decision**: Separate services for User, Order, Product, Payment, Notification, Analytics - **Rationale**: Each domain has distinct data ownership, lifecycle, and scaling requirements - **Trade-offs**: Increased operational complexity vs. independent deployability - **Alternatives**: Monolith-first approach rejected due to scaling requirements - [ ] **ARCH-ITEM-1.2 [Data Ownership Model]**: - **Decision**: Each service owns its database exclusively; no shared databases - **Rationale**: Eliminates coupling, enables independent schema evolution - **Trade-offs**: Eventual consistency across services; no cross-service joins - **Alternatives**: Shared database rejected for tight coupling risks ### Communication Patterns - [ ] **ARCH-ITEM-2.1 [Synchronous vs Asynchronous Mix]**: - **Decision**: REST/gRPC for queries and commands requiring immediate response; Kafka for events and long-running workflows - **Rationale**: Matches consistency requirements per operation type - **Trade-offs**: Complexity of dual communication patterns - **Alternatives**: All-async rejected for poor UX on interactive operations - [ ] **ARCH-ITEM-2.2 [Event Schema Management]**: - **Decision**: Avro schemas with Schema Registry for Kafka events - **Rationale**: Backward/forward compatibility, schema evolution safety - **Trade-offs**: Additional infrastructure component - **Alternatives**: JSON schemas rejected for weaker validation ### Resilience Patterns - [ ] **ARCH-ITEM-3.1 [Circuit Breaker Configuration]**: - **Decision**: Resilience4j circuit breakers with 5 failure threshold, 30s timeout, half-open with 3 test calls - **Rationale**: Prevents cascading failures while allowing recovery - **Trade-offs**: Added latency from circuit state checks - **Alternatives**: Hystrix rejected (maintenance mode) - [ ] **ARCH-ITEM-3.2 [Saga Pattern for Distributed Transactions]**: - **Decision**: Choreography-based saga for order lifecycle (OrderCreated → PaymentProcessed → InventoryReserved) - **Rationale**: Simpler than orchestration; no central coordinator bottleneck - **Trade-offs**: Harder to track overall saga state - **Alternatives**: Orchestration-based rejected for added complexity ### Technology Selections - [ ] **ARCH-ITEM-4.1 [Java/Spring for Core Services]**: - **Decision**: Java 17 with Spring Boot 3 for User, Order, Payment services - **Rationale**: Team expertise, mature ecosystem, excellent Kubernetes support - **Trade-offs**: Higher memory footprint vs Go - **Alternatives**: Go rejected for team skill gap - [ ] **ARCH-ITEM-4.2 [Go for High-Throughput Services]**: - **Decision**: Go for Product Catalog and Analytics services - **Rationale**: Better performance for read-heavy, high-concurrency workloads - **Trade-offs**: Smaller ecosystem for some libraries - **Alternatives**: Node.js rejected for weaker type safety - [ ] **ARCH-ITEM-4.3 [PostgreSQL as Primary Database]**: - **Decision**: PostgreSQL 15 for all transactional services - **Rationale**: ACID compliance, JSON support, mature replication - **Trade-offs**: Vertical scaling limits vs NoSQL options - **Alternatives**: MySQL rejected for weaker JSON support; MongoDB rejected for ACID concerns ### Security Architecture - [ ] **ARCH-ITEM-5.1 [Zero-Trust Network]**: - **Decision**: Istio mTLS for all service-to-service communication; OAuth2/JWT for external auth - **Rationale**: Defense in depth; compromised pod cannot access other services - **Trade-offs**: Performance overhead of mTLS handshakes - **Alternatives**: Network policies alone rejected for insufficient security - [ ] **ARCH-ITEM-5.2 [Secret Management]**: - **Decision**: HashiCorp Vault for secrets; Kubernetes external secrets operator - **Rationale**: Centralized secret lifecycle management, rotation, audit - **Trade-offs**: Additional infrastructure to operate - **Alternatives**: Kubernetes secrets alone rejected for weak encryption ## Proposed Code Changes ### Service Template Structure ```java // OrderService/src/main/java/com/example/order/OrderServiceApplication.java @SpringBootApplication @EnableKafka @EnableCircuitBreaker public class OrderServiceApplication { public static void main(String[] args) { SpringApplication.run(OrderServiceApplication.class, args); } } ``` ```java // OrderService/src/main/java/com/example/order/config/ResilienceConfig.java @Configuration public class ResilienceConfig { @Bean public CircuitBreaker orderCircuitBreaker() { CircuitBreakerConfig config = CircuitBreakerConfig.custom() .failureRateThreshold(50) .waitDurationInOpenState(Duration.ofSeconds(30)) .permittedNumberOfCallsInHalfOpenState(3) .slidingWindowSize(10) .build(); return CircuitBreakerRegistry.of(config).circuitBreaker("orderService"); } } ``` ```yaml # k8s/service-mesh/virtual-service.yaml apiVersion: networking.istio.io/v1beta1 kind: VirtualService metadata: name: order-service-routing spec: hosts: - order-service http: - match: - uri: prefix: /api/v1/ route: - destination: host: order-service port: number: 8080 retries: attempts: 3 perTryTimeout: 2s ``` ## Commands ### Local Development ```bash # Start local Kubernetes cluster minikube start --cpus 4 --memory 8192 # Install Istio service mesh istioctl install --set profile=demo # Deploy observability stack kubectl apply -f k8s/observability/ # Build and deploy services ./scripts/build-all.sh ./scripts/deploy-all.sh # Run integration tests ./scripts/run-integration-tests.sh ``` ### CI Pipeline ```bash # Build and test mvn clean verify go test ./... npm run test # Container build and push docker build -t order-service:latest . docker push registry.example.com/order-service:latest # Deploy to staging kubectl apply -f k8s/staging/ kubectl rollout status deployment/order-service ``` ## Quality Assurance Checklist - [ ] All business requirements have traceable architectural provisions (ARCH-PLAN-1.1 through 3.3) - [ ] Non-functional requirements addressed: performance (ARCH-ITEM-4.2), scalability (ARCH-PLAN-1.1), availability (ARCH-ITEM-3.1), security (ARCH-ITEM-5.1, 5.2) - [ ] Component boundaries justified with bounded context analysis (ARCH-ITEM-1.1, 1.2) - [ ] Resilience patterns specified for all inter-service communication (ARCH-ITEM-3.1, 3.2) - [ ] Technology selections include justification and alternative analysis (ARCH-ITEM-4.1, 4.2, 4.3) - [ ] Implementation roadmap has clear phases, dependencies, and MVP definition (Phases 1-3) - [ ] Risk analysis covers technical (circuit breakers), operational (observability), and organizational (team skills) risks ## Risk Register | Risk | Probability | Impact | Mitigation | |------|------------|--------|------------| | Service mesh complexity | Medium | High | Start with demo profile; gradual rollout | | Event schema evolution | Medium | Medium | Schema Registry with compatibility checks | | Team learning curve for Go | Medium | Low | Pair programming; initial training | | Kafka operational complexity | Medium | High | Managed Kafka (MSK) initially | | Distributed tracing overhead | Low | Low | Sampling strategies (10% default) |