Expert en architecture système

# System Architecture Design for [Project Name] ## Context ### Business Requirements - **BR-1**: [Primary business objective] - **BR-2**: [Secondary business objective] - **BR-3**: [User-facing functionality] ### Technical Constraints - **TC-1**: [Infrastructure limitation] - **TC-2**: [Team skill constraint] - **TC-3**: [Budget/timeline constraint] ### Non-Functional Requirements - **NFR-1**: Latency target: [e.g., p95 < 200ms] - **NFR-2**: Throughput: [e.g., 10k requests/sec] - **NFR-3**: Availability: [e.g., 99.95%] - **NFR-4**: Security: [e.g., SOC2, GDPR compliance] ## Architecture Plan ### Phase 1: MVP Architecture - [ ] **ARCH-PLAN-1.1 [API Gateway]**: - **Responsibility**: Entry point for all client traffic; handles auth, rate limiting, request routing - **Technology**: [e.g., Kong, AWS API Gateway, NGINX] - **Communication**: REST/HTTPS; synchronous - **Scaling**: Stateless; horizontal scaling via load balancer - [ ] **ARCH-PLAN-1.2 [Core Service]**: - **Responsibility**: [Primary business logic] - **Technology**: [e.g., Node.js/Express, Python/FastAPI] - **Communication**: REST for queries; event publishing for state changes - **Scaling**: Stateless; horizontal scaling; auto-scaling based on CPU/memory - [ ] **ARCH-PLAN-1.3 [Data Store]**: - **Responsibility**: [Primary data persistence] - **Technology**: [e.g., PostgreSQL, MongoDB] - **Communication**: Direct DB connection (internal only) - **Scaling**: Stateful; primary-replica replication; read replicas for scaling - [ ] **ARCH-PLAN-1.4 [Cache Layer]**: - **Responsibility**: Caching frequent reads; session storage - **Technology**: [e.g., Redis] - **Communication**: Internal; accessed by services only - **Scaling**: Stateful; Redis Cluster for horizontal scaling - [ ] **ARCH-PLAN-1.5 [Message Queue]**: - **Responsibility**: Async communication; event streaming - **Technology**: [e.g., Kafka, RabbitMQ] - **Communication**: Async; publish-subscribe - **Scaling**: Stateful; partitioned topics for parallel consumption ### Phase 2: Extended Services - [ ] **ARCH-PLAN-2.1 [Notification Service]**: - **Responsibility**: Email/push notifications; template management - **Technology**: [e.g., Node.js, AWS Lambda] - **Communication**: Event-driven; consumes from message queue - **Scaling**: Stateless; event-driven scaling - [ ] **ARCH-PLAN-2.2 [Analytics Service]**: - **Responsibility**: Usage metrics; business intelligence - **Technology**: [e.g., Python, ClickHouse] - **Communication**: Event-driven; consumes from message queue - **Scaling**: Stateful; distributed processing ## Architecture Items ### Service Boundaries - [ ] **ARCH-ITEM-1.1 [Bounded Context: User Management]**: - **Decision**: Separate user management as independent service - **Rationale**: Distinct domain with own data lifecycle; high cohesion - **Trade-offs**: Additional service complexity; inter-service communication overhead - **Alternatives**: Keep within core service; rejected due to coupling and scaling conflicts - [ ] **ARCH-ITEM-1.2 [Bounded Context: Order Processing]**: - **Decision**: Order processing owns order data exclusively - **Rationale**: Transactional integrity; independent scaling during peak loads - **Trade-offs**: Eventual consistency for order status queries from other services - **Alternatives**: Shared database; rejected due to coupling risks ### Data Architecture - [ ] **ARCH-ITEM-2.1 [Data Ownership Model]**: - **Decision**: Each service owns its data; no cross-service DB access - **Rationale**: Prevents tight coupling; enables independent deployment - **Trade-offs**: Eventual consistency across service boundaries - **Alternatives**: Shared database; rejected as anti-pattern - [ ] **ARCH-ITEM-2.2 [Consistency Model Selection]**: - **Decision**: Strong consistency for financial transactions; eventual for user profiles - **Rationale**: Business requirements dictate consistency needs per domain - **Trade-offs**: Strong consistency limits horizontal scaling for those operations - **Alternatives**: Eventual everywhere; rejected for financial integrity ### Communication Patterns - [ ] **ARCH-ITEM-3.1 [Sync vs Async Communication]**: - **Decision**: REST for queries; events for state changes and cross-service workflows - **Rationale**: Queries need immediate response; state changes benefit from decoupling - **Trade-offs**: Eventual consistency for async paths - **Alternatives**: gRPC for internal; rejected due to team familiarity with REST - [ ] **ARCH-ITEM-3.2 [Event Schema Design]**: - **Decision**: Avro with schema registry; versioned events - **Rationale**: Backward compatibility; schema evolution without breaking consumers - **Trade-offs**: Schema registry adds operational complexity - **Alternatives**: JSON events; rejected due to weak typing and evolution issues ### Resilience Engineering - [ ] **ARCH-ITEM-4.1 [Circuit Breaker Implementation]**: - **Decision**: Circuit breaker on all inter-service HTTP calls - **Rationale**: Prevents cascading failures; fails fast when downstream is unhealthy - **Trade-offs**: Additional latency in healthy state (minimal) - **Alternatives**: No circuit breaker; rejected due to cascade risk - [ ] **ARCH-ITEM-4.2 [Retry Strategy]**: - **Decision**: Exponential backoff with jitter; max 3 retries - **Rationale**: Handles transient failures without overwhelming downstream - **Trade-offs**: Increased latency for retried requests - **Alternatives**: Fixed retry; rejected due to thundering herd risk - [ ] **ARCH-ITEM-4.3 [Bulkhead Isolation]**: - **Decision**: Thread pool isolation per downstream dependency - **Rationale**: One slow dependency doesn't exhaust resources for others - **Trade-offs**: Higher resource usage - **Alternatives**: Shared pool; rejected due to failure containment needs ### Security Architecture - [ ] **ARCH-ITEM-5.1 [Zero Trust Model]**: - **Decision**: mTLS between all services; JWT for user auth - **Rationale**: Defense in depth; no implicit trust within network - **Trade-offs**: Certificate management complexity - **Alternatives**: Network segmentation only; rejected due to insider threat risk - [ ] **ARCH-ITEM-5.2 [Data Encryption]**: - **Decision**: AES-256 at rest; TLS 1.3 in transit - **Rationale**: Compliance requirements; industry standard - **Trade-offs**: Performance overhead for encryption/decryption - **Alternatives**: No encryption; rejected for compliance ### Observability - [ ] **ARCH-ITEM-6.1 [Distributed Tracing]**: - **Decision**: OpenTelemetry with Jaeger backend - **Rationale**: End-to-end request visibility across service boundaries - **Trade-offs**: Tracing overhead; storage costs - **Alternatives**: No tracing; rejected due to debugging difficulty - [ ] **ARCH-ITEM-6.2 [Metrics Collection]**: - **Decision**: Prometheus with Grafana dashboards - **Rationale**: Industry standard; rich query language; alerting integration - **Trade-offs**: Operational overhead of running monitoring stack - **Alternatives**: Cloud-native monitoring; rejected due to portability needs ## Proposed Code Changes ### File: `docker-compose.yml` ```yaml version: '3.8' services: api-gateway: image: kong:3.4 ports: - "8000:8000" environment: KONG_DATABASE: postgres KONG_PG_HOST: kong-db depends_on: - kong-db core-service: build: ./services/core environment: DB_HOST: postgres REDIS_HOST: redis KAFKA_BOOTSTRAP: kafka:9092 deploy: replicas: 3 depends_on: - postgres - redis - kafka postgres: image: postgres:15 environment: POSTGRES_DB: core POSTGRES_USER: app POSTGRES_PASSWORD: ${DB_PASSWORD} volumes: - pgdata:/var/lib/postgresql/data redis: image: redis:7 command: redis-server --appendonly yes kafka: image: bitnami/kafka:3.5 environment: KAFKA_CFG_NODE_ID: 0 KAFKA_CFG_PROCESS_ROLES: controller,broker KAFKA_CFG_LISTENERS: PLAINTEXT://:9092,CONTROLLER://:9093 KAFKA_CFG_ADVERTISED_LISTENERS: PLAINTEXT://kafka:9092 KAFKA_CFG_CONTROLLER_LISTENER_NAMES: CONTROLLER KAFKA_CFG_LISTENER_SECURITY_PROTOCOL_MAP: CONTROLLER:PLAINTEXT,PLAINTEXT:PLAINTEXT KAFKA_CFG_CONTROLLER_QUORUM_VOTERS: 0@kafka:9093 volumes: pgdata: ``` ### File: `services/core/src/index.js` ```javascript const express = require('express'); const { createCircuitBreaker } = require('./resilience/circuit-breaker'); const { trace } = require('@opentelemetry/api'); const app = express(); app.use(express.json()); // Circuit breaker for downstream calls const downstreamBreaker = createCircuitBreaker({ failureThreshold: 5, timeout: 10000, resetTimeout: 30000 }); app.get('/api/v1/orders/:id', async (req, res) => { const span = trace.getTracer('core-service').startSpan('get-order'); try { const order = await downstreamBreaker.execute(async () => { // Fetch order logic return { id: req.params.id, status: 'active' }; }); span.setStatus({ code: 0 }); res.json(order); } catch (error) { span.setStatus({ code: 2, message: error.message }); res.status(503).json({ error: 'Service temporarily unavailable' }); } finally { span.end(); } }); app.listen(3000, () => { console.log('Core service listening on port 3000'); }); ``` ### File: `services/core/src/resilience/circuit-breaker.js` ```javascript class CircuitBreaker { constructor({ failureThreshold = 5, timeout = 10000, resetTimeout = 30000 }) { this.failureThreshold = failureThreshold; this.timeout = timeout; this.resetTimeout = resetTimeout; this.failureCount = 0; this.state = 'CLOSED'; // CLOSED, OPEN, HALF_OPEN this.nextAttempt = Date.now(); } async execute(fn) { if (this.state === 'OPEN') { if (Date.now() > this.nextAttempt) { this.state = 'HALF_OPEN'; } else { throw new Error('Circuit breaker is open'); } } try { const result = await Promise.race([ fn(), new Promise((_, reject) => setTimeout(() => reject(new Error('Timeout')), this.timeout)) ]); this.onSuccess(); return result; } catch (error) { this.onFailure(); throw error; } } onSuccess() { this.failureCount = 0; this.state = 'CLOSED'; } onFailure() { this.failureCount++; if (this.failureCount >= this.failureThreshold) { this.state = 'OPEN'; this.nextAttempt = Date.now() + this.resetTimeout; } } } function createCircuitBreaker(config) { return new CircuitBreaker(config); } module.exports = { createCircuitBreaker }; ``` ## Commands ### Local Development ```bash # Start infrastructure docker-compose up -d postgres redis kafka # Run core service locally cd services/core npm install npm run dev # Run tests npm test # Build and run with hot reload npm run build && npm run start ``` ### CI Pipeline ```bash # Lint and type check npm run lint npm run typecheck # Run unit tests with coverage npm run test:coverage # Build Docker image docker build -t core-service:${TAG} . # Run integration tests docker-compose -f docker-compose.test.yml up --abort-on-container-exit # Push image to registry docker push core-service:${TAG} ``` ## Quality Assurance Checklist - [ ] All business requirements (BR-1 through BR-3) have traceable architectural provisions - [ ] Non-functional requirements (NFR-1 through NFR-4) addressed with specific design decisions - [ ] Component boundaries justified with bounded context analysis - [ ] Resilience patterns specified for all inter-service communication - [ ] Technology selections include justification and alternative analysis - [ ] Implementation roadmap has clear phases, dependencies, and MVP definition - [ ] Risk analysis covers technical, operational, and organizational risks ## Risk Register | Risk ID | Description | Probability | Impact | Mitigation | |---------|-------------|-------------|--------|------------| | RISK-1 | Team unfamiliarity with event-driven patterns | Medium | Medium | Training sessions; pair programming; pilot implementation | | RISK-2 | Kafka operational complexity | Medium | High | Use managed Kafka service; infrastructure-as-code for config | | RISK-3 | Data migration during service extraction | High | High | Strangler fig pattern; dual-write strategy; rollback plan | | RISK-4 | Performance degradation from circuit breakers | Low | Medium | Tune thresholds; monitor latency metrics; load testing | ## Implementation Roadmap ### Phase 1: Foundation (Weeks 1-4) - [ ] Set up infrastructure (Kubernetes cluster, CI/CD pipeline) - [ ] Implement API Gateway with basic routing and auth - [ ] Deploy core service with CRUD operations - [ ] Set up monitoring (Prometheus, Grafana, Jaeger) ### Phase 2: Resilience (Weeks 5-8) - [ ] Implement circuit breakers on all inter-service calls - [ ] Add retry logic with exponential backoff - [ ] Implement event-driven communication via Kafka - [ ] Set up dead letter queues and alerting ### Phase 3: Scale (Weeks 9-12) - [ ] Implement horizontal auto-scaling - [ ] Add caching layer for read-heavy endpoints - [ ] Implement database read replicas - [ ] Load testing and performance tuning ### Phase 4: Hardening (Weeks 13-16) - [ ] Implement mTLS between services - [ ] Add comprehensive distributed tracing - [ ] Disaster recovery drills - [ ] Security audit and penetration testing